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AFBE 2012 CONFERENCE PAPERS (UNITEN) ISSN 1905-8055

TABLE OF CONTENTS Marziana Mohamad, Abdul Hadi Abdul Aziz, Muhammad Amir Zainuddin, Sheikh Mohd Iszuan Sheikh Mohd Zurid, ―Small Business Taxpayers‘ Behaviour, Belief and Perception of Fairness: Evidence From Tax Practitioners in Kuantan, Pahang‖ Azrinawati Mohd Remali, Zuraini Abdullah Zawawi, Adnan Abdul Hamid, Khairul Nizam Surbaini, ―A Study of The Approaches of Learning Among Accounting and Business Students in Higher Education Instituion.‖

3

14

Azleen Ilias, Mohd Zulkeflee Abd Razak, ―Do Final Year Accounting Students Experience Communication Apprehension (Ca)?‖

25

Azrinawati Mohd Remali, Zuraini Abdullah Zawawi, Adnan Abdul Hamid, Khairul Nizam Surbaini, ―A Study of The Approaches of Learning Among Accounting and Business Students in Higher Education Instituion‖

42

Eid M. Al_Mohammed, Basheer Abbas Al-alak, ―The Role of Digital Marketing in Higher Education Institutions (Heis): The Case of Saudi Arabia Students‘ University Selection in Malaysia‖ Fahmi Zaidi Bin Abdul Razak, Noor Azizah Binti Noorashid, Hussin Bin Salleh, Fairus Bin Ahmad, ―Examining Ucsa Student Portal Success from The Perspective of Modified De Lean Success Model‖

53

Fatimah Hanim Abdul Rauf, Che Wan Noraisyah Che Wan Mohamad Yusop, Lisa Fatin Mohd Izhar and Noor Farziani Mahamad Fazil, ―Corporate Governance and Timeliness oOf Corporate Internet Reporting by Malaysian Listed Companies‖

80

Hamidah Ramlan, Rositah Bakar, Ahmad Fairuz Bin Long, ―Impact of Exchange Rate Movement on Foreign Direct Investment Flows in Malaysia‖

92

Juliana Anis Ramli, Mohd Rizuan Abdul Kadir, Khairul Nizam Surbaini, Zulkifli Zainal Abidin, ―Perceptions Towards an Internship Program: An Empirical Study of Accounting Undergraduate Studentsi Malaysian Higher Education Institutions.‖

107

Khairul Nizam Surbaini, Abdul Rahman Zahari, Elinda bt Esa, ―Shopping Behavior And Determinant Factors Of Mall Patronage Among Gen Y.‖

121

Shahrul Nizam Salahudin, Suhaimi Sudin, Christine Cheah, Zuliawati Mohamed Saad, Nazia Newaz, ―Carbon Footprint Calculator: Exploring Carbon Emission Measurement Tool of Malaysion Telecommunications Industry‖

136

I

61

Mohd Rizuan Abdul Kadir, Norlaila Mazura Hj. Mohaiyadin, Mohamed Ariff Jame‘an, Muzrifah Mohamed, Norsheilla Maulad Jamaluddin, ―Relationship of Fraud Triangle Model and Academic Dishonesty: Some Malaysian Evidence‖

150

Nor Edi Azhar Binti Mohamad, Thilagavathi A/P Veloo, ―Firm Characteristics And Its Effect on Stock Return‖

161

Nor Razuana Binti Amram, Prof. Madya Dr. Angappan, ―Impact of Blockholder Ownership and Dividend Payout on Government-Linked Companies‘ (Glcs‘) Value in Malaysia‖

170

Noraina Mazuin Sapuan, Mohammad Rahmdzey Roly, ―Shuratic Process and Optimal Mudarabah Investment‖

184

Nurul Nadiah Ahmad, Nor Azam Mastuki, ―Industry Analysis of Accrual Management by Government Linked Companies (GLCs)‖

194

Siti Fara Binti Abd Razak, Mohd Zulkeflee Bin Abd Razak, Azleen Binti Ilias, ―Matching Male and Female Fund Managers with Different Types of Unit Trust Funds: A Malaysian Perspective‖

208

Irene Wei Kiong Ting, Hooi Hooi Lean, ―Testing Trade off Against Pecking Order Theory of Capital Structure In Malaysia‖

225

Hamidah Ramlan, Norfhadzilahwati Rahim, Azrol Syazuan bin Aziz, ―Capital Structure: Asset Tangibility, Profitability, Growth Opportunities and Firm Size Relation with Firm Debt (Properties Sector)‖

237

Masdiah Abdul Hamid, Norlaila Mazura Haji Mohaiyadin, ―Effectiveness of Audit Committee, Management Ownership and Malaysian Auditor Independence‖

251

Norfaizah Mat Nor, Maimun Abdullah, Noraina Ismail, Rositah Bakar, Siti Sarah Mohd Yusni, ―A Study on The Customer Awareness Toward Ar Rahnu Scheme at Sungai Buloh, Selangor.‖

268

Norfhadzilahwati Rahim, Hamidah Ramlan, ―The Relationship Between Exchange Rate and Economic Growth in Malaysia: Identifying Major Contributing Factors‖

280

Marziana Mohamad, Wan Mohammad Taufik Wan Abdullah and Mohmad Sakarnor Deris, ―Audit Delay and Accountability Index in Local Authorities: Cases from Kedah, Perak and Kelantan‖

293

Marziana Mohamad, Abdul Hadi Abdul Aziz, Muhammad Amir Zainuddin, Sheikh Mohd Iszuan Sheikh Mohd Zurid, ―Small Business Taxpayers‘ Behaviour, Belief and Perception of Fairness: Evidence from Tax Practitioners in Kuantan, Pahang‖

303

II

Nurul Nadiah Ahmad, Suraya Ahmad, ―Students‘ Judgment On The Ethicality In Earnings Management‖

314

Elinda Esa, Abdul Rahman Zahari, Inaliah Mohd Ali, ―Corporate Social Responsibility Disclosure in Malaysia: A Study of The Financial Sector‖

322

Norkhazimah Ahmad, Lee Kaye Vern, Muhammad Sufiyan Mohd Salleh, Toh Chin Zang, ―The Compliance of Governance and Transparency Index (Gti) in Malaysia : Evidence of The Plantation Sector‖

332

Inaliah Mohd. Ali, Elinda Esa, Abdul Rahman Zahari, ―Sustainable Development - Corporate Social Responsibility (Csr) and Shareholder Value: A Study of Government Linked Companies‖

343

Mohammed S. Al-Abed, Mohammed A. Adnan, ―Technology Transfer

353

Performance in Yemeni Oil Nd Gas Companies: A Conceptual Framework‖

Hussain Ali Bekhet, Tahira Yasmin, ―Economic Growth and Pollutant Emission In Malaysia: An Empirical Analysis of Environmental Kuznets Curve‖

369

Nor Salwati binti Othman, Nik Fanidautty Binti Nik Abdul Majid, Nor Hamisham Binti Harun, Muhammad Anuar bin Adnan, Mohmad Sakarnor bin Deris, ―Investigating The Prospect of Offering Master of Science in Sustainable Energy Management Programme at Universiti Tenaga Nasional (UNITEN), Malaysia.‖

387

Hussain Ali Bekhet, Ali Matar, ―Causality of Macroeconomic Variables Impacting The Stock Market Index: Time Series Approach in Amman Stock Exchange‖

397

Hussain Ali Bekhet, Nor Hamisham Binti Harun, ―Analyzing Elasticities and The Relationship Among Construction Production Determinants in Malaysia‖

418

Khairul Nizam Surbaini, Abdul Rahman Zahari, Elinda bt Esa, ―Shopping Behavior and Determinant Factors of Mall Patronage Among Gen Y.‖

430

Norlaila Mazura Hj. Mohaiyadin, Masdiah Abdul Hamid, Alhana Othman, ―Association of English Communication, Assessment Methods and Prerequisite Knowledge of Students Towards Accounting Students‘ Performance at Universiti Tenaga Nasional (UNITEN)‖

445

Norlaila Mazura Hj. Mohaiyadin, ―Relationship of Effective Teaching Methods and Instructor Characteristics Towards Accounting Students‘ Performance at Universiti Tenaga Nasional (UNITEN)‖

455

Abdul Rahman bin Zahari, Hamiza Bte Jamaludin, Adnan Bin Abd. Hamid, Othman Bin Chin, ―Inclination Factors of Entrepreneurship

464

III

Education Program: An Experience of Higher Learning Institution‖ Basheer Abass Al-Allak, Mohammed Abdulellah Yousuf Saeed, ―SMSBased Mobile Marketing in Malaysia Youth Market a Conceptual Approach‖

475

Nor Hamisham Binti Harun, Nor Salwati binti Othman, Nik Fanidautty Binti Nik Abdul Majid, Mohamad Sukiman bin Ishak, Muhammad Anuar bin Adnan, ―Exploring Awareness of Energy Usage Amongst Consumers in Klang Valley, Malaysia‖

486

Noor Raida Abd Rahman, Izyan Zahirah Bt Ishak, Nur-fadzrini Binti Ramali, ―Capital Structure and Environmental Reporting Practices of Malaysian Companies‖

494

Saeed (M.Z) A. Tarabieh, Basheer Abbas Al-alak, ―Customer Orientation, Supplementary Services, Differentiation Advantage, and Organizational Perforamce in The Banking Industry‖

509

IV

SMALL BUSINESS TAXPAYERS’ BEHAVIOUR, BELIEF AND PERCEPTION OF FAIRNESS: EVIDENCE FROM TAX PRACTITIONERS IN KUANTAN, PAHANG

Marziana Mohamad, Abdul Hadi Abdul Aziz, Muhammad Amir Zainuddin, Sheikh Mohd Iszuan Sheikh Mohd Zurid

College of Business Management and Accounting, Universiti Tenaga Nasional (UNITEN), Malaysia 09 - 455 2020 [email protected] College of Business Management Accounting, Universiti Tenaga Nasioanl (UNITEN), Malaysia [email protected] College of Business Management and Accounting, Universiti Tenaga Nasional (UNITEN), Malaysia [email protected] College of Business Management and Accounting, Universiti Tenaga Nasional (UNITEN), Malaysia [email protected]

ABSTRACT This paper investigates using a survey among tax practitioners, perspective of small business taxpayers‟ behavior, beliefs and perceptions of fairness towards tax compliance. First, it analyses the level of behavior, beliefs and perceptions of fairness among small business taxpayers. Second, it investigates the relationship between behavior, beliefs and fairness on its tax compliance. 200 questionnaires were distributed to tax practitioners in Kuantan, Pahang, only 113 agreed to participate (56.5 percent response rate). Descriptive statistics indicated that the level of taxpayers‟ behavior, beliefs and perceptions of fairness was at an average level of their tax compliance. Furthermore, correlation analysis also indicated that there are relationships between taxpayers‟ behavior, beliefs and fairness among small business taxpayers with tax compliance. Keywords: Behavior, Belief, Perception of Fairness, Tax Practitioners.

INTRODUCTION

Small and Medium Enterprises(SME) are subjected to income tax payable either as individuals or as corporate taxpayers depending on the business establishment. The taxation of both individuals and corporate businesses is governed by the Income Tax Act (ITA) (Malaysia) 1967. Business taxpayers are required by law to file an annual tax return correctly 5

(Section 77 and 77A; ITA 1967), to keep sufficient records and documentations (Section 82 and 82A; ITA 1967) and to observe other tax related requirements (Section 107, 107B, 107C and 108; ITA 1967). Compliance to the regulatory requirements is mandatory in nature, placing an enormous burden and cost upon the business sectors. Largely, international experiences often indicate the difficulties faced by the SMEs in managing government laws and regulations (Fernandez & Lynne (1998).

The issues faced by SME business in relation to regulatory costs are worldwide phenomena almost identical in the US, UK, Australia and New Zealand. These include a lack of understanding of the regulatory requirement, frequent changes in regulations and high fixed costs (Francis et al. (2003). The previous study done by Hanefah et al. (2001) indicated that the Malaysian business tax system appears to be becoming increasingly more complex, either due to major amendments being made to existing laws or a new assessment system. Therefore, tax complexity could be measured via tax compliance costs (Simon et al. (1998); Pope, (1992).

For the majority of taxpayers, tax practitioners were their sole source of support. The tax practitioners are people that taxpayers can trust to keep them on the right side of the law. Having the honest tax practitioners or adviser was the highest priority. Tan (1999) was reported that New Zealand suggesting the core important contribution is the tax practitioners make to taxpayers as a whole to given them confidence that their tax matters are under control and their tax paying behavior is lawful. Collins et al., (1990) and Hite and McGill (1992) indicated similar conclusions in their work in United States.

SME businesses interested in tax minimization were open to have tax practitioners who understand both low and high risk strategies. In addition, the emergency of two distinct factors represents tax minimization with conflict avoidance on one hand and tax minimizing with high risk on the other (Yuka and Valeria (2003). Marshall et al., (1998) conclude that diversity occurs among Australian tax practitioners in the ethical stances that they take. Tax practitioners appear to be successful in marketing their skills in a way that is suitable to the clients‘ needs or the other hand.

This study analyses the level of behavior, beliefs and perceptions of fairness among SME business taxpayers. Besides that, this study also investigates the relationship between behavior, beliefs and fairness on its tax compliance from the perspective of tax practitioners. LITERATURE REVIEW

Tax Behavior, Belief and Perception of Fairness Behavior is related with the observable human behavior. The Organization for Economic CoOperation and Development (OECD) (2010) organized a forum on tax administration for SMEs in understanding and influencing taxpayers‘ compliance. The behavior of the taxpayers is as a result of his or her personal norms and experiences related to a specific context which are social, economic, and environmental and society. Allingham and Sandmo (1972) 6

indicated that people are behaving in an economically rational way. The compliant and non compliant behavior is the results of a cost benefit calculation. People comply when the costs of evasion outweigh the benefits of evasion and do not comply when the balance tips with the other side. The opportunity for tax evasion or compliance has also a great impact on taxpayers‘ behavior. In terms of keeping evasion in check, strong empirical support can be found for limiting the opportunity that potential tax evaders have for avoiding paying tax. Braithwaite (2008) reported that a third party has also been shown to improve compliance, lending credibility to enforcement capacity in the process. Previous researchers found that a broader behavioral perspective has identified a large number of factors and drives that are associated with tax compliance. According to Umashanker Trivedi et al., (2005), attitudes relate to one‘s own personal views about the behavior. Based on the previous literatures, the present study is trying to test the following hypotheses: H1: There is a significant relationship between behaviors of SME business and tax compliance

Belief is referred to the personal statement based on assumed personal knowledge or facts such as tax rates are high or tax agents are essential to ensure correct lodgment. Based on the theory of reasoned action (TRA), attitudes are believed to have a direct effect on behavioral intention. Ajzen and Fishbein (1980) defined attitude as the degree to which an individual has a good or poor evaluation of a particular behavior. Attitudes are influenced by a belief on an outcome in which it uses degrees to measure the outcomes evaluation. Belief is underlined by subjective norms which refer to a normative belief. A normative belief is influenced by one‘s belief toward a referent or a referent group. In a study by Erten (2002), the behavior of the individual within the society is under the influence of defined factors, originating from certain reasons and emerging in a planned way.

The higher rates of tax compliance were found to be associated with the higher ethical attitudes (Chan et al.., 2000; Kasipillai et al. 2003). Henderson and Kaplan (2005) reported that the relationship between taxpayers‘ ethical beliefs and their tax compliance decisions is not simply direct and one dimensional. Besides that, having to pay high taxes and the belief that others are also not complying with tax obligations are also being perceived as reasons why taxpayers would not be likely to exercise tax compliance. The taxpayers who believe that most referents with whom he or she is associated are motivated to comply if they think they should not perform the behavior that will be perceived as social pressure to avoid performing that behavior. Halizah et al., (2011) reported that the general subjective norm is determined by the perceived expectation of specific referent individuals or groups to comply with all expectations. Therefore, the second hypotheses as follows: H2: There is a significant relationship between beliefs of SME business and tax compliance

Blissenden (2002) said that procedural fairness entails that administrations follow particular processes in ensuring that their decision making process is fair. Importantly, authorities 7

should treat SME taxpayers in a fair and respectful manner when undertaking such procedures, particularly when the taxpayers are committed to pay their tax.. Murphy (2004) reported that the reasons for taxpayers to abide by or disobey institutional decisions have been prominent in psychological research. The taxpayers‘ are willing to comply if they are treated in a respectful and fair manner by the authorities. Wenzel (2003) identified three different areas of fairness in relation to tax compliance. They are distributive justice, procedural justice and retributive justice. Tax procedures are neutral and are consistently applied to all and this will have a favorable impact on the perceptions of fairness by the taxpayers. Taxpayers who perceive unfair treatment from the tax authorities will decrease their level of compliance (Tan, (1998); Sheffrin & Triet, (1992); Spicer & Becker, (1980). Cristensen et al., (1994) indicated that fairness is difficult to define because of four problems which are that it is multidimensional, it can be defined at the individual level or for society at large, fairness is intertwined with complexity and lack of fairness may be perceived as justification for or a cause of noncompliance. Therefore, the third hypotheses as follows: H3: There is a significant relationship between perception of fairness of SME business and tax compliance

Tax Compliance and Tax Knowledge Previous researches indicate that tax knowledge is essential in order to increase the level of tax compliance (Richardson, (2006); Kirchler et al., (2008). Hence, it is very important to have knowledgeable and competent taxpayers. Park & Hyun (2003), suggest that tax education is one of the effective tools to induce taxpayers to comply more. In other words, taxpayers are more willing to comply if they understand the basic concept of taxation. For example, the level of tax compliance in Japan is high. The main reason for the high tax compliance in Japan is because of the efforts made by the Japanese National Tax Administration (NTA). The Self Assessment System was introduced in 1947 and plays an important role in the taxation learning process to taxpayers. To promote the principles of voluntary compliance, the Japanese tax authorities performed activities such as public relations, tax education, tax consultation, guidance and examination (Rani, (2005).In addition, tax knowledge will also reduce the potential for evasion. In a cross country study by Richardson (2006) towards 45 countries in the world, he found that education in general has a negative relationship with tax evasion, where the tendency to evade tax reduces with the level of education.

However, it is still questionable whether this general level of education will increase tax compliance. This is because in a study by Loo and Ho (2005) toward a group of salaried individuals in Melaka, Malaysia, they found that the taxpayers‘ competency level is quite low even though most of them have tertiary education. This is an alarming situation because it might impact on their readiness to exercise appropriate compliance under the new self assessment system (SAS). In a study by Junainah (2002) towards the implementation of SAS among individual taxpayers in Kota Kinabalu, Malaysia, she also finds that most of the taxpayers were unwilling to participate in SAS because of the burden that they have to face, especially in terms of completing atax return and calculating income tax payable. They were comfortable with the simplification of the formal system. In his book entitled ―Malaysian 8

Taxation under Self Assessment‖ Kasipillai (2007) emphasizes that knowledge about tax law is assumed to be of importance for preference and to determine the acceptance of the Self Assessment System (SAS).

RESEARCH METHODOLOGY

Data were collected from respondents consisting of tax practitioners in Kuantan, Pahang who are doing the tax audit and tax compliance for SME business. The list of tax practitioners‘ officers was provided by the Inland Revenue Board (IRB) in Kuantan, Pahang. This research has been carried out through questionnaires. According to Sekaran (2003), a questionnaires survey is a formulated written set of questions to which respondents‘ records their answers, usually from clearly defined alternatives. 200 questionnaires were distributed to tax practitioners, but only 113 agreed to participate (56.6 percent respond rate).

There are four operational variables which comprise one dependent variable and three independent variables as shown in Table 1: TABLE 1: VARIABLES MEASUREMENTS Measurement

Variables Dependent Variable Tax Compliance  Evidence from Tax Practitioners

The level of tax compliance

Independent Variable Behavior Belief Tax Fairness

The level of tax related of behavior The level of tax related of belief The level of tax related of fairness

RESULTS AND DISCUSSION

Frequency Analysis Table 2 presents the total numbers of respondents of tax practitioners in Kuantan, Pahang. In terms of gender, most of the respondents were female which was 79 percent (n=89) followed by male which were 21 percent (n=24). Then, in terms of ethnicity Malays were 84 percent (n=95), followed by Chinese 14 percent (n=16) and Indian 2 percent (n=2).

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2.1: Gender Male Female

TABLE 2: RESPONDENT PROFILES Frequency 24 89

2.2 Races Malay Chinese Indian Total

95 16 2 113

Percent 21 79

84 14 2 100

Descriptive Analysis Table 3 presents the level of behavior, beliefs and tax fairness among the SME taxpayers. Out of 29 questions we found that 7 questions have the highest level of behavior, beliefs and tax fairness among the SME businesses who answered ―agree‖. In term of the level of behavior, the highest mean was 3.42 which was ―My client should inform and declare their actual income received from all sources to the IRB or tax practitioners”, followed by “My client are afraid of tax audits and prosecution” which was 3.13. The third highest mean was “To enable a decrease in tax liability, my client required my firm to share knowledge with them” which was 3.07. In terms of level of beliefs, the first question shows the highest mean in answering ―agree‖ which was “My client believes that by joining training courses offered by professional bodies is a good idea”(3.13). Then the second answer was ―My client believes that my firm is helpful in assessing their organization‘s tax risk” (3.09) followed by ―My client believes that specific advice offered by any organization external auditor is important” (3.07). In terms of the level of tax fairness, only one question showed the highest mean of agreement which was ―For the SME business, I think that the income tax system is fair and reasonable‖ (3.05).

TABLE 3: SUMMARIES THE LEVEL OF BEHAVIOR, BELIEF AND TAX FAIRNESS

Factors

1 2 3 4

Behavior My client should inform and declare their actual income recieved from all sources to the IRB or tax practionners. My clients are afraid of tax audits and prosecution. To enables a decrease in tax liability, my client required my firm to share knowledge with them. My client would not feel guilty if they excluded some of their income when completing the tax return. 10

Mean

Std. Deviation

3.42

0.637

3.13

0.657

3.07

0.437

2.35

0.766

Since the suporting documents do not need to be sent to the 5 IRB, my client has opportunity to manipulate the figure in the tax return. It is ethically wrong if my client excludes small amount of 6 income when completing the tax return. Tax returns take too much effort, so my client put it off 7 unless there is an incentive. My client operational decision makers are required to 8 consider the tax effects of their decisions My client organization possesses sufficient expertise to 9 share knowledge with my firm Overall my client organizations gives an appropriate level 10 of attention to taxation matters

2.32

0.749

2.95

0.843

2.51

0.695

2.94

0.419

2.86

0.526

2.97

0.542

3.13

0.590

3.09

0.400

3.07

0.437

2.42

0.638

2.26

0.654

2.97

0.558

2.46

0.668

2.44

0.801

2.88

0.578

2.97

0.525

3.05

0.497

2.96

0.516

2.66

0.591

2.51

0.568

Belief My client believes that by joining training courses offered by professional bodies is a good course My client believes that my firm is helpful in assessing their 2 organizations tax risk My client believes that a specific advice offered by any 3 organization external auditor is important My client believe the tax authority has limited capability to 4 investigate all income reported to them. My client believes that the probabilities of being detected 5 by the tax authority for not declaring the exact income that they receive are low. By paying right amount of income tax, my clients believe 6 that other people especially the poor will get the benefit. My clients believe that the penalty is lower than their tax 7 saving due to not comply with tax laws. My clients believe preparing an income tax return is a low 8 priority in their business nature. My client feel that tax is an obligation and believing in no 9 corruption. My client believe that it is important for my firm to 10 participate in their business meetings, forums and boards. 1

1 2 3 4

Fairness For the SME business, I think that the income tax system is fair and reasonable The benefits my clients receive from the government in exchange for their income-tax payments are reasonable. Current tax laws require my client to pay more than their fair share of income taxes. Compared to the amount paid by bigger firm or company my client pay more than their fair share of income taxes. 11

5 6 7 8 9

A ‗fair‘ tax rate means it should be the same for everyone. High-income company or firm has a greater ability to pay income taxes, so it is fair that they should pay higher rate of tax than low-income tax earners. My client think that special provisions in the income tax law apply only to a few people are unfair. It is fair that high-income firm pay proportionately more tax than low-income firm. Generally my clients feel that the income tax is a fair tax.

2.56

0.777

2.92

0.703

2.60

0.750

2.96

0.441

2.89

0.469

Correlation Analysis Table 4 depicts the correlation between the level of behavior, beliefs and tax fairness with tax compliance. Based on the results from the respondents all independent variables have a significant relationship with tax compliance. First, in terms of the level of behavior, it has a significant relationship with tax compliance which had a p value less than 0.01 (correlation value -0.428). It shows that the evidence from the tax practitioners regarding the behavior of SME business is valuable. This is consistent with previous studies, for example Braithwaite (2008). Therefore, the alternate hypothesis (H1) is accepted.

Second, in terms of the level of beliefs also showed a significant relationship with tax compliance which had a p value less than 0.01 (correlation value -0.393). Third, in terms of the level of tax fairness also reported that it had a significant relationship with tax compliance which was a p value less than 0.001 (correlation value -0.424). The result showed that the higher rates of tax compliance were found to be associated with higher ethical attitudes (Chan et al., (2000); Kasipillai et al. (2003). Therefore, taxpayers‘ perception of the tax system was important because fairness and belief of the tax system would instill compliant behavior among SME taxpayers. Therefore, the alternate hypothesis (H2) and (H3) is accepted.

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TABLE 4: SPEARMAN’S RHO CORRELATIONS Mean Behavior

Mean Belief

Mean Tax Compliance Correlation -.428** -.393** Coefficient Sig. (2-tailed) 0.00 0.00 N 113 113 Mean Behavior Correlation 1.000 .663** Coefficient Sig. (2-tailed) 0.00 N 113 113 Mean Belief Correlation .663** 1.000 Coefficient Sig. (2-tailed) 0.00 N 113 113 Mean Fairness Correlation .627** .667** Coefficient Sig. (2-tailed) 0.00 0.00 N 113 113 **Correlation is significant at the 0.01 level (2-tailed)

Mean Fairness

Mean Tax Compliance

-.424**

1.000

0.00 113

113

.627**

-428**

0.00 113

0.00 113

.667**

-.393**

0.00 113

0.00 113

1.000

-.424**

113

0.00 113

RECOMMENDATIONS AND CONCLUSION

This study analyzes the level of behavior, beliefs and tax fairness among the SME business based on the perceptions of the tax practitioners. The perceptions of the tax practitioners is needed and the results indicate that they play an important role to provide the understanding of tax related behavior, beliefs and tax fairness among the SME businesses. For the majority of SME taxpayers were using the tax practitioners in calculating their tax returns and submitting them to the IRB by the due date.

Based on Section 77 of the ITA 1967, among the responsibilities of the taxpayers are to give full information of their taxable incomes, to submit their returns on time, to maintain proper records and to pay the accurate amount of tax. From the analysis conducted, it shows that all the SME taxpayers agreed that they should inform and declare their actual income received from all sources to the IRB. The tax practitioners were helpful to them in assessing their organization tax risk and believed the programs organized by the professional bodies were good and valuable. Based on the correlation analysis, all of the independent variables which were behavior, beliefs and tax fairness had a significant relationship with tax compliance. Therefore, all the hypotheses were accepted.

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This study, however, cannot be generalized to all SME taxpayers, since it was only conducted to the clients of tax practitioners in Kuantan, Pahang. Besides that, the questions of the level of behavior, beliefs and tax fairness were also restricted to evidence from tax practitioners only. In addition, the level of fairness was difficult to define because four problems which are multidimensional, it can be defined at the individual level or for society at large, fairness is intertwined with complexity and lack of fairness may be perceived as justification or a cause of noncompliance (Christensen et al., (1994).

REFERENCES Allingham, M.G., and Sandmo, A. (1972). Income Tax Evasion: A Theoretical Analysis. Journal of Public Economics, 1, 323-338 Braithwaite, V. (2008). Tax Evasion. Handbook on Crime and Public Policy, Oxford: Oxford University Press. Christensen, F., Saleem, K., and Panikkos, P. (1994). Tax Regulation and Small Business in the USA, UK, Australia and New Zealand. International Small Business Journal, 21(1): 93115. De Vaus, D. (2002). Analyzing Social Science Data (1st ed). London: Sage Publication Ltd. Fernandez, P and Lynne Oats (1998). The Small Business under a Goods and Services Tax Regime, In Tax Administration facing the challenges of the future, edited by C. Evans, and A. Greenbaum, 159-176.NSW: Prospect, 1998. Furnham, A. and Arfyle, M. (1998). The Psychology of Money, London. Routledge (FA) Hite, P.A., and McGill, G. (1992). An Exanimation of Taxpayers Preference for Aggressive Tax Advice, National Tax Journal, 45, 389-403 Income Tax Act (ITA) (Malaysia) 1967 Junainah, J. (2002). Sistem Tafsiran Sendiri: Satu Kajian Kes Tanggapan Pembayar Cukai Individu di Kota Kinabalu. Tesis Sarjana, UKM. Kasipillai, J. (2007). Malaysian Taxation under Self Assessment System. 2nd Edition. Kuala Lumpur: McGraw Hill Kasipillai, J., Noraza, M.U., and Zaimah, Z.A. (2003). How do Moral Values Influence Tax Compliance Behaviour? Finding from a Survey, The Charted Secretary Malaysia, June 2003. Kirchler,, E., Hoelzl, E., and Wahl., (2008). Enforced versus voluntary tax compliance: the ―slippery slope‖ framework. Journal of Economic Psychology 29, 210-225 Loo, E.C., and Ho, J.K.,( 2005). Competency of Malaysian Salaried Individuals in Relation to Tax Compliance under Self Assessment. http://www.austlii.edu.au/au/journals/eJTR/2005. eJlTaxR 3; (2005) 3(1) eJournal of Tax Research 47. Retrieved 4 February 2012.

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Marshall, R.L.,Armstrong, R.W., and Smith, M. (1998). The Ethical Environment of Tax Practitioners: Western Australian Evidence, Journal of Business Ethics, 17, 1265-1279 Organization for Economic Co-Operation and Development (OECD) (2010), Center for Tax Policy and Administration (CTPA): Understanding and Influencing Taxpayers Compliance. Ott, R.L. and Donnelly, D.P. (1999). Practitioners perceptions of the important of specific corporate tax knowledge for the new hires working in tax. Journal of Accounting Education, 17, 35-50. Park, C.G. and Hyun, J.K. (2003). Examination the determinants of tax compliance by empirical data: A case of Korea. Journal of Policy Modeling, 25, 673-684

Rani, J. S. (2005). SAS for Individuals: Preparing for effective management of tax matters. PricewaterhouseCoopers International Limited. www.pwc.co.za/en/tax/index.jhtml. Retrieved 4 February 2012. Richardson, G., (2006). Determinants of Tax Evasion: A Cross Country Investigation. Journal of International Accounting, Auditing & Taxation 15 . 150-169 Sekaran, U. (2003). Research Methods for Business: A Skill Building Approach, New York: John Wiley & Sons Spicer, M.W., and Lundsedt, S.B. (1976). Audit Probabilities and Tax Evasion Decision: An Empirical Approach. Journal of Economic Psychology, 2, 241-245 Tan, L.M. (1999). Taxpayers Preference for Type of Advice from Tax Practitioner: A Preliminary Examination, Journal of Economic Psychology, 20, 431-447

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A STUDY OF THE APPROACHES OF LEARNING AMONG ACCOUNTING AND BUSINESS STUDENTS IN HIGHER EDUCATION INSTITUION.

Azrinawati Mohd Remali (Leader) College of Business Management & Accounting, Universiti Tenaga Nasional (UNITEN) Bandar Muadzam Shah, Pahang, Malaysia Email: [email protected] Zuraini Abdullah Zawawi (Member) College of Business Management & Accounting, Universiti Tenaga Nasional (UNITEN) Bandar Muadzam Shah, Pahang, Malaysia Email: [email protected]

Adnan Abdul Hamid (Member) College of Business Management & Accounting, Universiti Tenaga Nasional (UNITEN) Bandar Muadzam Shah, Pahang, Malaysia Email: [email protected] Khairul Nizam Surbaini (Member) College of Business Management & Accounting, Universiti Tenaga Nasional (UNITEN) Bandar Muadzam Shah, Pahang, Malaysia Email: [email protected]

ABSTRACT

This study aims to investigate the differences in approaches of learning towards the academic performance between on Accounting and Business students. The Approaches and Study Skills Inventory for Students (ASSIST) was administered to the students in various universities in the East Coast Region, Malaysia; Accounting students (N=213) and Business students (N=178). Approaches to learning refer to; deep approach which is an approach where the students attempt to make sense of the subject area in a framework of ideas and concepts. A surface approach is characterized by memorization of information and procedures and relying on notes, passive memorization and academic anxiety. The result revealed that there a significant relationship between deep study approaches and academic performance among accounting students meanwhile there is also significant relationship (negative way) between surface learning with academic performance among business students.

Keywords: deep learning, surface learning, academic performance, accounting and business students.

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INTRODUCTION

This study investigates whether the approaches of learning between Accounting and Business students will affect their academic performance. Approaches to learning have been studied and describe the main way in which students engage with learning matter and how temporal matters surrounding the task are organized. The approaches to learning refer to how students tackle specific learning tasks and ―deep and surface approaches‖ has been identified as two different level of processing (Ballantine, Duff and Larres (2008)).

In order to help the students achieve the good performance in their result, this study researches about the students‘ studying and learning pattern. Davidson (2002) highlighted in his research the lack of knowledge in the approaches to learning and that this would will be a bottleneck to good performance in the examinations. Hence, this study investigates approaches to the learning strategy adopted by accounting and business students in Malaysia and its effect on academic performance.

The purpose of this study is to provide empirical evidence on the relationship between approaches of learning and academic performance and try to achieve the following objectives: (1) To investigate any relationship between approaches of learning and academic performance among accounting students and business students in the East Coast Region of Malaysia and (2) To determine any difference of approaches on learning based on demographic factors (gender & hometown).

The finding will provides useful information for educators and also for higher learning institution to promote effective learning strategies to the students in order to produce good quality of students by designing effective instructional strategies to facilitate learning. Yong and Lew (2005) stated that the key elements in getting the learners involved in learning lies in an understanding that leaning approaches can have an impact on their academic performance. In conclusion, this paper is concerned on how students study (approaches of learning) rather than what they study which will affect the academic performance (CGPA).

LITERATURE REVIEW

Deep and Surface Approaches to Learning According to Ballantine et al. (2008), students‘ approaches to learning (SAL) have drawn a distinction between two defining approaches to learning; namely a deep approach and a surface approach. Hassal and Joyce (2001) define a deep approach as where the students attempts to make sense of the subject area in a framework of ideas and concepts. The student will seek real meaning and be interested in the subject matter for its own sake. The deep approach student looks for meaning in the matter being studied and critically relates it to 17

other experiences and ideas. Meanwhile, a surface approach is characterized by memorization of information and procedures (relying on notes, passive memorization and academic anxiety). The student reduces what is to be learned to a list of facts that exist to be memorized – often failing to perceive the subject relevance and who might be motivated by fear of failure, for example in an exam (Hassal and Joyce (2001).

A study conducted by Davidson (2002) found that there was a significant relationship between the use of a ‗deep‘ study approach and grades received. They suggested encouraging the students to develop a deep study approach which may help them to improve their ability to work with more complex material. This is in line with the study done by Yong and Lew (2005) that found that the relatively higher scores of deep and achieving approaches to learning compared to the surface learning approaches for both youth and adult learners indicated that they used the deep learning approach to obtain the highest grades and to be model students. Duff et al. (2004) in their study found that the deep approach is positively associated with academic performance compared to the surface approach.

Warburton (2003) stated that deep learning is a key strategy by which to extract meaning and understanding from course material and experience. The author also mentioned that the challenge for educational institutions is not simply to teach the concrete facts about the environment but to create an active, transformative process of learning that allows values to be lived out and debated.

A number of studies have been conducted in educations, which demonstrate that deep learning approach can enhance students‘ academic performance (Ballentine 2008); Spencer (2003); Hassal & Joyce (2001)). Spencer (2003) concludes in her finding that a surface approach is associated with a less successful academic performance and a deep approach is associated with greater examination success and more enthusiasm for the subject. She suggested that the accounting educators should encourage a deep approach so that the students may become more proficient with complex material.

Other Factors Influencing Academic Performance

Previous research has related a number of factors to academic performance. Past academic performance as indicated by grades or CGPA is the factor most closely related to examination performance. Other factors are gender, motivation, effective learning strategies and others. Research done by Davidson (2002) found that motivation, past academic performance and gender – although the evidence is mixed also affect the performance. This is in line with the research done by Hassal & Joyce (2001) who also found that gender; domicile and study method will affect the students‘ performance. The impact of gender on academic performance has also been examined in many prior studies, but the results have been conflicting, perhaps as a result of student-instructor gender.

Ervina and Othman (2005) also found that knowledge prior to entering the university (such as in economics, mathematics and accounting) is crucial in assisting the students in undertaking 18

the course in both business and accounting programme. They also suggest that the female students perform better than male students; whilst Chinese students perform better than Malay and Indian students.

Lau and Chan (2001) found that the lack of effective learning strategies relate directly to poor performance. Pintrich and Roesser (1994) also found that learning strategy is among the important factors affecting students‘ academic performance. Duff et al. (2004) in their research also discuss that the relationship between personality and approaches to learning reveals significant impact on student performance in their study in university.

FIGURE 1 :METHODOLOGY

Deep Approach H1a, 1b Demographic Factors (Gender & Hometown)

Academic performance CGPA

H3

H2a, 2b

Dependent Variable

Surface Approach

Figure 1 summarises the theoretical framework of this study. There are two approaches of learning selected as independent variables namely, deep approaches and surface approaches. Meanwhile, the dependent variable is academic performance which is measured by cumulative grade point average (CGPA).

Dependent Variables This study uses the latest available students‘ CGPAs as the measure of academic performance which is widely used to measure this academic performance and as such is considered as appropriate and reliable to use. A good academic performance implies self-mastery and demonstration of student ability. It is chosen, for several reasons: grades are clearly the most common indicator of academic performance, CGPA is instrumental for graduation and can be considered a meaningful measure of students‘ performance, students are generally aware of

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their CGPA since they receive regular feedback throughout their academic lives, most of the literature is based on measurement of CGPA/GPA for students‘academic performance.

Independent Variable

Deep Learning Approach is an approach where the students attempt to make sense of the subject area in a framework of ideas and concept and the student will seek real meaning and be interested in the subject matter for its own sakes (Balletine et al. (2008)). Hence the study hypothesises that; H1a – There is a significant relationship between a „deep‟ study approach and accounting students academic performance. H1b - There is a significant relationship between a „deep‟ study approach and business students academic performance.

Meanwhile a surface approach is characterized by memorization of information and procedures for example relying on notes, passive memorization and academic anxiety. The students reduces what is to be learned to a list unconnected facts that exist to be memorized – often failing to perceive the subject‘s relevance and may be motivated by fear of failure, for example in an exam (Balletine et al. (2008)). Hence the study hypothesises that; H2a – There is a significant relationship between a „surface‟ study approach and accounting students academic performance. H2b – There is a significant relationship between a „surface‟ study approach and business students academic performance.

The study also aims to determine any differences of learning approaches based on demographic factors (i.e gender, year of study and hometown). There are mixed findings about differences regarding academic performance based on demographic factors. (Davidson (2002), Ervina & Othman (2005) & Hassal & Joyce (2001)). Hence, the hypothesis is; H3 – There is a significant relationship between demographic factors and a „deep‟ study approach and a „surface‟ study approach affecting academic performance (gender and hometown).

Data Collection

Students from various Higher Education Institutions from the East Coast Region participated in the study. Collecting data from two different courses but both from the social sciences in this study gave the possibility to study the correlation of approaches of learning towards the academic performance. Among the institutions are UNITEN, UiTM, Politeknik and UMP. 20

There were approximately about 500 of these students in the all targeted higher institutions. The analysis of data utilised the statistical package of SPSS version 18/19. In order to achieve the objectives stated earlier, several analyses and techniques were used for data testing for example the Spearman correlation, the Mann-Whitney test and data testing such as the reliability test and the normality tests.

Instrument and measures

The questionnaire was adopted and adapted from ASSIST originally developed by Entwistle et al. (2000) updated by Davidson (2002). The questionnaire was divided into two sections. The first section (Part A) was the ASSIST questionnaire consisting of 16 questions for the deep approach and 16 questions for the surface approach. Students were expected to indicate their agreement on a 5-point Likert scale (1 = agree, 2 = somewhat agree, 3 = neither agree nor disagree, 4 = somewhat disagree and to 5 = disagree). The second section (Part B) gathered personal information such as age, gender, place of study, course and etc. Table 1 presents the structure of the questionnaire used.

TABLE 1: STRUCTURE OF THE QUESTIONNAIRE Section Content Item Part A Approaches of Learning - Deep Approaches 16 - Surface Approaches 16 Part B General Question 6

RESULT AND DISCUSSION

Descriptive Results

A total of 213 accounting students and 178 business students took part in this study. Table 2 shows the distribution of collected questionnaires according to institutions studied. The questionnaire was distributed in class with instructors‘ supervision in order to make sure that the students answer all the questions.

TABLE 2: DISTRIBUTION OF STUDENTS ACCORDING TO INSTITUTION Institution Accounting Business UNITEN 146 129 UiTM 35 0 Politeknik 32 0 UMP 0 49 Total 213 178 21

Table 3 depicts the descriptive findings in terms of gender, Cumulative Grade Point of Average (CGPA) and hometown in recent semester. TABLE 3 : DEMOGRAPHIC DATA Demographic Factors Accounting Male 61 (26.8%) Gender Female 152 (71.4%) >3.5 25 (11.7%) 3.00-3.49 90 (42.3%) CGPA 2.5-2.99 86 (40.4%) 0.5). This finding supported the research by Tho (1999), who found that there was no influence on subsequent accounting performance between urban and rural students on academic performance. In addition, there was no significant difference 23

between males and females. This was supported by Carpenter et al. (1993) and Bartlett (1993) in their accounting studies who found that there was no significant difference in gender performance.

TABLE 6: COMPARISON BETWEEN APPROACHES OF LEARNING AND DEMOGRAPHIC FACTORS Deep Learning Surface Learning Gender 0.425 0.759 Hometown 0.374 0.536 *Significant at 0.05 level

CONCLUSION

The main objective of this study was to investigate the relationship between approaches of learning practiced by accounting and business students and to examine any influences of these approaches on the academic performance. The test used a sample of 391 students in various institutions in the East Coast Region. The results revealed that there were significant relationships between deep study approaches with academic performance among accounting students meanwhile there was a negative significance between surface learning with academic performance among business students. Meanwhile, there is no significant difference between the approaches of learning variables and all demographic factors tested (gender and hometown).

There were several limitation that should be highlighted here. First, there were various factor affecting academic performance. However, this study only considered approaches to learning. Future study should explore some other factors such as motivation, student behaviour, study environment and class activity. Second, it is also important to note that the generalisability of the results may be limited by the student population. This study merely considered the accounting students in learning institution in the East Coast Region. Future research should consider a wider group of students in order to have a reliable generalisation of the learning approaches of accounting students and business students.

This study will provides very information for educators and also higher learning institution to make changes in teaching strategies that can influence the learning approaches adopted by the students towards the desired approaches. Accounting instructors can encorage the students to develop a deep study approach as it appears to help them to become better at solving complex problems (Davidson (2002)). In addition to that, the implication for teaching is that educators should engage in a supportive roles in order to enhances‘ student learning approaches and maintain students‘ good academic performance. Finally, this finding is helpful to support instructional design of learning environments in order to cater to the students characterics in learning approaches.

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REFERENCES Ballantine, J. A., Duff A. and Larres P. M. (2008). Accounting and Business Students‘ Approaches to Learning: A Longitudinal Study. Journal of Accounting Education. Vol. 26 pp 188-201. Bartlett, S. M., Peel, J. and Pendlebury, M. (1993). From Fresher to Finalist: A Three-year Study of Student Performance on an Accounting Degree Program. Accounting Education : An International Journal. Vol. 2 pp 111-122 Carpenter, V.L., Friar, S. and Lipe, M.G. (1993). Evidence on the performance of accounting college-level financial accounting course, The Accounting Review. Vol. 63(1) pp 137-47. Davidson, RA. (2002). Relationship of study approach and exam performance. Journal of Accounting Education. Vol. 20 pp 29-44. Duff, A. (2004). The role of Cognitive Learning Styles in Accounting Education: Developing Learning Competencies. Journal of Accounting Education. Vol. 22 pp 29-52. Ervina, A & Othman, MN (2005). Undergraduate students‘ performance: the case of University of Malaya. Quality Assurance in Education. Vol. 13 pp 329-343. Field, A. (2007). Discovering Statistics using SPSS for Windows, Great Britain: SAGE Publications Ltd. Hassal, T & Joyce. J (2001). Approaches to Learning of management accounting students. Education +Training. Vol. 43 pp 145-152. Lau, K. L. and Chan, D. W. (2001). Motivational StyleCharacteristics of Under-Achievers in Hong Kong. Educational Psychology. Vol. 21(4) pp 417-430. Pintrich, P. R. and Roeser, R.W. (1994). Classroom and individual differences in early adolescents‘ motivation and self-regulated learning. Journal of Early Adolescence. Vol. 14(2) pp 139-162. Spencer, K. (2003), Education in a Changing Environment 17th – 18th September 2003, University of Salford. Tho, L M. (1999). Predicting Success In University Accounting Examination Performance. Jurnal Pendidikan, Vol. 20 pp 95-104. ISSN 0126-5261 Yong, ST & Lew, TY (2005). Deep learning approach among marketing students: Adult versus youth learner. Retrieved from www.herdsa.com. Warburton. K, (2003), Deep learning and education for sustainability. International Journal of Sustainability in Higher Education. Vol. 4 pp 44-56.

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Zhu, C., Valcke, M. & Schellens, T. (2008), A cross-cultural study of Chinese and Flemish university students: Do they differ in learning conceptions and approaches to learning? Learning and Individual Differences. Vol. 18 pp 120-127.

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DO FINAL YEAR ACCOUNTING STUDENTS EXPERIENCE COMMUNICATION APPREHENSION (CA)?

Azleen Ilias Department of Accounting-College of Business and Administration UNITEN-Campus Sultan Haji Ahmad Shah, 26700, Muadzam Shah, Pahang Malaysia [email protected] / [email protected] Mohd Zulkeflee Abd Razak Department of Marketing & Entrepreneur Development-College of Business and Administration UNITEN-Campus Sultan Haji Ahmad Shah, 26700, Muadzam Shah, Pahang Malaysia [email protected] / [email protected]

ABSTRACT The objective of this study is to identify the level of Communication Apprehension (CA) among final year accounting students particularly in Universiti Tenaga Nasional and to test the Personal Report Communication Apprehension (PRCA). The PRCA items are considered reliable to be adopted in the Malaysia scenario since the reliability analysis is aligned with McCroskey (1977). This study indicates more than 50% of the highest level of CA for the Generalized Context pertaining to four contexts in group discussions, meetings, interpersonal and public speaking. The main implication for educators is to develop and implement several strategies in teaching styles in reducing fear and anxiety among students.

INTRODUCTION

Background of the study

Nowadays, communication skill is considered to be one of the important skills needed to be developed by undergraduate students especially to find an opportunity in government and commercial industry. Most of employers are very concerned about the ability of communication skill in group discussions, conducting meetings, and interpersonal and public speaking. Lack of communication skill is one of reasons why employers are reluctant to hire job applicants. It can be supported by on a report in Malaysia Today ―Malaysia Has 60 000 Graduates Unemployed‖ (2005), due to lack of certain skills such as communication skill, poor command of English and lack of work experience. Lack of communication skill is due to fear, anxiety feelings and having less confidence that exists in some situation s when communicate with other people.. Based on McCroskey (1985), this feeling is called communication apprehension. He developed this concept of communication apprehension. The experience of fear and anxiety is considered a normal experience to everyone but in some circumstances it can be a major problem in order to communicate with other people.. 27

According to McCroskey, (1977, pp.78), communication apprehension is one of primary elements associated with poor communication skills development. Communication apprehension (CA) is an "individual level of fear or anxiety associated with either real or anticipated communication with another person or persons" (McCroskey, 1977,pp.78).

Problem statement

This study is looking into communication apprehension for students that can affect communication skills needed for employability in the future. Communication apprehension can be a problem for several conditions whenever anxiety and fear will affect a person‘s ability to communicate well such as in meetings, public speaking, and interpersonal and group discussions. These feelings will engage their intention and attitude to get into some communication situations whether encouraging or discouraging them to communicate.

A previous study by Albrecht & Sack (2000) indicated that accounting practitioners have stated that the accounting educational model is obsolete because this model is more about content knowledge and is less focused into skill development needed in order to be a more successful professional. Accounting practitioners and educators believe that the top five important skills are analytical/critical thinking, written communication, oral communication, computing technology and decision making.

According to previous evidence in newspaper online (Kang Soon Chen, April 15, 2012) that the Deputy Higher Education Minister Datuk Saifuddin Abdullah stated most students meet the criteria and qualification needed by employers but they are still lacking in communication skills. The Malaysian Employers Federation Executive Director Shamsuddin Bardan also mentioned that even in a good economic time there have been many unemployed graduates due to reluctance to interact and engage well in communication (Hariati Azizan, Sunday July 5, 2009). In addition, according to Kelly Services as a recruitment company explained that communication skills, problem solving, ability to participate in decision making, people management and strategic thinking are the top five skills in employability demand (Jagdev Singh Sidhu, February 12, 2001). Even though graduates have fulfilled their qualifications and are equipped with theoretical knowledge they also need to overcome their lack of soft skills. In a report from the United Nations Educational, Scientific and Cultural Organization (UNESCO (2012), the employers have voiced out to the Ministry of Higher Learning Education (Malaysia) that universities have produced a bunch of graduates with less of good quality supply to the market. According to Graduate Employability in Asia (2012), the good quality criteria refers to the adequacy of self-confidence and soft-skills particularly competence in communicating in the English language, focus and commitment.

RESEARCH OBJECTIVES

Studies done on communication apprehension particularly for final year accounting students is rarely found. Researchers need to find out the level of communication apprehension among final year accounting students in order to improve the style of teaching and learning in class 28

for communication skills development. Thus, the educators can provide better teaching, learning and facilitating students and enhance soft skills in course syllabi and programmes in order to reduce fear and anxiety in developing communication skills such as in meetings, group discussions, and interpersonal and public speaking. Therefore, this study is done in order: To describe the level of overall and subscore communication apprehension among final year accounting students particularly in Universiti Tenaga Nasional. To test the Personal Report Communication Apprehension (PRCA) theory by McCroskey (1977) by relating overall communication apprehension to subscore communication apprehension (group discussions, meetings, interpersonal and public speaking) among final year accounting students particularly in Univesiti Tenaga Nasional.

RESEARCH QUESTIONS Descriptive Questions: RQ1: What is the level of overall communication apprehension among accounting students? RQ2: What is the level of communication apprehension in group discussions, meetings, interpersonal and public speaking among accounting students?

Relationship Questions: RQ3: How strong the level of communication apprehension in group discussions, meetings, interpersonal and public speaking related to overall communication apprehension among accounting students? SIGNIFICANT CONTRIBUTION The study aims to contribute to the existing body of knowledge in the area of communication skills, communication apprehension and soft skills in education. Further, the study provides the constructs to measure and evaluate the Personal Report Communication Apprehension (PRCA) test. Theoretically, this study measures and validates the instrument of McCroskey (1977). In addition, research evidences from the current study will be able to suggests and recommend to the educators, lecturers, and everyone that is involved in education sectors to implement several actions and teaching styles in reducing fear and anxiety among students since their early stages in the university. Thus, the graduates will be well equipped and competent with knowledge, generic skills and soft-skills particularly needed by the Malaysian Institute of Accountant (MIA) in implementing MIA Chartered Accountant‘s Relevant Experience (CARE). Overall, the good quality graduates will contribute to the Ministry of Higher Education (MOHE). This paper continues with a literature review in discussing and elaborating of communication apprehension. Next, the research design includes a research framework, sample, 29

instrumentation and data collection are presented. This is followed by quantitative analysis and the findings are discussed using descriptive analysis, reliability analysis, and correlation. The final part concludes the study and provides suggestions for further research.

LITERATURE REVIEW

Communication Apprehension (CA) CA is ‗an individual‘s level of fear or anxiety associated with either real or imagined communication with another person or persons‘ (McCroskey,(1977,pp.78). Within this context, it is important to distinguish CA from other constructs similar in definition identified in the literature that include reticence, shyness, unwillingness to communicate, introversion, and social anxiety. (Berger et al..(1983); Henjum (1982); Leonard and Johnson (1998).

Communication Apprehension Contexts

McCroskey (1970) advanced the construct of CA, he made no explicit mention of whether it is a trait of an individual or a response to the situational elements of a specific communication transaction (a state). The distinction is important because of its implications for possible intervention strategies to modify levels of CA. McCroskey (1984a) believes the trait/state distinction is a false dichotomy. To view all human behaviour as emanating from either a trait-like, personality orientation of the individual or from the state-like constraints of a situation ignores the interaction of these two sources.

Trait-like CA

A true trait is an invariant characteristic of an individual, such as eye colour and height. Traits-like personality variables, although highly resistant to change, can be and often are changed during adulthood. There is substantial research on treatment of people identified as having high CA that suggests CA can be changed (Condit, (2000), Beatty et al., (1998); and Opt and Loffredo,(2000)for recent views that CA may be a fairly stable personality trait that is not easily subject to change). Trait-like CA is viewed as a relatively enduring, personalitytype orientation toward a given mode of communication across a wide variety of contexts (McCroskey, 1984,pp.18). Generalised-Context CA

Generalised-Context CA viewed from this perspective represents orientations toward communication within generalisable contexts. Fear of public speaking (stage fright), the oldest of the CA conceptualisations, is an example. This view recognises that people can be 30

highly apprehensive about communication in one type of context while having less or no apprehension in another context. CA is viewed as a relatively enduring, personality-type orientation in a given type of context. McCroskey (1984a) identifies four classic types of CA context: public speaking, speaking in formal meetings, speaking in small group discussions, and speaking in dyadic interactions (i.e. conversations). Causes of Generalised-Context CA

The causes of situational CA appear much clearer than those offered for trait-like CA.Buss (1980) suggests that the major elements in the situation that can result in increased CA are novelty (increased uncertainly about behaviour); formality (narrower confines for acceptable behaviour); subordinate status (appropriate behaviour is in the hands of the superior); conspicuousness (new social settings or standing up to speak in a class or meetings); unfamiliarity (more comfortable when communicating with whom they are familiar); dissimilarity (with audience); and degree of attention from others (moderate attention is the most comfortable, but being stared at intently or ignored is uncomfortable). Two other elements are suggested by work from Daly and Hailey (1983). These are the degree of evaluation (more anxious if evaluation is occurring) and prior history (success breeds success but, conversely, prior failure will result in fear of failure and increased apprehension).

Communication Apprehension in Accounting

There have been a small number of studies investigating CA in accounting students ( Stanga and Ladd, (1990); Ruchala and Hill, (1994); Simons et al., (1995); Fordham and Gabbin, (1996); Warnock and Curtis, (1997); Hassall et al .(2000). Findings from several of these studies support Daly and Stafford‘s (1984) observation that highly anxious individuals select majors having significantly fewer perceived communication demands than those selected by people with low levels of anxiety. Occupations perceived as low in communication demands included accountant (among others), and several studies have sought to investigate levels of CA in accounting majors relative to their peers in other (business) majors, and in relation to McCroskey‘s (1984a) national norms. Typically the results indicate that accounting students have higher average levels of CA than do other business majors and, for entry-level students, above national norms (Stanga and Ladd, (1990); Simons et al., (1995); Hassall et al., (2000). Hassall et al‟s (2000) study also indicates that prior educational background (science-based, arts-based, or a mix) is significantly associated with average levels of written CA for accounting and business majors, with those from a science background being highest and those from an arts background being lowest. Students‘ self-ratings of their own academic ability are also found to be significantly associated with average levels of CA for both writing and oral communicating, with those students reporting higher than average ability having lower than average levels of CA. Gardner et al.(2005) stated that curriculum changes have been aimed at motivating increased learning outcomes and communication skills development. In the light of the previous discussion about the kinds of interventions required to treat and reduce levels of CA, she 31

would not expect the changes made as educators to necessarily have reduced the levels of CA in our students. On the contrary, the concern is whether the changes made to improve communication skills development are actually increasing the levels of CA among our students, or among a subset of our students and, as a result, this is harming such developments and overall academic performance. Based on Warnock and Curtis (1997), using a small sample of Irish accounting students, they found that the overall average levels of oral CA was 72.6 – much higher than found in other studies, but there was no association between overall academic performance and levels of CA. However, they did find significant association between levels of CA and participation in tutorials and, importantly, they found that levels of CA were associated with the apparent success of students to get job offer from the (then) Big Six accounting firms.

RESEARCH METHODOLOGY

Respondents

Based on the focus of the current study, only final year accounting students from Universiti Tenaga Nasional were included in the final respondent sample (N= 179). The method of sampling was purposive sampling due to specific type of people and conforms to some criteria set by the researcher. The selection is due to the objective of the study which is looking into the final year students that have been well prepared with knowledge and skills in accounting for internship final year programme. The sample of respondents is as much as necessary based on Roscoe (1975) in Sekaran (2010), who stated that sample sizes larger than 30 and less than 500 are appropriate for most research. Instrumentation

All respondents received a set of questionnaire consisting of a demographic questionnaire and Personal Report Communication Apprehension (PRCA). The questionnaires were completed and returned at the end of a lecture class. Demographics- Participants completed a short demographic questionnaire assessing their gender, ethnicity, age, current CGPA result, languages used other than Malay, expected salary for a full time accounting position and expected accounting position after graduating. The Personal Report Communication Apprehension (PRCA) - This questionnaire has been adopted from McCroskey‘s PRCA-24 that is widely used to measure communication apprehension. According to McCroskey (1984), the 20-item, 10-item, 25-item, and 24-item versions of this instrument all use five-step Likert type response formats and the reliability is very high at above alpha= 0.90 in most cases. The most recently developed 24-item version of the instrument includes six items for each of four contexts: public speaking, speaking in formal meetings, speaking in small group discussions, and interpersonal interaction. This version also permits the generation of four sub-scores as well as an overall score. The independent variables are the four sub-scores and the dependent variable is overall score. 32

Respondents respond to the 24 items by choosing the number on a 5-point Likert-type scale from 1(strongly agree), 2 (agree), 3 (neither agree nor disagree), 4 (disagree) and 5 (strongly disagree). The type of scale measurement also has been adopted from McCroskey (1984). Statistical analysis In analyzing the data, this study employs SPSS (Statistical Package for Social Science) software for windows namely Descriptive Statistics, Reliability Statistics and Pearson correlation. The study ignores the normality assumption due to De Vaus (2002), it does not seem to have a severe effect on results since the size of a sample (N=179) is more than 100. In fact, the central limit theorem states the important principle that as a size increases and is large, it is reasonable to use statistics that assume a normal distribution. FINDINGS AND DISCUSSION

Reliability Analysis for Overall Communication Apprehension TABLE 1 : CRONBACH’S ALPHA COEFFICIENTS FOR RHE PRCA-24 ITEMS QUESTIONNAIRE FOR PREVIOUS STUDIES AND CURRENT STUDY Study Cronbach's N of Area of study Alpha Items McCroskey (1985) .97 24 CA in undergraduates enrolled in Introductory Communication courses Current study .948 24 CA in Accounting Final Year Students Investigated over 50 McCroskey (1977) .90 24 studies that consistently reported reliabilities over .90. K. Simons et al.. .94 24 CA in Accounting Major‘s Students / Upper (1995) Level Ibrahim M. Aly, .94 24 CA between two groups of accountancy Majidul Islam, (2003) students: those entering the program and those exiting the program after completion. Azmi Sarriff and .76 24 CA in first year of undergraduate pharmacy Wasif S Gillani (2011) students Mark G. Borzi & .88 24 289 students at two Timothy H. Mills AACSB-accredited midwestern universities (2001) which were well advanced in their major Dan Shanahan (2011) .95 24 CA among business and accounting students Clare T. Gardner et .90 24 CA of students studying all levels of al.(2005) undergraduate accounting at a New Zealand University in 2002 The reliability of the PRCA-24 items Questionnaire for the current study was determined and it was finally found that Cronbach‘s alpha measure of internal consistency reliability is .948. Table 1 shows a comparison of the Cronbach alpha coefficients for each of the varied populations. Most of the Cronbach alpha shows more that .70 which indicates that this instrument items and scales produce reliable and robust results due to the rule of thumb developed by Hair e al.(2010) and Sekaran (2000). They stated if Cronbach alpha of more than .07 can be considered acceptable. The closer the Cronbach Alpha coefficient gets to 1.0, 33

the better the results of reliability will be. Reliabilities that are less than 0.6 are considered to be poor, those in the 0.7 ranges, acceptable, and those 0.8 are good (Sekaran, 2000). In the analysis from previous study, the internal consistency reliability of the measures used can be considered to be good for the PRCA-24 items except Azmi Sarriff and Wasif Gillani (2011) can be considered to be acceptable.

Reliability Statistics for Sub-score Communication Apprehension TABLE 2 : CRONBACH’S ALPHA COEFFICIENTS FOR THE SUB-SCORE FOR PREVIOUS STUDIES AND CURRENT STUDY Levine & Current study Dan Shanahan Clare T. McCroskey (2011) Gardner et al.l (1990) (2011) Group Discussion .86 .736 .87 .883 Meeting .88 .851 .87 .88 Interpersonal .83 .837 .90 .837 Public Speaking .85 .82 .88 .86

Mostly, previous results produced only reliability analysis based on overall score of communication apprehension. Table 2 shows a comparison of the Cronbach alpha coefficients for each of the sub-score from the PRCA-24 items. The results show that every item from four contexts is considered to be good except .736 from the current study which can be considered acceptable. In order to understand further, refer to Table 3.

TABLE 3: PERSONAL REPORT OF COMMUNICATION APPREHEMNSION (PRCA-24) Personal Report of Communication Apprehension (PRCA-24) 1. I dislike participating in group discussions. 2. Generally, I am comfortable while participating in group discussions. 3. I am tense and nervous while participating in group discussions. 4. I like to get involved in group discussions. 5. Engaging in a group discussion with new people makes me tense and nervous. 6. I am calm and relaxed while participating in group discussions. 7. Generally, I am nervous when I have to participate in a meeting. 8. Usually, I am comfortable when I have to participate in a meeting. 9. I am very calm and relaxed when I am called upon to express an opinion at a meeting. 10. I am afraid to express myself at meetings. 11. Communicating at meetings usually makes me uncomfortable. 12. I am very relaxed when answering questions at a meeting. 13. While participating in a conversation with a new acquaintance, I feel very nervous. 14. I have no fear of speaking up in conversations. 15. Ordinarily I am very tense and nervous in conversations. 16. Ordinarily I am very calm and relaxed in conversations. 17. While conversing with a new acquaintance, I feel very relaxed. 18. I'm afraid to speak up in conversations. 19. I have no fear of giving a speech. 34

20. Certain parts of my body feel very tense and rigid while giving a speech. 21. I feel relaxed while giving a speech. 22. My thoughts become confused and jumbled when I am giving a speech. 23. I face the prospect of giving a speech with confidence. 24. While giving a speech, I get so nervous I forget facts I really know. Scoring Formula: Group discussion: 18 - (scores for items 2, 4, & 6) + (scores for items 1,3, & 5) Meetings: 18 - (scores for items 8, 9, & 12) + (scores for items 7, 10, & 11) Interpersonal: 18 - (scores for items 14, 16, & 17) + (scores for items 13, 15, & 18) Public Speaking: 18 - (scores for items 19, 21, & 23) + (scores for items 20, 22, &24) PRCA, simply add your sub-scores together Adopted from McCroskey et al., (1985). Respondents’ Profile TABLE 4: RESPONDENTS’ PROFILES Gender Frequency Male 55 Female 124 Race Frequency Malay 138 Chinese 17 Indian 23 Others 1 Age Frequency 18-21 years old 44 22-26 years old 133 More than 26 years old 2 Current CGPA result Frequency Below 2.00 7 2.00-2.49 23 2.50-2.99 65 3.00-3.49 68 Above 3.50 16 Languages use other than Malay Frequency English 154 Mandarin 16 Others 9 Expected salary for fulltime accounting Frequency position RM800-RM1000 15 RM1000-RM2000 32 RM2000-RM3000 81 More than RM3000 51

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Percent 30.7 69.3 Percent 77.1 9.5 12.8 .6 Percent 24.6 74.3 1.1 Percent 3.9 12.8 36.3 38.0 8.9 Percent 86.0 8.9 5.0 Percent 8.4 17.9 45.3 28.5

Expected accounting position

Frequency 83 62 34

Public Accounting Corporate/Industry Position Non-profit Organization

Percent 46.4 34.6 19.0

A total of one hundred and seventy nine (179) questionnaires were distributed among the respondents. Out of this figure, 124 (69.3%) were female and 55 (30.7%) were male. The study respondents constituted Chinese (9.5%), Malay (77.1%), Indian (12.8%), and other races (0.6%), respectively. The average age range was 18 to 22 years. In term of academic results, the current CGPA performance showed that 47% (about 84 students) achieved not less than 3.00. In using language, most of them only knew English as their second language. In future, about 132 of the students expert to earn a salary more than RM2000-RM3000 and less than 50% expect to pursue their career in public accounting (46.4%).

Descriptive Statistics TABLE 5: DESCRIPTIVE STATISTICS N Minimum Maximum Mean Group Discussion 179 14.00 38.00 18.3520 Meeting 179 15.00 24.00 18.7318 Interpersonal 179 14.00 22.00 18.2011 Public Speaking 179 14.00 24.00 18.6480 PRCA 179 66.00 90.00 73.9330

Std. Deviation 2.22451 1.64748 1.47404 1.71383 3.76948

Table 5 represents the descriptive presentation of the study. The minimum number of students indicated that most students agreed with the statement and the maximum indicated they disagree with the statement of communication apprehension for each context. The statements provided in each context reflect three positive feelings and three negative feelings through communication situation. (refer to Table 3 for further understanding).

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Level of Communication Apprehension TABLE 6: PERSONAL REPORT COMMUNICATION APPREHENSION Frequency Percentage Level of Overall Communication Apprehension (CA) High CA 167 93.3 Average CA 12 6.7 Level of Communication Apprehension in Group Discussion High CA in Group Discussion 107 93.3 Low CA in Group Discussion 72 6.7 Level of Communication Apprehension in Meeting High CA in Meeting 138 77.1 Low CA in Meeting 41 22.9 Level of Communication Apprehension in Interpersonal High CA in Interpersonal 121 67.6 Low CA in Interpersonal 58 32.4 Level of Communication Apprehension in Public Speaking High CA in Public Speaking 139 77.7 Low CA in Public Speaking 40 22.3 The overall communication apprehension score varied from 24 to 120. The levels of overall CA is categorized into low (scores below 51); average (scores 51 to 80); and high (scores more than 80). The level of CA in the four contexts is categorized into low (score below 18) and high (score more than 18). In Table 5, the results have been sub classified into the level of CA. The high CA in overall communication apprehension means their levels of anxiety and fear is highest in communicating with others. From this result, researchers can indicate that most of the students in this case face anxiety and fear feelings whenever they need to talk during meetings, public speaking, group discussions and interpersonal communication. Relationship for Communication Apprehension TABLE 7: CORRELATIONS

PRCA Pearson (current study) Correlation Sig. (2-tailed) PRCA (McCroskey, 1985)

Group Discussion Meeting .546** .483** .000 .000

Pearson .86** Correlation .000 Sig. (2-tailed)

.88** .000

Public Interpersonal Speaking .533** .568** .000 .000 .61** .000

.77** .000

**. Correlation is significant at the 0.01 level (2-tailed). Theoretically, the correlation could range between -1.0 and +1.0, whether it has a positive or a negative relationship. From the results, the overall score, as would be expected, significantly (p3.5 25 (11.7%) 3.00-3.49 90 (42.3%) CGPA 2.5-2.99 86 (40.4%) 0.5). This finding supported the research by Tho (1999), who found that there was no influence on subsequent accounting performance between urban and rural students on academic performance. In addition, there was no significant difference between males and females. This was supported by Carpenter et al. (1993) and Bartlett

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(1993) in their accounting studies who found that there was no significant difference in gender performance.

TABLE 6: COMPARISON BETWEEN APPROACHES OF LEARNING AND DEMOGRAPHIC FACTORS Deep Learning Surface Learning Gender 0.425 0.759 Hometown 0.374 0.536 *Significant at 0.05 level

CONCLUSION

The main objective of this study was to investigate the relationship between approaches of learning practiced by accounting and business students and to examine any influences of these approaches on the academic performance. The test used a sample of 391 students in various institutions in the East Coast Region. The results revealed that there were significant relationships between deep study approaches with academic performance among accounting students meanwhile there was a negative significance between surface learning with academic performance among business students. Meanwhile, there is no significant difference between the approaches of learning variables and all demographic factors tested (gender and hometown).

There were several limitation that should be highlighted here. First, there were various factor affecting academic performance. However, this study only considered approaches to learning. Future study should explore some other factors such as motivation, student behaviour, study environment and class activity. Second, it is also important to note that the generalisability of the results may be limited by the student population. This study merely considered the accounting students in learning institution in the East Coast Region. Future research should consider a wider group of students in order to have a reliable generalisation of the learning approaches of accounting students and business students.

This study will provides very information for educators and also higher learning institution to make changes in teaching strategies that can influence the learning approaches adopted by the students towards the desired approaches. Accounting instructors can encorage the students to develop a deep study approach as it appears to help them to become better at solving complex problems (Davidson (2002)). In addition to that, the implication for teaching is that educators should engage in a supportive roles in order to enhances‘ student learning approaches and maintain students‘ good academic performance. Finally, this finding is helpful to support instructional design of learning environments in order to cater to the students characterics in learning approaches.

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REFERENCES Ballantine, J. A., Duff A. and Larres P. M. (2008). Accounting and Business Students‘ Approaches to Learning: A Longitudinal Study. Journal of Accounting Education. Vol. 26 pp 188-201. Bartlett, S. M., Peel, J. and Pendlebury, M. (1993). From Fresher to Finalist: A Three-year Study of Student Performance on an Accounting Degree Program. Accounting Education : An International Journal. Vol. 2 pp 111-122 Carpenter, V.L., Friar, S. and Lipe, M.G. (1993). Evidence on the performance of accounting college-level financial accounting course, The Accounting Review. Vol. 63(1) pp 137-47. Davidson, RA. (2002). Relationship of study approach and exam performance. Journal of Accounting Education. Vol. 20 pp 29-44. Duff, A. (2004). The role of Cognitive Learning Styles in Accounting Education: Developing Learning Competencies. Journal of Accounting Education. Vol. 22 pp 29-52. Ervina, A & Othman, MN (2005). Undergraduate students‘ performance: the case of University of Malaya. Quality Assurance in Education. Vol. 13 pp 329-343. Field, A. (2007). Discovering Statistics using SPSS for Windows, Great Britain: Sage Publications Ltd. Hassal, T & Joyce. J (2001). Approaches to Learning of management accounting students. Education +Training. Vol. 43 pp 145-152. Lau, K. L. and Chan, D. W. (2001). Motivational StyleCharacteristics of Under-Achievers in Hong Kong. Educational Psychology. Vol. 21(4) pp 417-430. Pintrich, P. R. and Roeser, R.W. (1994). Classroom and individual differences in early adolescents‘ motivation and self-regulated learning. Journal of Early Adolescence. Vol. 14(2) pp 139-162. Spencer, K. (2003), Education in a Changing Environment 17th – 18th September 2003, University of Salford. Tho, L M. (1999). Predicting Success In University Accounting Examination Performance. Jurnal Pendidikan, Vol. 20 pp 95-104. ISSN 0126-5261 Yong, ST & Lew, TY (2005). Deep learning approach among marketing students: Adult versus youth learner. Retrieved on 22 April 2011 from www.herdsa.org.au/wpcontent/uploads/conference/2005/082.pdf. Warburton. K, (2003), Deep learning and education for sustainability. International Journal of Sustainability in Higher Education. Vol. 4 pp 44-56.

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Zhu, C., Valcke, M. & Schellens, T. (2008), A cross-cultural study of Chinese and Flemish university students: Do they differ in learning conceptions and approaches to learning? Learning and Individual Differences. Vol. 18 pp 120-127.

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THE ROLE OF DIGITAL MARKETING IN HIGHER EDUCATION INSTITUTIONS (HEIs): THE CASE OF SAUDI ARABIA STUDENTS’ UNIVERSITY SELECTION IN MALAYSIA

Eid M. Al_Mohammed, College of Graduate Studies (COGS), Universiti Tenaga Nasional (UNITEN), Putrajaya Campus, 43000 Selangor, Malaysia. E-mail: [email protected] Basheer Abbas Al-alak, College of Graduate Studies (COGS), Universiti Tenaga Nasional (UNITEN), Putrajaya Campus, 43000 Selangor, Malaysia. E-mail: [email protected] ; E-mail: [email protected] ABSTRACT The paper aims to closely examine the extent to which digital marketing can influence recruitment of Saudi Arabia students in Malaysia higher education institutions (HEIs). As competition intensifies in HE sector to attract students as well as academic staff and collaborate with other academic institutions, HEIs decision-makers should value electronic marketing and its potential contribution as a vital income resource to their institutions. A survey of quantitative method was developed for the purpose of this study and the data is collected through group of Saudi Arabia students who are studying in Malaysia‟s HEIs in and were chosen randomly. The results can shed a light to what extent electronic marketing had influenced students‟ decisions in university selection.

Keywords: digital marketing, higher education, university students, quantitative method, Saudi Arabia.

INTRODUCTION The latter part of the 21st century witnessed unsurpassed technological development and along with it a commercial development of education. In the current times, Higher Education (HE) has gone through monumental changes as the need for successful achievement and knowledge creation are significantly on the rise. Generally speaking, educational institutions play an important role in the society and economy and have been categorized into one of the categories of service industry. As a result, Higher Education Institutions (HEIs), akin to many companies in the service industry, are in a competition in a place where in economic rationalism expects the market to deliver only the best as consumers rationally choose their purchases. In other words, consumers are well aware of their interests more than any entity that regulates the industry (Gomes & Murphy, 2003). Internet use, because of its freedom and ease of access, is becoming widespread in this decade than ever before. This is where electronic marketing has an edge over conventional 55

marketing. As a consequence, digital marketing has become one of the main strategies that the organization makes use of to transform a potential market to the real one. The Internet experts advocate HEIs taking advantage of the Internet for their marketing. According to Andu (2009), in the current times, HE has significantly transformed as the needs of the time require outstanding outcomes and knowledge creation. Institutions have incorporated online education in their agenda and this type of education‘s popularity is rising judging from the increasing number of students enrolled in distance programs all over the world in general, and in Malaysia in particular. Hence, several institutions and universities are adopting strategic plans to incorporate online education in their mode of education. It is reported that developments in the World Wide Web, digital satellite technology and new applications relating to virtual reality for simulated learning classrooms are expected to have tremendous impact on the learning environment in all aspects. To this end, universities are looking into enhancing accessibility to the existing programs, developing new designs to leverage the emerging technologies and advertising programs to potential students in various techniques.

What is Internet (Digital) Marketing? The idea of marketing HE is not a novel one (Ivy, 2008). According to Kotler and Fox (1995), marketing is the analysis, planning, implementation, and control of appropriately designed programs to present a voluntary exchange of value with the plausible market for greater institutional achievement. In addition, marketing generally involves developing the organization‘s offerings to suit the target markets requirements and needs through the appropriate pricing, communication and distribution to relate, motivate and to be of service to the said markets. Effective marketing calls for HEIs to determine their target population comprehend and directly interact with them (Laurer, 2006). Internet marketing on the other hand, is categorized into four phases: communicating, selling, offering content and finally developing a network wherein marketing can function in (Hofacker, 2001).

Usage of the Internet in Higher Education Institutions Internet use is becoming widespread and according to experts in the field, HEIs should leverage the potential of websites (Thomases, 2007; Antil, 2008). Moreover, when it entails the marketing techniques of educational institutions, the main player is digital marketing; a technique that increases the reach to global prospective students (Marketwire, 2011). Higher education prospective students must search for an institution that meets their specific needs (Broekemier, 2002; Brown, 2004). Brown found that more than half of the adult students pursuing postsecondary programs used websites to search further information about institution programs of study. In the context of Australia, Gomez and Murphy (2003) reported that 175,372 international students are studying inland while 34,905 are enrolled offshore. In Malaysian local universities, the number of international students is reported to be 75, 000 (Ministry of Higher 56

Education Malaysia, 2012). The available descriptive data implies that universities and businesses consider the Internet‘s wide reaching capabilities when competing at a global scale. Hence, Internet marketing needs to be acknowledged as higher educations‘ first interactions with the prospective global foreign students will be realized online (Andu, 2008).

LITERATURE REVIEW Prior literature concerning Internet marketing reveal that it plays a crucial role in higher education HE and professional services although only a slight number of Internet marketing research has been carried out in both areas (Ngai, 2003). This is further reinforced by Hemsley-Brown (2006) who reported that research dedicated to higher education marketing is still in the infancy stage with only a small number of notable studies from both exploratory and strategic points of view. Among the notable ones is by Alexa et al. (2012) who aimed at analyzing the use of online marketing and social media strategies and in investigating universities websites and social media‘s contribution in Romanian public and private universities. They reveal that universities websites is an important tool and private universities leverage this tool more consistently in their two way interaction with prospective students. They further reveal that social media usage is used actively but only by a few universities with the social network as the most used instrument. In a similar study, Gray, Fam and Liannes (2003) carried out a study concerning international education branding and found out that the World Wide Web along with the print media were considered to be the main source of universities information in Malaysia, Singapore and Hong Kong. Therefore, the current study attempts to analyze the Saudi students‘ behavior regarding their decision to study in Malaysian Universities taking into consideration there are over 106.000 Saudi students pursuing their higher education abroad (Ministry of Higher Education Saudi Arabia, 2012).

METHODOLOGY The present study‘s main focus is to quantitatively analyze the university electronic marketing in the context of Malaysia. The method of data collection found suitable for the study is the survey questionnaire which is designed to provide an in-depth look on the factors comprising the Internet marketing and web search behavior influencing the students‘ choice. The study population is confined to six Malaysian universities that are considered to be a suitable representative of the whole of Malaysia. A sample Saudi university students studying in these universities is selected through the probability method of stratified sampling for the purpose of ensuring sufficient cases to answer the research questions. Hence, questionnaires are distributed to 320 Saudi students in 6 Malaysian Universities and 85 questionnaires are returned. The survey comprised of 15 questions measured by 5 point Likert-scale adopted from Andu (2009).

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RESULTS OF DATA ANALYSIS The table (Table 1) below presents the respondents‘ background. From the 85 students involved in the study, 71 (83.5%) are male while 14 (16.5%) are female. 16 respondents out of 85 (18.82%) are over 18 but under 22 years of age, 33 of them (38.8%) are 23 but under 28 years of age, 16 of them (18.8%) are over 29 but under 34 years of age while 20 of them (23.5%) are over 34 years of age. Majority of the respondents (57.6%) study in public universities while the remaining (42.3%) study in private universities. TABLE 1: BACKGROUND OF THE RESPONDENTS Factor

Group

Frequency

Percentage

Gender

Male

71

83.5%

Female

14

16.5%

18-22

16

18.82%

23-28

33

38.8%

29-34

16

18.8%

Above 34

20

23.5%

Public

49

57.6%

Private

36

42.4%

Age

University Type

The findings imply that the university website details played an important role in their university choice. Among the 85 students, 59% indicated that the universities websites were the key decision maker for their selections of Malaysian HEIs, while 24% of them rated neutral and finally 18% rated that universities website did not influence their decisions regarding universities selections. The second question involved the clarity of the university websites‘ service features and in this, 52% of the students rated agree that university websites‘ service features was clear, 33% rated neutral, and 15% of them rated that university websites‘ service features was not clear. The third question concerns the entry image, whether it was appropriate and easy to remember. In this, more than half (51%) of the students rated agree, 39% rated neutral and 11% rated that entry image was inappropriate and not easy to remember. The fourth question concerns the quality of university features when it comes to supporter services, programs and courses. 62% of the respondents agreed that the website conveys important and interesting information about universities facilities, support service, and programs and courses, 25% rated neutral and 13% rated disagree. In question five, the sentence reads, ―the website provided a source that goes beyond the ordinary‖ and 40% of the respondents rated neutral, 36% rated agree, and 24% rated disagree. The majority of the students (67%) agreed that the websites contain a mixture of content formats. This is followed by 22% who were neutral, and 11% who disagreed. 58

With regard to the attractiveness of the website design, of the respondents, 42% rated agree, followed by neutral 40% and 18% who disagree. When it came to the website‘s representation of the university‘s service quality, 60% of the respondents agreed, 27% neutral, and 13% disagreed. In addition, of the total respondents, 44% agreed to the websites provision of extensive information regarding the university, 25% rated neutral, and 32% rated disagree. As for the information regarding international student‘s life in the university, 38% of the respondents rated neutral of its existence in the websites, 31% rated disagree, and only 32% rated agree. Most of the students (38% neutral 37% disagreed) indicated that the websites don‘t offer a quick response to the questions posted online by the students while only 25% believe otherwise. Moreover, the findings reveal that the websites under study have a good communication features including e-mail and contact numbers. This is evident in question number 12 whereby majority of the students (58%) rated agree to the websites‘ sufficient communication features, and 22% rated neutral, while 20% rated disagree. Of the respondents 48% rated agreed of finding the university through search engines, 22% disagree and only 29% rated neutral. The total percentage of respondents who rated disagree regarding finding the university website through promotional materials is 42% followed by 38% who neutral, and a mere 20% who agreed. On the other hand, 36% of the students are neutral regarding their finding of the university website through educational portals, followed by 35% who agreed, and 29% who disagree. The final question concerns the respondents‘ finding the university website through educational agent‘s portal with 39% of them rating disagree, 34% neutral and agreeing 27%.

CONCLUSION AND DISCUSSION The present paper conducted an analysis into the empirical data collected from Saudi students for the study and a discussion of the findings. The results of the analysis provided an overview of the use of universities websites by prospective students of the Malaysian universities. Strong behavioral differences among the students in their way of choosing universities and the website usage were found in this study. Most of the Saudi students indicated that their universities‘ websites had greatly influenced their enrollments in Malaysian HEIs. Also, it is been proved that search engines play a decisive role in finding HEIs information since the majority of the Saudi students stated that they found their university website through search engine. Based on the findings, some Malaysian universities‘ websites contained insufficient information regarding their services and offerings. Malaysian universities should revise their marketing plan to cater to the attraction of international students. In conclusion, the present paper conducted a review of prior studies and research concerning Internet marketing program and all its aspects, provided the definition of Internet marketing and descriptive data and listed obstacles in achieving both reliable and successful Internet marketing in the context of higher educational entities. More importantly, this study concludes that every country should consider all these aspects and expend efforts in enhancing this technological mode of marketing. It is evident that a need exists for better 59

planning and monitoring Malaysian higher educational institutions for the purpose of achieving goals through significant developments of advance technology.

REFERENCES Alexa, E.; Alexa, M. and Stoica, C. (2012). The use of online marketing and social media in higher education institutions in Romania, Journal of Marketing Research & Case Studies, Vol. 2012 (2012), Article ID 721221. Anctil, E. J., (2008). Selling higher education: Marketing and advertising America‘s colleges and universities, ASHE Higher Education Report, September, Vol. 34, No. 2, pp.152. Andu, A. (2009). Factors influencing foreign students choice of institution (UUM)- internet marketing and web search behavior. Master Thesis, University Utara Malaysia, Malaysia. Broekemier, G. M. (2002). A comparison of two-year and four-year adult students: motivations to attend college and the importance of choice criteria, Journal of Marketing for Higher Education, 12(1): 31-49. Brown, J. (2004). Marketing and retention strategies for adult degree programs, J. Pappas & J. Jerman (Eds.), Developing and delivering adult degree program, No. 103. New Directions for Adult and Continuing Education, (pp. 51-60). San Francisco: Jossey-Bass. Gomes, L., and Murphy, J., (2003), An exploratory study of marketing international education online, The International Journal of Education Management, Vol. 17, No. 3, pp. 116-125. Gray, B.J., Fam, K.S., and Llannes, V.A. (2003), Cross cultural values and the positioning of international education brands, Journal of Product and Brand Management, Vol. 12, No. 2, pp. 108-119. Hemsley-Brown, J., (2006), Universities in a competitive global marketplace: a systematic review of the literature on higher education marketing, International Journal of Public Service Managemen, Vol. 19, No. 4, pp. 316-338. Hofacker, Charles F. (2001). Internet marketing, Third Edition, New York: John Wiley. Ivy, J., (2008). A new higher education mix: the 7Ps for MBA marketing, International Journal of Educational Management, Vol. 22, No. 4, pp. 288-299. Kotler, P. & Fox, K. F. A. (2002). Strategic marketing for educational institutions, Upper Saddle River, New Jersey, Prentice Hall. Laurer, L. D. (2006). Advancing higher education in uncertain times, Council for Advancement and Support of Education, New York, pp. 255.

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Marketwire, (2011). Educational institutions increasingly turning to digital marketing to attract prospective students, Says New AdReady/Stamats Survey, February 2012, (online) from http://finance.yahoo.com/news/Educational-Institutions-iw-2188376283.html [Retrieved 3th February 2011]. Ngai, E.W.T. (2003). Commentary: Internet marketing research (1987-2000): a literature review classification, European Journal of Marketing, Vol. 37, No. 1/2, pp. 24-49. Thomases, H. (2007). Surveying higher education about online marketing, August 14, 2007 (online) from http://www.clickz.com/3626716 [Retrieved January 25, 2009].

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EXAMINING UCSA STUDENT PORTAL SUCCESS FROM THE PERSPECTIVE OF MODIFIED De LEAN SUCCESS MODEL Fahmi Zaidi Bin Abdul Razak E-mail address: [email protected] Noor Azizah Binti Noorashid E-mail address: [email protected] Hussin Bin Salleh E-mail address: [email protected] Fairus Bin Ahmad E-mail address: [email protected]

Faculty of Education & Social Science University College ShahPutra (UCSA) BIM Point, Bandar Indera Mahkota, 25200 Kuantan, Pahang, Malaysia Tel.: 609-5737777 Fax: 609-5738899

ABSTRACT

UCSA‟s student portal has been implemented since 2005. Due to the fact that UCSA‟s student portal is only for registration purpose and time-table viewing, the hit account throughout the year was not so pretty. Based on limited IT budgets and the need to justify investment in student portals, assessing the benefits of these is an important field in research and practice .This study use modified De Lone McLean success model (Delone & McLean, 2003) in the context of student portal. The hypothesized model is validated empirically using a sample collected from 279 students of UCSA. The results demonstrate that satisfaction was found positively related to users‟ continuance intention explaining a total of 67% variance. The implications of these findings for e-learning practitioners are discussed at the end of this work. Keywords: continuance intention, service quality, satisfaction, structural equation modeling, student portal

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INTRODUCTION The measurement of information systems (IS) success or effectiveness has been widely investigated by the IS research community. However there is a lack of studies on applying IS success model in the context of continuance intention. Previously, numerous studies only focusing on initial acceptance e.g.; (Lin, 2007; Masrek, 2007; Chen & Cheng, 2009) whereas eventual success depend on its continued use rather than first-time use (Bhattacherjee, 2001). The importance of continuance is clear, that is customer turnover will lead to acquiring new customers that may cost as much as five times more than retaining existing ones (Bhattacherjee, 2001).

The success of retaining customers will help organizations by reducing the cost of and increasing availability of training. Present study desired to explore individuals‘ intentions to continue using student portal system. De Lone & Mc Lean IS Success model were used to measure student portal success and thus obtain an understanding of individuals‘ continuance intention towards using portal system. From the perspective of continuance intention, previous studies utilized numerous of determinants and IS model e:g Self-Determination Theory (Roca & Gagne, 2008); Expectation-Confirmation Model (Bhattacherjee, 2001); Personal Innovativeness (Shih-Wei Chou, 2009); UTAUT-Unified Theory of Acceptance and Use of Technology (Chiu & Wang, 2008); Technology Acceptance Model-TAM (Wangpipatwong & Wichian Chutimaskul, 2008; Terzis & Economides, 2011; Roca, Chiu, & Martınez, 2006); user e-learning experience (Lin , 2011); subjective norm (Lee, 2010); contribution intention (He & Wei, 2007); habit (Limayem, Moez, Hirt, & Cheung, 2007).

Previous research have shown that satisfaction have a relationship between satisfaction and continuance intention (Bhattacherjee, 2001; Yu-Hui Tao, 2009; Kang, Hong, & Lee, 2008; Chen, Yen, & Hwang, 2012; Wen-Shan Lin, 2011; Shih-Wei Chou, 2009).Oliver (1980) demonstrate that satisfaction will lead to intention to use. Consequently, we also argued that satisfaction influenced student portal system continuance intention through these variables. Antecedent of the satisfaction was also included in this study as proven in previous study: information quality (Chen & Cheng, 2009); system quality (Wang, 2008) and service quality (Wang, 2008). Therefore, we considered De Lone & Mc Lean Success Model as a determinant of continuance intention

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THEORY AND LITERATURE REVIEW

Student portal system The definition of portal is still not clearly defined (Masrek, 2007). However, in general, it is defined as a single, personalized interface through which users access all information resources and services in a secure, consistent and customizable manner (Masrek, 2007). The portal is resource-based as the members can download and upload all kinds of information such as documents, articles, websites, software, exercises, video upload, links to interesting events (Pynoo et al. 2012). In the context of UCSA, the new implemented portal information system will help student in registration purposes and timetable viewing. However since its inception, no studies have been conducted to assess to measure the adoption of the portal

De Lone Mc Lean Success model There are several measures of Information system success. De Lone & McLean (1992) reviewed comprehensively the different information system success measures and propose a six-factor IS success model as a taxonomy and framework for measuring the complex dependent variables in IS research (Wang, 2008). They are System Quality, Information Quality, IS Use, User Satisfaction, Individual Impact and Organizational Impact. However, Delone & Mclean (1992) did not provide an empirical validation of the model and, thus, suggest that further development and validation is needed for their model as well as it not well accepted by the management IS community (Chen & Cheng, 2009) as it ignores the emergence of new economic activities. Because of the criticisms suffered from other studies, Delone & McLean (2003) proposed the updated version of IS success model in 2003. The objective of this new model was to update the old one and evaluate its usefulness in light of dramatic change in information technology (IT) evolution, especially the emerging growth of e-commerce. The major alteration that has been made to the model were the addition of a ‗service quality‘ construct and a partial division of the ‗use‘ construct into ‗intention to use‘ and ‗actual use‘. Delone & McLean (2003) also combined the individual and organizational impacts of use into a single factor called ‗net benefits‘. Although the model has been revised, but it still needs further validation before it can serve as a basis for the selection of appropriate IS measures (Wu & Wang, 2006). Wang (2008) extended the model to explain e-commerce success in terms of reuse as a dependant variable. Therefore, it seems reasonable to assume that De Lone & Mc Lean IS Success model can be use to study the continuance.

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RESEARCH MODEL AND HYPOTHESES Main focus on IS research is to know why and how individuals choose to adopt new technologies (Schauppa & Lemuria Carter, 2010). Numerous studies (e.g., Venkatesh, Morris, & Davis 2003; Davis, 1989; Su-Chao Chang, 2008; Park, 2009; Abdulhameed Rakan Alenezi, 2010; I-Fan Liu & Yeali S. Sun, 2010; Il Im & Kang, 2011; Boštjan Šumak, 2011; Vachiraporn Khayun, 2011; Shu-ming Wang, 2011) have shown that all those variables involved in the studies affected individuals to adopt new technologies at initial stages but not at eventually success. The study on long-term viability of an information system is crucial. Therefore, the proposed model uses satisfaction, information quality, service quality and system quality to explain students‘ continuance intention to use student portal system in UCSA (Fig. 1) FIGURE 1 PROPOSED RESEARCH MODEL

Information Quality Satisfaction System Quality

Continuance Intention

Service Quality

Satisfaction Satisfaction is defined as emotional reactions to the transaction of business (Oliver, 1980). Satisfaction is considered as an important determinant of continuance intention (Bhattacherjee, 2001) and critical to the survival of an organization (Kettinger & Sung-Hee ‗‗Sunny‘‘ Park, 2009). If the customer has good experiences of using MIM (mobile instant message) over time, then he will have cumulative customer satisfaction (Zhaohua Deng, 2010). Wang (2008) reported that customers‘ satisfaction with e-commerce was significantly associated with their continuance intentions. Therefore, the following hypothesis is proposed. 65

H1. Satisfaction is positively related to student‘s continuance intention to use UCSA‘s student portal

Service Quality Service quality has been widely studied since the early work of Zeithaml &. Berry (1996). Oliver (1980) argued that, service quality is a performance perception which influences customer satisfaction through two mechanisms, directly via customer observation of good or bad service quality and indirectly via an input to the disconfirmation comparison (i.e. discrepancy between performance and expectation). Service quality was a late addition to the De lone and McLean model (Trkman & Trkman, 2009). Parasuraman & Zeithaml (1985) proposed that higher level of service quality result in increased customer satisfaction. In recognition of the expanded role of the IS department and the importance of IS and ecommerce (EC), researchers have begun to include service quality as a measure of IS satisfaction/success in recent years. Prior studies, Kettinger & Sung-Hee ‗‗Sunny‘‘ Park (2009) indicated that service quality was significantly related to customer satisfaction. Therefore, the following hypothesis is proposed. Therefore, we proposed H2. Service quality is positively related to student‘s satisfaction with UCSA‘s student portal.

Information Quality According to Gorla & Somers (2010), information quality is a concept that is related to the quality of information system output, can be described in terms of outputs that are useful for business users. As stressed by Salaun & Flores (2001), good quality information is becoming a necessary prerequisite for the setting-up of an active partnership between supplier and consumer (in this case-the student portal system and the students). Delone & Mclean (1992) IS success model suggests that higher level of information quality result in increased user satisfaction. Chen (2010) and Landrum, Prybutok, & Zhang (2010), indicated that information quality had a significant effect on user satisfaction. Accordingly, the following hypothesis was proposed. H3. Information Quality is positively related to student‘s satisfaction with UCSA‘s student portal.

System Quality The concept of system quality, first introduced by Delone & Mclean (1992), was defined as quality manifested in a system‘s overall performance and measured by individuals‘ perceptions (Delone & McLean, 2003). Gorla & Toni M. Somers (2010) defined system quality as quality of information processing itself, which is characterized by employment of state-of-the-art technology, a system offering key functions and features (which is denoted as IS excellence, and software) that is user friendly, easy to learn, and easily maintainable (which is denoted as IS value). Cheung & Lee (2011) examined the users‘ satisfaction on e66

learning portal. They found that system quality affected overall satisfaction and was the best predictor of satisfaction. Prior studies on IS success (e.g., Wang, 2008; Wu & Wang, 2006; Chen & Cheng, 2009) have also provided support for the notion that system quality positively affected user satisfaction. Accordingly, the following hypothesis was proposed. H4. System Quality is positively related to student‘s satisfaction with UCSA‘s student portal.

METHOD

Sample The participants for current studies comprised 279 students from UCSA who use UCSA‘s student portal for course registration. Of the 300 questionnaires distributed, 279 were completely filled. Regarding gender, female samples were the majority of total samples; the percentage of females was around 76%. For the semester currently studied, semester 4 is the majority of the sample. Concerning course taken, 44.4% was from Nursing (UCSA) program. The rest are Pharmacy 7.5%, Medical Lab Technology 2.5%, Art & Design (UiTM) 2%, Diploma in Science (UiTM) 0.7%, Nursing UiTM 6.1%, Office Management UiTM 5%, BA Business (UPM) 1.1%, Diploma in Business (UPM) 5.4%, Property management UTM 3.6%, Quantitative Surveying (UTM) 11.5%, Architecture (UTM) 6.1% Computer Science UTM 1.8%, Medical Assistance (UCSA) 1.8%

Instrument development Our research model includes five constructs, each of which was measured with 28 items. All items were obtained from previously validated instruments. After the questionnaire was formulated, it was tested among several students. Based on their comments, some were revised to improve the readability. Each item was measured with a seven point Likert scale, whose answer choices range from ‗‗strongly disagree‖ (1) to ‗‗strongly agree‖ (7). Continuance intention was measured with three items and adapted from Bhattacherjee (2001). While the measures of satisfaction (eight items), information quality (six items), service quality (four items) and system quality (seven items) were adapted from Delone & McLean (2003) and Chao- Min Chiu & Chang (2007). All of the items used were modified to the context of student portal.

Data Analysis This study employs a two-step structural equation modeling (Anderson & Gerbing, 1988). It performs confirmatory factor analysis (CFA) analysis on the items corresponding to the constructs. The reason of adopting SEM for analyze the relationship between variables is due to general theoretic of social science and behavioral science, which is usually constructed by some unobservable or unmeasured variance (Pai & Tu, 2011) 67

RESULTS

Psychometric properties measures Psychometric properties measurement involves assessing internal consistency and construct validity. The traditional criterion for assessing internal consistency is Cronbach alpha (Table 1) while the recent one is uses composite reliability (Urbach, Smolnik, & Riempp, 2010). The CA values in our model are exceeding recommended value of 0.5 (Fornell & Larcker, 1981) while CR values indicated above the generally recommended minimum of 0.7 (Nunally & Bernstein, 1994). All of the variables in this study were adapted from relevant literature thus exhibited strong content validity.

Convergent validity was evaluated for the measurement scales using two criteria suggested by (Fornell & Larcker, 1981): (1) all indicator factor loadings should be significant and exceed 0.70 and (2) average variance extracted (AVE) for each construct should exceed the variance due to measurement error for that construct (i.e., should exceed 0.50). As shown in Table 1, most items exhibited loading higher than 0.7 on their respective constructs, providing evidence of acceptable item convergence on the intended constructs. Therefore, all conditions for convergent validity were met. TABLE 1 RESULT OF CONVERGENT AND RELIABILITY TEST

Construct items SATISFACTION Satis4 Satis5 Satis6 SYSTEM System 3 System 6 System 5 System 4 INFORMATION IQ 4 IQ 3 IQ 2 IQ 1 SERVICE SQ1 SQ2 SQ3

Composite reliability 0.89

AVE 0.73

Cronbach Alpha 0.89

0.88

0.65

0.88

0.86 0.84 0.84 0.81

0.9

0.7

0.9

0.79 0.86 0.86

0.88

0.7

0.87

Std. loading 0.80 0.88 0.88 0.80 0.83 0.80 0.80

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CONTI Continuance 1 Continuance2 Continuance3

0.86 0.94 0.86

0.92

0.79

0.91

Discriminant validity assesses the extent to which a concept and its indicators differ from another concept and its indicators (Bagozzi, Yi, & Phillips, 1991). The discriminant validity of items and variables were examined using factor and correlation analyses. As we can see from the factor analysis in (Table 2), all items, had cross loading coefficients that are at least 0.10 lower than the factor loading on their respective assigned latent variables (Gefen & Straub, 2005). Overall, the measurement model demonstrated adequate reliability, convergent validity and discriminant validity. TABLE 2 ITEM-CONSTRUCT CORRELATION

ITEMS Systm3 Systm6 Systm5 Systm4 IQ4 IQ3 IQ2 IQ1 SQ1 SQ2 SQ3 satis4 satis5 satis6 Continuance1 Continuance2 Continuance3

SYSTEM 0.80 0.83 0.80 0.80 0.70 0.68 0.69 0.65 0.65 0.71 0.71 0.59 0.66 0.66 0.53 0.58 0.53

INFORMATION 0.65 0.67 0.65 0.65 0.86 0.84 0.84 0.81 0.59 0.64 0.64 0.62 0.69 0.69 0.52 0.57 0.52

SERVICE 0.66 0.68 0.66 0.66 0.64 0.62 0.63 0.60 0.79 0.86 0.86 0.55 0.61 0.61 0.46 0.51 0.46

SATIS 0.59 0.62 0.59 0.60 0.67 0.66 0.66 0.63 0.55 0.60 0.60 0.80 0.88 0.88 0.58 0.63 0.57

CONTI 0.49 0.51 0.49 0.49 0.52 0.51 0.51 0.49 0.43 0.47 0.47 0.53 0.59 0.59 0.86 0.94 0.86

Evaluation of the measurement model The measurement model for the construct is measured using confirmatory factor analysis. This procedure is done using AMOS 18. To demonstrate a reasonable fit for the model, a number of fit indices were computed including Chi-square/degrees of freedom, Goodness-offit index (GFI),Adjusted Goodness-of-fit Index (AGFI , Adjusted Goodness-of-fit Index 69

(AGFI), Comparative Fit Index (CFI), and Root Mean Square of Approximation(RMSEA). A very good fit is normally deemed to exist when GFI and CFI are greater than 0.90, Root Mean Square of Approximation (RMSEA) is around 0.10 (Hair & Black W.C., 2006), and AGFI is greater than 0.80. The chi-square was not used because it is sensitive to sample size. Thus, the use of relative (chi-square/df) seemed appropriate; it is assumed that value less than 3 is indicative of an acceptable fit (Bagozzi & Yi, 1988). The indices for the measurement model 1 with all 28 items showed that the data did not fit well (see Table 3). Some of the indices, such as GFI (0.79), and AGFI (0.75) were below acceptable levels. Therefore, the measurement model was reevaluated. Anderson & Gerbing (1988) suggested four methods to improve model fit: (1) relate the indicator to a different factor, (2) delete the indicator from the model, (3) relate the indicator to a multiple factor, or (4) use correlated measurement error. The researchers stated that the first two methods are preferred because they preserve unidimensional measurement (Cho, Johanson, & Guchait, 2009), whereas the second two methods do not. Therefore, we chose to delete the indicators instead of relating them to a different factor because we could not find a theoretical support for the approach. This process resulted in the deletion of 10 items to improve the model fit, A respecification of Model 1 without these items was necessary to improve it. In the deleting procedure, each item must be deleted one at a time (Kim, 2008) and Model 1 was reevaluated. In order to make sure that deleting those items did not worsen the reliability and validity of the constructs, we conducted a composite reliability and validity test for the first measurement model (before deleting the items) and the modified measurement model (after deleting the items). Table 3 shows the results of the composite reliabilities and validity for the two models. The composite reliabilities were satisfactory for both models which exceeding the minimum criterion, .50 (Fornell & Larcker, 1981). After discarding those items, the measurement model, Model 2, was reevaluated; its indices indicated a good fit which is chi-square/degree of freedom = 2.24, GFI = .91 and AGFI = .873.

TABLE 3: RESULT OF COMPOSITE RELIABILITY AND VALIDITY

CONSTRUCT SYSTEM INFORMATION SERVICE SATIS CONTI

Number of items 1st model 2nd model 7 4 6 4 4 3 8 3 3 3

Composite reliability 1st model 2nd model 0.91 0.89 0.92 0.90 0.90 0.88 0.94 0.89 0.92 0.92

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convergent validity (AVE) 1st model 2nd model 0.60 0.65 0.64 0.70 0.68 0.70 0.67 0.73 0.79 0.79

Evaluation of the structural model

For the purpose of examining the structural model, we use a similar set of model-fit indices. (Table 4) shows the estimation from the structural modeling.

TABLE 4 SUMMARY OF THE OVERALL FIT INDICES FOR MEASUREMENT MODEL 1 AND 2

Model Measurement model 1 Measurement model 2 Structural model Suggested value

Chi-Square/df 2.85

2.24 2.26 ≤3

GFI 0.79

0.91 0.91 >0.95

AGFI 0.75

0.87 0.87 ≥0.80

TLI/NNFI 0.90

CFI 0.91

RMSEA 0.08

0.96 0.95 ≥0.90

0.96 0.96 ≥0.90

0.07 0.07 CV 5% (-2.960411) and from this level result it is shown that the data on the two variables has a long run relationship. The estimation results suggest that there are long-run equilibrium relationships between Foreign Direct Investment and the Exchange Rate and this result is also supported by the study of Lin and Pan (2006). By doing co-integration, we can strongly reject the null hypothesis which is that there is no long

term relationship of the independent variable (Exchange rate) on Foreign Direct Investment (FDI) and accept the alternative hypothesis which is that there is a long term relationship of independent variable (Exchange rate) on Foreign Direct Investment (FDI). This means that this data is co-integrated and relates to the first objective

TABLE 5: ORDINARY LEAST SQUARES (OLS) TEST

Variables OLS for FDI (LOGER) Constant for FDI OLS for Exchange Rate (LOGFDI) Constant for Exchange Rate

Coefficient 1.827983 5.809542 0.090751 0.380631

R-squared = 0.165890 F-statistics = 5.966501 Prob statistics = (0.020685) Regression Model: Log FDI = 5.809542 + 1.827983 + ε 104

Probability 0.0207 0.0000 0.0207 0.2017

From this test we can conclude that Foreign Direct Investment is more sensitive towards the changes in exchange rate because the coefficient is nearer to 1. If the Exchange Rate increases by 1 unit then Foreign Direct Investment will increase by 1.827983. Furthermore, the reading of R2 shows low relativity where the value is 16.58%. This is because a high rsquared indicates that we have found all of the significant causes. If the r-squared is low, it only means there are more factors acting on the data. You need to keep looking for more causes. The result is significant, where the Probability value is less than 5% and is positively related to the variables and this is supported by Haynes on April, 2010. By using Ordinary Least Squares (OLS), we can reject the null hypothesis that there is no change in the independent variable (Exchange rate) towards the sensitivity on Foreign Direct Investment (FDI) and accept the alternative hypothesis which is that there is a change in the independent variable (Exchange rate) towards the sensitivity on Foreign Direct Investment (FDI). In other words, we have achieved the second research objective that is to be analysed, the sensitivity of Foreign Direct Investment towards the Exchange Rate. We also achieved the third hypothesis where there is a positive impact of FDI and the exchange rate.

CONCLUSION AND RECOMMENDATION From the results tested earlier by using the Stationary Test using Augmented Dickey–Fuller, OLS Test (multiple regressions), and the Co-integration Test, we can conclude that Exchange Rates have a positive impact towards the changes in Foreign Direct Investment. But, foreign direct investment does not have any effect on exchange rates which means it is does not give a positive or negative impact. This is because the data is not significant which is 0.090751 that is not larger than 1 that matches macroeconomics theory. For the first hypothesis, the alternative hypothesis is accepted that is there is a long term relationship of the independent variable (Exchange rate) on Foreign Direct Investment (FDI) by using a co-integration test which indicates the long term relationship between the two variables. Data is significant with a probability of 5% and this explains both variables co integrated for a long run relationship. The change of one unit of the Exchange Rate will result in a change of 1.827983 units of foreign direct investment. The data is also significant where the ADF is smaller than the critical value which is ADF – 3.035293> CV 5% (-2.960411). This is supported by. Lim and Pan (2006). For the second hypothesis, the alternate hypothesis is accepted that is there are changes in the independent variable (exchange rates) towards the sensitivity on FDI by using the ordinary least squares (OLS) test. Foreign direct investment is more sensitive towards the changes in the exchange rate because the coefficient is nearer to 1. Reading the R2 shows a low relative position where the value is 16.58%. This is because a high r squared indicates that we have found all the significant causes. If the r squared is low, it only means there are more factors acting on the data. This is supported by Haynes (2010). For the last hypothesis, the alternate hypothesis is accepted that is there is a positive impact on FDI based on the independent variable (Exchange Rate) by using the Augmented Dickey Fuller or unit root test. At level FDI (-2.509412) is greater than the 5% critical value of (2.960411) and at the level of the Exchange Rate (-1.312777) is greater than the 5% critical value(-2.960411) which is at a level where the data are not stationary. At the 1st difference 105

FDI (8.264590) is less than the 5% critical value of (-2.963972) and at the 1st difference ER (4.885833) is less than the 5% of critical value (-2.963972) which means that the data are stationary. The two variables (exchange rate and foreign direct investment) will be stationary at the first difference where the value is less than the 5% of critical value. These theories have been supported by Tingi (2000). The study can conclude that all of the null hypotheses are rejected and accepts all alternate hypotheses whereas there is a long term equilibrium between the two variables (co integration test), the changes of ER towards sensitivity of FDI (OLS test), show that the entire two variables will be stationary at the first difference where the value is less than 5% of critical value (unit root test @ ADF). Movement of foreign direct investment does not have an impact on the flow of the exchange rate and a low R-squared means there are more factors acting on the data such as growth of domestic product, inflation rates, interest rates, etc.

The study shows that all hypotheses have been approved and accepted over the entire alternate hypothesis. The results explain that the exchange rate has a strong relationship with foreign direct investment. Study for the positive and negative impact may differ in different countries as well as different exchange rates due to the economic environment. This will influence the effect or impact on foreign direct investment. Lower currency and higher currency may influence the impact of foreign direct investment, such as when the Baht or Rupiah are lower than the Malaysian Ringgit but the Euro or Pound may be higher than the Malaysian Ringgit that may impact exchange rates towards the foreign direct investment in Malaysia. We can use other variables that influence foreign direct investment such as growth domestic product, interest rates, inflation rates, exports and imports, and others that may influence the different impact of foreign direct investment. We can use r-squared which is a low relative unit because it means there are more factors acting on the data that effect foreign direct investment. Does the growth domestic product mostly influence the foreign direct investment that may give a positive impact on Malaysian economic performance? Other than that, we can use across industry sectors that effect foreign direct investment such as the consumer products sector, the manufacturing sector, the construction sector, the finance or banking sector, the mining sector, and others. It also may be influenced by economic environment performance that affects the dependent variables such as inflation, regression, politics, etc. These findings of this study may provide some meaningful insights to the body of knowledge both for investors and researchers. For the policy implications, it is hoped that the findings will help the regulatory bodies to better understand the effects of exchange rates on FDI behavior towards achieving improved economic performance. Due to the latest trend that the Malaysian Prime Minister YAB Dato' Sri Haji Mohd Najib bin Tun Haji Abdul Razak has introduced ―Transformasi Berjaya Rakyat Sejahtera‖ the Malaysia government must not only transform the country that is only focused on foreign companies but also on our Malaysian efforts..

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REFERENCES Abbas, Q., Akbar, S., Nasir, A.S., Ullah, H.A, Naseem, M.A. (2011). Impact of Foreign Direct Investment on Gross Domestic Product. Global Journal of Management and Business Research.Vol.11 pp 11-51 Arratibel. O., Furceri. D., Martin. R., Zdzienicka. A. (2010). The Effect of Nominal Exchange Rate Volatility on Real Macroeconomic Performance in the CEE Countries. Economic System, Vol. 35, pp 261-277. Baek, I.M. and Okawa, T. (2001). Foreign Exchange Rates and Japanese Foreign Direct Investment in Asia. Journal of Economics and Business, Vol. 53 pp 69-84 Ibarra, C.A. (2010). Capital Flows and Capital Flows and Real Exchange Rate appreciation in Mexico, Univ. Americas Puebla, Cholula, Mexico. Lee, B.S., and Min, B.S. (2011). Exchange Rates and FDI Strategies of Multinational Enterprise. Pacific Basin Finance Journal, Vol 11. pp 586-603. Noorbakhsh, F., Paloni, A. and Youssef, A. (2001). Human capital and FDI Inflows To Developing countries: New Empirical Evidence. World Development, Vol. 29, pp 1593-1610. Russ, K.N. (2006). The Endogeneity of the Exchange Rate as a Determinant of FDI: A Model of Entry and Multinational Firms. Journal of International Economics, pp 344-372. Takagi, S., Shi, Z. (2011). Exchange Rate Movements and Foreign Direct Investment (FDI): Japanese investment in Asia. Japan and the World Economy Journal , Vol 23. pp 265-272 Vu, T.B., Noy, I. (2008). ―Sectoral Analysis of Foreign Direct Investment and Growth In Developed Countries‖. Int. Finance Markets inst and Money, Vol. 19, pp 402-413. Xing, Y. (2005). ―Why is China So Attractive for Foreign Direct Investment? The Role of Exchange Rates‖. China Economics Review. Vol. 17, pp 198-209. Xing, Y., Zhao, L. (2006). ―Reverse Imports, Foreign Direct Investment and Exchange Rates‖, Japan and World Economy. Vol. 20, pp 275-289.

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PERCEPTIONS TOWARDS AN INTERNSHIP PROGRAM: AN EMPIRICAL STUDY OF ACCOUNTING UNDERGRADUATE STUDENTS IN MALAYSIAN HIGHER EDUCATION INSTITUTIONS. Juliana Anis Ramli Universiti Tenaga Nasional (Uniten) Department of Accounting, COBA, Uniten, 26700 Muadzam Shah,Pahang. Email: [email protected] Mohd Rizuan Abdul Kadir Universiti Tenaga Nasional (Uniten) Department of Accounting, COBA, Uniten, 26700 Muadzam Shah,Pahang. [email protected] Khairul Nizam Surbaini Universiti Tenaga Nasional Department of Marketing & ED, COBA, Uniten, 26700 Muadzam Shah,Pahang. [email protected] Zulkifli Zainal Abidin Universiti Tenaga Nasional Department of Accounting, COBA, Uniten, 26700 Muadzam Shah,Pahang. [email protected] ABSTRACT This study attempts to examine the demographic factors and students‟ perceptions on the internship program involving undergraduate accounting students in Malaysian higher education institutions. The primary data collection was through self-administered questionnaires which were distributed to a sample of 190 undergraduate accounting students upon their completion of the internship program. Factor analysis and multivariate ANOVA have been employed in order to meet the objectives of the study. The results reveal that there are six (6) dimensions underpinning the internship perception scale and there is a significant difference between the students in different types of company placement and their perception towards internship. However, it is found that there are no significant differences between gender and CGPA results with what students have perceived on the internship. Keywords: Internship Program, Perceptions, Accounting Students, Malaysian Higher Education Institutions, Demographic Factors.

INTRODUCTION Due to an increasing rate of unemployment, the market is unable to absorb the increasing number of graduates seeking jobs, hence this problem has prompted higher learning institutions to provide an internship program as part of a comprehensive curricula in undergraduate programs. Since 2000, it has been made compulsory for students to undergo 108

an internship as a requirement for graduation (Lay Leng et al., (2007), since the Malaysian Deputy Higher Education Minister, Datuk Ong Tee Kiat stated that internships should be prepared with a certain standard in order to equip the undergraduates for the job market (The Star, May 13, 2007). Moreover, internships are not an optional course but are seen as an indispensible collegiate experience component (Collins,(2002). Hence, traditional pedagogical methods, such as lectures are perceived to be less appropriate to students since such methods may turn students into passive underachievers (Guyton, (2000) who are unable to make the transition from memory to action (Bransford and Vye, (1989). Internship, a supervised practical training undertaken by undergraduates before completing their studies, is viewed as a smooth transition for undergraduates from the academic world to the working environment (Muhammad et al., (2009). Internship provides a myriad of benefits and is viewed as a ‗win-win‘ situation for the triangular parties, involving the student, participating organization and the university. From students‘ perspectives, among the major benefits they could acquire from internship includes better chances of employment upon graduation (Cannon and Arnold, (1998), prepares them with the opportunity of gaining valuable on-the-job experience (Coco, (2000), eases the search to a permanent job (Cannon and Arnold, 1998), opportunity to work with professionals (Cook.et al.., (2004); Cannon and Arnold, (1998), and better networking and increasing the level of self-esteem. Besides, Knouse et al. (1999) state that internship also benefits students to have confidence, less anxiety and enhances specific academic skills. Hence, it can soften the reality shock in students of transitioning from classroom learning to the working environment. Furthermore, with the enhancement of interpersonal skills and personal maturity while on internships (Cook et al., (2004), the students who had internships are likely to find jobs more quickly than their counterparts who did not have an internship experience (Henry, (1979). From the employer perspective, they benefit from not only gaining a source of inexpensive labor (Miner & Crane, (1995) but they also receive the intern‘s knowledge of the latest academic information and skills (Cook et al., (2004) because by having interns who have advanced knowledge would provide better service quality to their customers (Kusluvan and Kusluvan, (1998). In addition, the employer also would have better hiring decisions in which they can evaluate their potential future employee much more effectively in terms of their working attitudes and technical skills during internship (Beck and Halim, (2008). Besides, according to Chong (2005), firms tend to hire people with experience and soft skills rather than without experience. Tang (2005) added that most companies would prefer to hire students who have performed well during their internships. Meanwhile, the university also can benefit from involving students in an internship program. For instance, internship allows the university to gain an idea of the effectiveness and relevance of its curriculum in order to meet the job requirements in becoming professionals. Linking with industry, the university can also develop a good rapport with the participating companies and gain improved employment prospect for its students. Other potential benefits may include monetary support for research, access to guest lecturers and opportunities for field trips (Coco, 2000). Even though the internship provides numerous benefits to the triangular parties, the interns who have undergone the internship, can value what they have perceived and the experiences gained through this form of experiential education. Hence, the purpose of this study is twofold; firstly to determine the factors that underpin the intern‘s perceptions on the internship program and, secondly to investigate if there is a significance difference between internship factor(s) and demographic factors (for instance, gender, CGPA results and type of company placement). 109

The remainder of the paper is organised as follows. Section 2 reviews the literature with regard to the benefits of internship on the three participating parties, students, firms and universities and students‘ perceptions on internships. Section 3 outlines the instrumentation, and samples and sampling procedures. Section 4 presents the analysis of findings and discussion of the results. Finally, section 5 concludes the study and sets out the limitations and directions for future research. LITERATURE REVIEW The Importance/Benefits of Internship and Perceptions on Internship Programs Internship provides huge impacts to the level of employability of graduates upon their graduation. Previous researchers have established the three main reasons as affecting graduates‘ lack of employability, which are a weak command in English, poor attitude and personality, and unrealistic expectations of salaries and benefits (The Star, August 21, 2005). Internship is defined by Collins (2002), as a ―bridge‖ from classroom to workplace, this means that it is not just an optional enhancement to academic record, but an essential idealistic experience component. Students, accordingly, perceived internship as a credible means to land their first job (Cannon and Arnold, (1998); Lam and Ching, (2007). Internships can also significantly and positively increase the students‘ knowledge base and inspire their motivation to become professionally before entry into the marketplace (Beard, (1998). This internship can provide a tacit knowledge (Nonoka and Takeuchi, 1995), which refers to skills and experiences gained from the internship (Wasonga and Murphy, (2006). According to Lam and Ching (2007), students and industry are aware of the benefits of internship which can be considered as one of the positive strategies for universities/colleges to provide a comprehensive curriculum, so that the students equip themselves for subsequent employment after graduation, and such learning opportunities can provide a significant means for bridging the gap between the classroom and business environment (Beard, 1998). Internship is such a valuable program that provides hands-on learning that the students cannot obtain from the classroom. Students, nowadays have increasingly realized the importance of internship as a ‗stepping stone‘ before they enter the real job marketplace after graduating. Internship also is a primary entry point of full-time employment (Band, (2007). Indeed, academicians and practitioners of the accounting profession have recognized the contribution and bountiful benefits of internships to the three parties; participating students, university and industry (employers). Beard (1998) found that most internship programs are fairly new, are for credit only, occur during the junior year, are paid rather than unpaid, and require a written project to be completed by the student. Beard added that most programs in accounting do not have full or part-time coordinators, most do not require on-site visits and most share the responsibility for identifying internship sites with students and others. Beard also noted that improvement of job/career opportunities after graduation and relevance for past and future classroom learning as benefits to students, while recruitment of future employees and parttime and special project employees are benefits to the firms, and placement opportunities of graduates and enhancement of classroom learning are benefits to the faculty/university itself. Pianko (1996) stated that students seem to believe that internships give them abundant benefits and advantage for their employment opportunities compared to those who have not completed an internship. On top of that, most students are seeking internship opportunities to increase their marketability after graduation, to receive more job offers, offer an intangible morale boost, are able to do real work like a regular employee would normally do and even 110

that some of them are offered a starting salary which is quite high. This also has been supported from the findings of Cannon and Arnold (1998) that students are using an internship program as a method of getting a job. They also have suggested that the faculty should consider the structure of an internship program which should reflect less on the academic value in the internship, including less paper writing and exams, and outside reading, and should add more to increase both the quantity and quality of the available internships. It is also interesting to note that their findings reveal that the students with lower GPA showed greater agreement with the notion that internship would lead to obtaining fulltime jobs and disagreed with the ideas of writing papers. In the study of Cook et al. (2004), they revealed that students perceive the value of internships largely in the social aspects and for enhancing personal maturity. Furthermore, the researchers have reported that 89 percent indicated that participation in the internship program was a valuable experience, and 66 percent of the students indicated their agreement with the notion that internship experience helped them to relate academic theories learned in the classroom to the workplace‘s experiences. Cook et al.. added that the students seem to believe that the internship experiences would not influence their choice of careers however those experiences would make them more confident in their abilities to obtain a job in their fields of choice. Furthermore, internships also assist to develop and enhance job skills that relate to their field of job environment. This is supported by the study of Kardash (2000), who investigated the perspectives from both undergraduate interns and faculty mentors of learning in a research laboratory. She found that undergraduates‘ research experiences (URE) increase interns‘ abilities to engage in the real environment of ‗scientist‘ and have a positive impact on development of interns‘ research skills. There are few arguments with regard to the payment of internship. Some students prefer wellpaid internship that is commensurate with their work contributions, while some have lower expectations of high payment job. Garrett and Bauer (1995), found that students preferred paid internships and wanted to receive academic credit for the internship experience. However, Lam and Ching (2007) found that students had the lowest expectations of training allowances, since their major purpose of internship is to fulfill the program requirements and to acquire practical experience, but not to earn money. Indeed, job experience is worthy rather than high compensation and most students seem to prefer to develop job opportunities possibly in the same placement upon their graduation. Lam and Ching (2007) reported that students who perform well in the training period always increase their chances of being employed again by the placement companies and treat this internship as a stepping-stone to entry into the field. In the context of internship in accounting education, Beck and Halim (2008) explored the impact of internships on accounting students, and identified that among the learning outcomes of the internship, two factors, self-efficacy/ interpersonal skills and computer skills were considered as significantly very important for their future career development. In addition, the acquisition of those skills was supported by completing a logbook (useful to expedite Reflective Learning) and interestingly, they also found that a realistic experience of working under pressure in the accounting internship influenced the students to consider alternative professions. In the Malaysian context, Muhammad et al. (2009) found that students did not benefit from the internship attachment due to difficulty of adaptation to the working environment and this difficulty is rooted from not being treated as regular employees and thus they were not being given appropriate and specific tasks that related to job settings and experience exposure. They also suggested that faculty staff of the university should assist

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the students to arrange their internship placement and that the most appropriate internship period should be six months instead of three months or less.

RESEARCH METHODOLOGY Instrumentation This study adopted a quantitative research design, where a self-administered questionaire was developed in order to meet the objectives of the study. The questionnaire items that related to internship perceptions were adopted from several existing literature, such as Lam and Ching (2007), Patterson and George (2002), Alpert et al. (2009), and Kandasamy and Ancheri (2009). The structured questionnaire consisted of two sections. Section one collected the socio-demographic data of respondents such as gender, age, location of internship, type of university, type of company involved during internship and also respondent‘s CGPA results. Section two examined the respondents‘ perceptions towards the internship program and overall it consisted of 25 internship variables. For instance, for one of the variables in internship perception ―develop technical skills‖, the respondents were asked to provide their perceptions on technical skills whether the technical skills were gained after completing their internship, measured on a 5-point Likert-type scale that ranged from „strongly disagree‟ (1) to „strongly agree‟ (5). Samples and sampling procedures The sampling frame of this study consisted of accounting undergraduates from both public and private universities. The sample of the study involved final year accounting students who were completing their internship program. The questionnaires were distributed through the mail to the respective companies that provided an internship program for undergraduates. The respective companies were identified through faculty members who were responsible to manage the internship procedures and placement for undergraduates. Altogether, 190 questionnaires were distributed and 168 were collected from the respondents, representing a response rate of 90.5 percent. However, 27 questionnaires were discarded due to incomplete information. Therefore, total available questionnaires used in this study were 141. Scale reliability analysis was used to measure the internal consistency of the internship perceptions construct, and a generally agreed upon lower limit for the Cronbach‘s alpha was set at 0.70 (Coakes, Steed and Price, (2008)). In order to assess the normality distribution for a particular variable, a normality test was used using the Kolmogorov-Smirnov and ShapiroWilk tests. In addition, the researchers also utilised factor analysis in order to find a smaller number of factors that attributed to students‘ perceptions towards an internship program. Principal components (PC analysis) and VARIMAX rotation method were used to factor analyse the 25 internship variables into a set of composite factors, eigenvalues equal or greater than 1.0 were considered significant, and chosen for interpretation, while factor loadings equal to or greater than 0.3 were chosen for analysis since this matrix is suitable for factoring (Juat Hong, (2007); Coakes et al., 2008). Meanwhile, multivariate analysis was conducted in order to examine the significant differences between demograhic data i.e. gender , CGPA Results and type of placement company, and the six factors (dimensions) of internship perception (Palaniappan, (2011); Coakes et al., (2008) .

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DISCUSSION OF FINDINGS Descriptive Findings Table 1 shows that among 141 respondents, 65.2 percent were female and 34.8 percent were male. Such a finding is commensurate with the general phenomenon that almost all the accounting faculty in business schools in most universities in Malaysia has more female students than males. Majority of the students were in the age range of 21- 22 years of age (72.3percent), 31 students (22 percent) were in the age range of 23 - 24, and only 8 students (5.7 percent) were in the category of 25 years and above. Meanwhile, most of the students were Malay (64.5 percent), followed by Chinese (24.1 percent), Indian (8.5 percent), ethnics from Sabah/Sarawak represents 2.1 percent and only one person was Punjabi (.70 percent). Majority of the respondents were from private universities (60.3 percent), while the rest were from public universities (39 percent). In addition, the internship program with a duration period of 6 months was taken by most students (83.0 percent), while 7.1percent undertook their internship for a 3-month period, and there were nine students (6.4 percent) undertook internship for more than a 6 -month period because some of them were required by the company to stay a longer period due to insufficient staff. Meanwhile, there were very few students (3.4 percent) who undertook an internship period of less than 3 months. More than half of the respondents (60.3percent) undertook their internship in medium tier accountant firms, 10.6 percent had their internship in the Big-Four accounting firms, 23.4percent were in small accountant firms, 5.0 percent were in non-accounting firm and the remaining 0.7percent were in other types of company placement, i.e. government sector. The Big-Four audit firms are the largest international accounting and professional services firms, such as KPMG, PWC (PriceWaterhouseCoopers), Ernst & Young and Deloitte. Other than these BigFour audit firms would fall under category of medium or small audit firms. Majority of the respondents had their internship in the vicinity of Klang Valley (73 percent), 7.1 percent of them were in the East Coast Malaysia, and 9.9 percent of the respondents‘ internship placements were located in Northern and Southern areas of Peninsular Malaysia. The number of respondents who scored the Cumulative Grade Point Average (CGPA) in the range of 3.50 and above (n = 33, 23.4 percent) were slightly different to the number of respondents who scored CGPA in the range of 2.50 – 2.99 (n = 30, 21.3 percent). More than half of the respondents obtained CGPA 3.00 – 3.49 (n = 75, 53.2 percent), and only 2.1 percent respondents obtained the range of CGPA, 2.00 – 2.49. Almost half of the respondents sought their placement through Internet (48.9 percent), 31.2 percent were introduced by their family or friends, 14.2 percent was recommended by lecturers, 3.5percent sought through advertisement in profession-related magazines i.e. Malaysia Institute of Accountants (MIA) and even in newspapers, and the rest of 2.1percent sought the placement by doing some surveys on potential internship placements.

TABLE 1: PROFILES OF THE RESPONDENTS (n = 141) Variable Gender: Male Female

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Frequency

Percentage (percent)

49 92

34.8 65.2

Age: 21-22 23-24 25 years and above

102 31 8

72.3 22.0 5.7

Race: Malay Chinese Indian Bumiputera Sabah/Sarawak Others:

91 34 12 3 1

64.5 24.1 8.5 2.1 0.7

Type of University Public university Private university

56 85

39.7 60.3

Duration: Less than 3 months 3 months 6 months 6 months and above

5 10 117 9

3.5 7.1 83.0 6.4

Type of company: Accountant Firm -Big-Four Accountant Firm –Medium Tier Accountant Firm – Small company Non-Accounting Firm Others

15 85 33 7 1

10.6 60.3 23.4 5.0 .70

Location: Klang-Valley East Coast Area (Pahang, Kelantan & Terengganu) Northern Area (Perak, Penang, Kedah & Perlis) Southern area (Negeri Sembilan, Melaka & Johor)

103 10 14 14

73 7.1 9.9 9.9

CGPA: 3.5 and above 3.00 -3.49 2.50 – 2.99 2.00 – 2.49

33 75 30 3

23.4 53.2 21.3 2.1

44 20 69 5

31.2 14.2 48.9 3.5

3

2.1

Selection of the Internship Placement: Introduced by friends/family Advised by lecturer Find through Internet Find through newspapers or profession-related magazines Others: Find myself

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Inferential Statistics Factor Analysis Principal component analysis followed by VARIMAX rotation was employed to analyze the l 45 perceptions internship variables based on the Eigenvalues of 1 and above, and factor loadings of 0.3 and greater. Results as shown in Table 2 suggest that 6 factors were developed for an internship perception scale with its 25 variables for interpretation of the scale. They explained 69percentpercent of the perception‘ variance with a Kaiser-MeyerOlkin (KMO) measure of the sampling adequacy of 0.906, and the Barlett Test of Sphericity of 2139.58 (p = 0.00) for respondents‘ perceptions on internship. All 25 variables were included in the subsequent analysis as their results were shown as having high communalities (>0.30) and all were significant. The six factors underpinning the perception scale that have been developed t from the analysis were ‗task identity and work appraisal‘ (5 items), ‗future employment benefits‘ (5 items), ‗manageable workload and support from manager‘ (4 items), ‗job-related skills and adaptation‘ (6 items), ‗encouraging environment in the workplace‘ (3 items) and ‗self-quality improvement‘ (2 items). Among these factors, some were similar to the findings of Lam and Ching (2007), for example manageable workload and support from manager (Factor 3), and future employment benefits (Factor 2). The reliability tests indicated that the reliability coefficients of the six factors ranged from 0.78 to 0.88 that were close or greater than the recommended significance level of 0.70 which implies a relatively high internal consistency (Juat Hong, 2007).

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TABLE 2: FACTOR ANALYSIS ON INTERNSHIP PERCEPTION VARIABLES Variables

Factor 1: Task Identity and Work Appraisal Clear job description Emphasized on quality improvement Fair treatment and appraisal Appraisal on work contribution Confident on internship Factor 2: Future Employment Benefits Resume Technical skills Future career development Broad experience Good communication Factor 3: Manageable Workload & Support from Manager Manageable workload Acceptable work pressure Tolerable manager Support from manager

Factor Loading

Communality

.778 .754 .706 .675 .607

.793 .836 .746 .716 .610

.787 .754 .663 .544 .532

Eigen-value

percent of variance

Cum.var percent

10.821

43.285

43.285

1.655

6.618

49.904

1.326

5.303

55.207

.747 .722 .783 .672 .524

.726 .726 .593 .587

.742 .654 .629 .749

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Factor 4: Job-Related Skills and Adaptation Opportunity future employment Challenging task Minimum supervision Develop interests and skills Teamwork Fair compensation Factor 5: Encouraging Environment in the Workplace Growing and well-performance of company Healthy work environment Well-known brand image company Factor 6: Self-Quality Improvement Self-development Able to meet deadlines

.862 .560 .528 .491 .416 .392

1.260

5.039

60.245

1.130

4.520

64.765

1.058

4.233

68.998

.813 .667 .667 .556 .622 .595

.820

.792

.790 .586

.757 .684

.763 .454

.589 .667

Rotated factor matrix: Extraction method: Principal Component Rotation method: Varimax with Kaiser Normalisation a. Rotation converged in 8 interations

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TABLE 3 : RANK OF INTERNSHIP PERCEPTION : RANK OF INTERNSHIP internship Factor Factor 1: Task identity and work appraisal Factor 2: Future employment benefits Factor 3:Manageable workload and support from manager Factor 4: Job-related skills and adaptation Factor 5: Encouraging environment in the workplace Factor 6: Self-quality improvement

Perception Mean (standard dev.) 20.55 (3.473) 21.57 (2.865)

Rank

16.348 (2.610) 24.25 (3.628)

4 1 5

12.77 (1.892) 8.77 (2.750)

3 2

6

perception by six (6) factors (n= 141)

The perceptions means of the six factors were calculated in order to find the ranking among them. Table 3 shows that the largest mean was ‗job-related skills and adaptation‘ (m= 24.25, s.d.= 3.628, R=1), followed by ‗future employment benefits‘ (m=21.57, s.d.=2.865, R=2), suggesting that the students perceived that these two dimensions (factors) were the most important elements they gained during the internship period and these elements would be useful to them especially when they are searching for permanent jobs upon their completion of study. However, they perceived less importance of factors such as ‗encouraging environment in the workplace‘ (m=12.77, s.d. =1.892, R=5) and ‗self- quality improvement‘ (m = 8.77, s.d.2.750, R=6). Multivariate ANOVA Analysis MANOVA was undertaken to investigate gender, students‘ academic performance (CGPA results) and type of company placement differences in the six (6) internship perception factors. All assumptions relating to normality, linearity, univariate and multivariate outliers (Mahalanobis Distance within required limits), homogeneity of variance – covariance matrices (Box‘s M for three independent variables were not significant at p .05; and F (3,137) = 1.004, p > 0.5, respectively. However, we found that there was a significant difference in the type of company placement and internship perception factor, F (4, 136) = 1.952, p < 0.5. The findings revealed that there were significant differences between the different type of company placement and the students‘ perception of the usefulness of the internship program. It is empirically found that ―job-related skills and adaptation‖ (Factor 4)) was significantly different between the students in small accountant firms and medium tier accountant firms (p = .015), and between the students in the small accountant firm and Big-Four accounting firms (p = .002). These findings implied that those students who were placed in the Big-four and medium- tier accountant firms were found easily to get acquainted with other staff in the company and gained those job-related skills within a shorter period compared to those students in the small accounting firms. This indicates that those students who were being in the larger and medium-tier of accounting firms were perceived that they being more confident, independent, high self-esteems, simultaneously possessed valuable workrelated skills during the internship period, compared with other students who were being in. 118

CONCLUSION & FUTURE RESEARCH This study attempted to answer the following question: What do students perceive after their internship completion? What are the factors underlying the internship perceptions? Are there any significant differences of what students perceived between demographic factor such as gender, CGPA results and type of company placement. The findings of the study have shown that there were six dimensions/ factors which came from the students‘ perception on internship. The students perceived job-related skills and adaptation in the company (Factor 4) as the most important, followed by future employment benefits (Factor 2), and task identity and work appraisal (Factor 1) as the third ranking of the students‘ perceptions on their internship. On the other hand, the majority of the students did not perceive the reputation of the company or an encouraging environment (Factor 5) or self-quality improvement (Factor 6) as so important which would reflect on their job searching when they completed their study. The researchers also would like to examine whether there were significant differences in students‘ perception towards internship which might vary across the three tested demographic factors of gender, CGPA results and type of placement company. The findings suggest that those students from different types of company placement have perceived differently on the internship dimension, especially on the job-related skills and adaptation (Factor 4) as students have experienced those things during internship based on their on-job-training per se. On the other hand, there were no significant differences found between other demographic factors and other dimensions. Hence, it is recommended for future studies to be conducted that can include a larger sample size to be collected from both private and public universities. In addition, students‘ perception could be incorporated with students‘ expectation in order to measure the level of students‘ satisfaction towards internship. Perhaps, further investigation on the comparison between the students‘ expectations towards internship, and their employers‘ expectations towards the students‘ performance during internship can also be examined to produce fruitful contribution to the existing literatures.

REFERENCES

Beard, D.F., (1998) The status of internships/cooperative education experiences in accounting education. Journal of Accounting Education, Vol. 16, No. 3/4, 507-516. Beck, J.E. and Halim, H., (2008). Undergraduate Internships in Accounting : What and How do Singapore Interns Learn from Experience?. Accounting Education: An International Journal, Vol.17,No2,151-172. Callanan, G., and Benzing, C., (2004). Assessing the role of internships in the career-oriented employment of graduating college students. Education and Training, Vol. 46, No. 2, 82-89. Cannon, J.A., and Arnold, M.J., (1998). Student expectations of collegiate internship programs in business: A 10-year update. Journal of Education for Business,, 73, 4, ABI/INFORM Global, 202205.

119

Caroll, S.J., (1966). Relationship of various college graduate characteristics to recruiting decisions. Journal of Applied Psychology, 50, 421-423. Chong, M. (2005) ―Employable Skills‖, Thestar.online.com.my., August, 21 2005. Retrieved on 4 June 2012. Collins, A.B., (2002). Gateway to the real world: industrial training, dilemmas and problems. Tourism Management, 23 (1), 93-96. Cook, S.J., Parker, R.S., and Pettijohn, C.E., (2004). The perceptions of interns: A longitudinal case study. Journal of Education for Business, 79, 3, ABI/INFORM Global, 179-185. Dennis, A., (1996). The benefits of using college interns in a firm. Journal of Accountancy, 181, 889-892. Dykxhoorn, H.J.,and Sinning,K.E., (1996). Perception of master of accountancy graduates concerning their job search and employment experiences with public accounting firms. Journal of accounting Education, Vol.14, No.4, 415-434. Gault, J., Redington, J., and Schlager, T., (2000). Undergraduate business internships and career success: are they related? Journal of Marketing Education, 22 (1), 45-54. Geiger, M.A., and Ogilby, S.M., (2000). The first course in accounting : students‘ perceptions and their effect on the decision to major in accounting. Journal of Accounting Education,,63-78 Harris, K.J., and Zhao, J., (2004). Industry internships: Feedback from participating faculty and industry executives. International Journal of Contemporary Hospitality Management. Vol. 16, No. 7, 429-435. Healy , C.C., and Mourton, D.C., (1987). The relationship of career exploration, college jobs, and grade point average. Journal of College Student Personnel, 28, 28-36. Henry, N., (1979). Are internships worthwhile? Public Administration Review, 245-247. Hite, R., and Bellizzi, J., (1986). Students expectations regarding collegiate internship programs in marketing. Journal of Marketing Education, 8 (3), 41-49. Kai-Wen, C., (2011). A study on relationship between personality traits and employment factors of college students. Journal of Case Studies in Education. pg. 1-9. Kandampully, J., Mok, C., and Sparks, B., (2001). Service Quality Management in Hospitality , Tourism and Leisure, New York, Haworth Hospitality Press. Kardash, C.M., (2000). Evaluation of an Undergraduate Research Experience : Perceptions of Undergraduate Interns and Their Faculty Mentors. Journal of Educational Psychology, Vol.92, No.1, 191-201. Knouse, S.B., Tanner, J.R., and Harris, E.W., (1999). The relation of college internships, college performance, and subsequent job opportunity. Journal of employment Counselling, 36 (1), AB/INFORM Global, 35-43. Kusluvan S., and Kusluvan Z., (2000). Perceptions and attitudes of undergraduate tourism students towards working in the tourism industry in Turkey. Tourism Management, 21(3), 251-269.

120

Lam, T. and Ching, L., (2007). An exploratory study of an internship program: The case of Hong Kong students. Hospitality Management, 26, 336-351. Muhamad, R.,Yahya,Y., Shahimi, S. and Mahzan, N., (2009). Undergraduate Internship Attachment in Accounting : The Interns Perspective. International Education Studies,, Vol.2,No.4, pg. 49-55. Nadiri, H., Kandampully, J., and Hussain, K., (2009). Students‘ perceptions of service quality in higher education. Total Quality Management,, 20 (5), 523-535. Narayanan, V.K., Olk, P.M., and Fukami, C.V., (2010). Determinants of internship effectiveness: an exploratory model. Academy of Management Learning and Education, Vol. 9, No. 1, 61-80. Ng, E.S.W., L, Schweitzer., Lyons, S.T., (2010). New Generation, Great Expectations: A Field Study of the Millennial Generation. Journal of Business Psychology, 25,281-292. Nonoka, I., and Takeuchi, H., (1995). The Knowledge Creating Company : How Japanese companies create the dynamics of innovation, New York, Oxford University Press. Pasewark, W.R., Strawser, J.R., and Wilkerson Jr., J.E., (1989). An empirical examination of the effect of previous internship experience on interviewing success. Journal of Accounting Education, Vol. 7, 25-39. Patterson, D.K., and George, C., (2002). Mapping the contract : An exploration of the comparative expectations of graduate employees and human resource managers within the hospitality,leisure and tourism industries in the United Kingdom. Journal of Services Research, Vol.2, No.1, pg. 55-74. Pianko, D., (1996). Power internships. Management Review, 85, 12 ABI/INFORM Global, 31– 33. Tang, G. (2005), ―Employable Skills‖, Thestar.online.com., August 21, 2005. Retrieved on 4 June 2012. Taylor, M.S., (1988). Effects of college internships on individual participants. Journal of Applied Psychology, 73, 939-401. Wasonga, T.A, and Murphy, J.F., (2006). Learning from tacit knowledge: the impact of the internship. International Journal of Educational Management,, Vol. 20, No. 2, 153-163. Weible, R., (2010). Are universities reaping the available benefits internship programs offer?. Journal of Education for Business,, 85, 59-63. Wood, S., (1986). Work experience that works. Personnel Management, 18 (11), 42-45.

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SHOPPING BEHAVIOR AND DETERMINANT FACTORS OF MALL PATRONAGE AMONG GEN Y. Khairul Nizam Surbaini Department of Marketing & Entrepreneur Development College of Business Management and Accounting Universiti Tenaga Nasional (UNITEN) Muadzam Shah,Pahang. Email : [email protected] Abdul Rahman Zahari Department of Marketing & Entrepreneur Development College of Business Management and Accounting Universiti Tenaga Nasional (UNITEN) Muadzam Shah,Pahang. Email: [email protected] Elinda bt Esa Department of Accounting College of Business Management and Accounting Universiti Tenaga Nasional (UNITEN) Muadzam Shah,Pahang. Email: [email protected] ABSTRACT The superiority of the shopping mall as a social interaction and entertainment destination has given a significant impact on business strategies. The purpose of this paper is to assess the shopping behavior and the factors involved in selecting one shopping mall among Gen Y. A total of 364 usable surveys were obtained from a shopping mall i.e. East Coast Mall (ECM), Kuantan, Pahang, Malaysia. Findings shows that gen Y were visiting the shopping mall less and 46.2 per cent visited the mall once in a month. Moreover, they only spent RM 100 and below per month and the numbers of different stores visited by Gen Y were quite small with only 4 to 6 stores during a visit at the stated shopping mall. In addition, mall convenience, service quality, and mall loyalty are influenced by gender. Levels of age and income have significant influence with the overall mall environment, mall awareness, mall entertainment, and mall convenience. However the other demographic characteristics are found be insignificant with mall awareness and mall image. Keywords: Shopping Behavior, Mall Awareness, Mall Image, Gen Y. INTRODUCTION A shopping mall is a group of retail businesses planned, developed, owned, and managed as a unit. It can be divided into a regional shopping mall, a community shopping mall, strip malls, and power centres (Kotler, (2006). Graham, (1988) discussed mall shopping that has become an expression of personal values. In many instances, the shopping mall is a social and recreational meeting place 122

attracting youngsters and seniors. The characteristics of shopping malls are important to attract potential customers or shoppers to frequently visit them (Yusniza and Lee , (2010). Moreover, shopping as an everyday activity permeates societal processes and social conventions (Miller, 1998). This behavior is acquired through social interaction and is context and situation-based. More people are perceived to get something of a more valuable shopping experience particularly relate to shopping malls environment. Thus, this may force the shopping mall to match up with the needs and wants of people with new designs, decorations, an ambient atmosphere and a more attractive mall environment. Malls also are viewed as cultural and entertainment centers. Most of the research studies have identified mall ambience, decoration, environment and facilities provided which contribute to mall patronage and also are an attraction. The mall is an important retail venue that generates to consumer experience and Carbone (1999) mentioned that any future purchase is more a result of how customers feel about a mall or company than what they think about the product or service. The rise of Gen Y in spending their money at shopping malls has been seen to be a chance for researchers to explore this generation‘s habits in a shopping mall and investigate the factors that attract them to patronage of the shopping mall. Gen Y is the group of teenagers having the most money ever to spend about 51% more than teenagers in 1995 (Morton, 2002). An the average teenager is estimated to spend more than 100 dollars per week and they seem to prefer shopping in malls than on the Internet or by catalogue which means that 44% of teenagers patronize their favorite mall during weekends (Zollo, (2004). Besides, Taylor and Cosenza, (2002) stated that shopping for teenagers is exciting, interesting, and fun. According to Mediamark Research Inc.‘s Teen Market Profile, Gen Y prefers shopping in malls and visits shopping centers more often than other age groups (Quart, 2003). Based on previous studies in Malaysia, most of the generation Y (Gen Y) are motivated to shop at a mall because of the interior design of the mall, products that interest them, opportunities to enjoy and socialize with their group and also is a convenient one stop shopping centre (Ahmed, et al. 2006). They also highlighted that shopping malls have transcended their role as a business activity to become a community center for social and recreational activity. So that there is an increasing trend of Gen Y for pleasure and spending their time in shopping centers. Thus, this paper‘s aim is to determine the shopping behavior of Gen Y and the factors that contribute to mall patronage among Gen Y. LITERATURE REVIEW Shopping Behavior Consumer behavior can be defined as the behavior that consumers display in searching for, purchasing, using, evaluating and disposing of products and services that they expect will satisfy their needs (Schiffman & Kanuk, (2010). According to Tauber (1972), consumer behavior consists of three distinct activities: shopping, buying, and consuming. More progress has been achieved in identifying behavioral dimensions of buying and a number of theories on buying behavior have been postulated in past research. However, a smaller number has researched about the determinants of consuming and shopping behavior. Generally, there are many discussions about consumer shopping. Shopping has been described as an activity that refers to the obtaining consumer goods. It is also considered as an expressive activity such as shopping for consumer goods, dreaming about outfits and objects. (Ramli, (2010). Lately, the study on shopping behavior seems to suggest that the key factors to attract customers and retain them are accessibility or location, new design, the assortments of retailers, leisure attraction, the communication mix, cost of access, customer services provided and the interaction between centre 123

,store and customer participants (Kirkup and Rafiq, (1999) Yusniza and Lee , 2010). In his study, Assael, (1987) had discussed shopping behavior as a distinctive form of consumer behavior. Tauber (1972) also argued that shopping is more than plain purchase but also as leisure activity. Generation Y In their study Schiffman & Kanuk, (2010) define Generation Y (Gen Y) as an age cohort of individuals born over a relatively short and continuous period of time and which includes somewhere between 80 and 100 million Americans aged 30 and under in 2008. They are the children of baby boomers and depending on the source, were born between 1977 and 1994, or between 1982 and 2000. In addition, these age groups have significant buying power. Gen Y is often typified as being highly consumption oriented and sophisticated in terms of tastes and shopping preferences. (Wolburg and Pokrywczynski, (2001). This group has had a profound impact on retail businesses because Gen Y members love to shop. Research has shown that for members of Gen Y, social motivation predicts perceptions of atmospheric qualities of a shopping environment, perceptions of excitement at a mall and intention to return to a mall in the future (Martin and Turley, 2004). According to Foot and Stoffman, (2000), Gen Y is the most important demographic cohort after the baby-boomer generation. They were born between 1980 and 1995; these young consumers are today between 13 and 28 years old, half of which are teenagers (13–19 years old). This group represented about 60 million consumers in America (Neuborne and Kerwin, (1999). Furthermore, younger segments are considered to be window browsers and window shoppers (Jarboe and McDaniel, (1987). And, teenagers use the mall as a place to hang out, meet friends or to make new ones (Shopping Center Age, 1994). What factors motivate Gen Y to re-patronage the shopping mall? According to Bloch et al. (1994), the factors that are influencing Gen Y to be attracted in visiting shopping malls include aesthics (location, décor, noise, aromas, lighting intensity, physical layout, and also music), convenience (close proximity with their homes, universities, colleges and schools, travel time, business hours, and one stop center), social (seeking new acquaintances and meeting the opposite sex), and also escapism (seek freedom after school and their routine life i.e. hang out with their friends in shopping malls). Besides those three factors by Bloch, Chebat and Hedhli (2009) they also stated two major components for consumers to re-patronage shopping malls i.e. mall awareness and mall image. They defined mall awareness as the informational node associated with the name of the mall in the shopper's memory, representing the extent to which a shopper is able to recognize and easily recall the mall characteristics. Mall awareness relates to the likelihood that mall characteristics will come to a shopper's mind, and the ease with which it does so. Thus, mall awareness would be reflected by mall recognition and mall recall performance. Mall recognition represents the shopper's capacity to correctly discriminate a particular mall (e.g., its characteristics) from competitor malls. The role of mall awareness in managing the mall equity is to increase the possibility that the mall will be included in the shopper‘s consideration set. Moreover, the strength of mall awareness could positively impact on the mall selection among shoppers. In addition, mall awareness will help to develop the mall image due to the information-rich embedded in shoppers‘ mind. Keller (2008) defined awareness is related to the strength of the node or trace in memory, where the consumers can measure the ability to identify the mall under different conditions. Therefore, awareness with strong associations forms a specific mall image. Moreover, awareness plays an important role in consumer decision making by bringing three advantages; these are learning advantages, consideration 124

advantages, and choice advantages. What is more, awareness is the result of a consumer‘s detection to the brand through the advertisement, publicity or other methods in integrated marketing communications. Moreover, Chebat and Hedhli (2009) defined mall image as representing the way in which a mall is defined in the shopper‘s mind. It is the set of functional qualities as perceived by shoppers (e.g., convenience, parking facilities, and services quality) as well as an aura of psychological attributes (e.g., salesmanship and atmosphere). Wakefield and Baker (1998) mentioned that the mall environment shows that music and layout in a shopping centre give a positive relationship of excitement and desire to stay in the shopping centre. The atmosphere in a shopping centre manipulates internal design and layout including space utilization and environment, colour and sound. Mall convenience is related to the factors of security, cleanliness, parking space, wide and comfortable in the shopping mall. These factors can influence the consumer to decide which shopping mall that they intent to visit (Wong et al. (2001); Bellenger et al. 1977). Garvin (1984); (1987) introduced a well-known framework of product quality based on eight dimensions namely performance, features, reliability, conformance, durability, serviceability, aesthetics, and perceived quality. Moreover, product quality is often considered to contribute to the development of competitive advantage. Thus the manufacturers need to design and produce products tailored to customers‘ need and want (Benson et al. (1991); Flynn et al., (1994). Perceived quality is defined as ―the customer‘s perception of the overall quality or superiority of a product or service with respect to its intended purpose, relative to alternatives‖ (Zeithaml, 1988). It is a competitive necessity and many companies today have turned customer-driven quality into a potent strategic weapon. They create customer satisfaction and value by consistently and profitably meeting customers‘ needs and preferences for quality. In addition to the above definition, Kotler (2000) mentioned that perceived quality draws attention to the intimate connection among product and service quality, customer satisfaction, and company profitability. Moreover, Parasuraman et al., (1985) mentioned that there are several factors to be considered in order to analyze and measure perceived quality, such as reliability, serviceability, appearance, performance, durability, etc. From the definitions given above, perceived quality is relating to the ability of the products or services to meet the customer satisfaction in terms of durability, performance, color, multiple functions and other factors.. In the other words the perceived quality can be explained as meeting the satisfying level of customers. From the manufactures view, the perceived quality can be achieved through the conformance of the design with the actual products. Bellenger et al., (1977) identified that a movie theatre is the first entertainment item and was associated with an attribute called ‗presence of related services‘. Nevin and Houstan (1980) included special events or exhibits as part of mall entertainment. Fresquest et al., (2001) explained two entertainment items i.e. events and exhibitions, and attractive leisure offer were classified with the ―atmosphere/leisure‖ attribute. Entertainment is a big factor for a shopping centre because it causes consumer shopping experience to become exciting or delighting. Moreover, the transformation of shopping into a pleasurable experience specifically focuses on entertainment which has thus become a common strategy among retailers (Jones, 1999) and nowadays, retail stores are increasingly adding entertainment services to the traditional retail mix. This can attract loyalty and fix customers on that shopping centre (Haynes & Talpade (1996). Items which are needed in this factor are such as having a cinema in a shopping centre (Bellenger et al. 1977) indicates to have a specific area to show or display special events and various kinds of entertainment (Wakefield & Baker (1998). Mall Loyalty 125

Aaker (1991) defines loyalty as a situation which reflects how likely a customer will be to switch to another brand, especially when that brand makes a change, either in price or in product features. While, Keller (2003) examines loyalty under the term ―brand resonance‖ which refers to the nature of customer-brand relationship and the extent to which customers feel that they are ―in sync‖ with the brand. Moreover, Amine (1998) in her literature distinguishes two main approaches to define the loyalty construct: the behavioral one suggests that the repeat purchasing at a mall over time by a consumer expresses their loyalty, and; the attitudinal perspective which assumes that consistent buying at a mall is a necessary but not sufficient condition of ‗true‘ loyalty and it must be complemented with a positive attitude towards this mall to ensure that this behavior will be pursued further. In addition, Chaudhuri & Holbrook (2001) had proposed a model of loyalty that suggests that purchase loyalty tends to lead to greater market share, while attitudinal loyalty leads to higher relative mall pricing. METHODOLOGY The study was conducted in one small city in Malaysia (Kuantan,Pahang) and attached shopping mall namely East Coast Mall (ECM). We have succeeded and obtained a sample size of 364 respondents which is Generation Y (Gen Y). These completed questionnaires yielding a response rate of 80.89 %. In addition, this research used non-probability sampling, where the inclusion or exclusion of elements in a sample is left to the discretion of the researcher (Hair et al., 2007). This study used the mall intercept method of sampling to gather the data from respondents. The shoppers were randomly solicited and invited by researchers to complete a self-administered questionnaire after their shopping trip. The questionnaire contains five parts: the first part is shopperbased mall equity constructs. The second part is pertaining to mall loyalty. The third part refers to mall equity constructs. The fourth part represents the questions about the shopping behaviors and the last part is the profile of respondents. Mall awareness was measured by 5 items adapted from Yoo, Donthu, and Lee (2000). In addition, mall loyalty was measured by 3 items and mall equity (6 items) was also adapted from Yoo, Donthu, and Lee (2000). Mall convenience was captured by 5 items adapted from Downs (1970) as well as from Frasquet et al., (2001), Wong et al.al. (2001) and Bell (1999). Overall mall environment was captured by 6 items adapted from Fisher (1974) as well as from Mehrabian and Russel (1974). Two items were adapted from Dabholkar, Thorpe, and Rentz (1996), while 3 items are from Berman and Evans (2001) to assess shoppers' subjective judgments about the mall's overall service quality. The perceived products' quality was captured using 3 items adapted from Dodds, Monroe, and Grewal (1991) and another 2 items was adapted from Frasquet et al., (2001), Wong et al.., (2001). Mall entertainment was measured by 5 items adapted from Bellenger et al., (1977), Nevin and Houston‘s (1980). Thus, the resulting initial pool contained 40 items. The items were measured on 7point scale from 1 (strongly disagree) to 7 (strongly agree). The completed instrument was pre-tested by 25 respondents at UNITEN. Based on the feedback obtained from these respondents, the questionnaire was subsequently refined. Data obtained from the personally administered questionnaire was analyzed using some statistical tools contained in the statistical software. i.e., ‗Statistical Package of Social Science‘ (SPSS) 19.0 for Windows. Besides descriptive analysis, two different statistical analyses were used in this study including T-test, and analysis on variance (ANOVA).

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RESULT AND DISCUSSIONS As mentioned earlier, the total number of respondents for this study is 364. The study sample comprises respondents who vary on such demographic characteristics such as gender, age, ethnic, education level, job position level, income level and marital status. In spite of various demographic characteristics, all respondents are generation Y. Table 1 shows the respondents profile. The study sample constitutes respondents who depart on such attributes as gender, age, marital status, education level, job position, income level and ethnicity. As mentioned before, the total number of respondents for this study is 364. From the total of 364 respondents, 31.6 per cent are male respondents and the remainder 68.4 per cent are female respondents. Also, there are about 55.5 per cent respondents in the age range between 18 to 22 years old and majority of respondents are not married with 84.3 percent. Furthermore, with respect to ethnics groups, majority (335) are Malays, the remainder 8 per cent are Chinese, Indian, Bidayuh, and other ethnic groups. Most of the respondents in this current study are degree holders with 48.1 per cent and then followed by Diploma holders with total number amounting to 133 respondents. Moreover, it clearly indicates that most of the respondents (75.3 per cent) are students and the top management represents the smallest percentage (0.5 per cent). On the other hand, 72.8 per cent of the respondents have an income level below than RM 1,000 per month and only 4.7 per cent manage to get a salary more than RM 4000 per month.

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TABLE 1: DESCRIPTIONS OF RESPONDENTS

Item

Description

Gender

Male Female

Frequency n = 364 115 249

Age

18 to 22 years old 23 to 27 years old 28 to 32 years old

202 98 64

55.5 26.9 17.6

Ethnic

Malay Chinese Indian Bidayuh Indonesian Others

335 9 16 2 1 1

92.0 2.5 4.4 0.5 0.3 0.3

Level of Education

SPM/MCE STPM/HSE Diploma Degree Masters/PHD

21 3 133 175 32

5.8 0.8 36.5 48.1 8.8

Job Position

Professionals Top Management Middle Management Lower Management Admin and Technical Support Student Lecturer

64 2 11 5 4 274 4

17.6 0.5 3.0 1.4 1.1 75.3 1.1

Income Level

Below 1000 1001 to 2000 2001 to 3000 3001 to 4000 4001 and above

265 19 34 29 17

72.8 5.2 9.3 8.0 4.7

Marital Status

Single Married

307 57

84.3 15.7

Percentage 31.6 68.4

Table 2 shows the shopping habit of Generation Y at East Coast Mall (ECM), Kuantan, Pahang. Most of the respondents (33 per cent) went to East Coast Mall (ECM) and spent an average time of 1.1 hour to 2 hours. Furthermore, about 11 per cent of them spent an average time of more than 4 hours during their visit to East Coast Mall (ECM). There are 37 respondents who mentioned that they cannot identify the number of different stores visited, while 38.7 per cent visited 4 to 6 different stores and 15.4 per cent declared that they visited 10 or more different stores at East Coast Mall (ECM). In addition, Table 2 also shows that only 1.1 per cent of the respondents visited East Coast Mall (ECM) everyday. Large numbers of respondents mentioned that they visit the East Coast Mall 128

(ECM) once every two weeks or once a month with 46.2 per cent and 28.8 per cent respectively. Moreover, 87 of respondents visited East Coast Mall (ECM) once a week. Since the majority of the respondents‘ incomes were limited to scholarships, study loans, and fathers‘ or mothers‘ contributions, it may slow down the monthly expenditure spent in the East Coast Mall (ECM). The result shows that the majority of the respondents with 58.2 per cent only spent less than RM 100 as a monthly purchase at East Coast Mall (ECM). Besides, the same percentage of 2.7 per cent of respondents spent RM 301 to RM 400 and RM 400 and above respectively as a monthly expenditure at East Coast Mall (ECM). Another 27.7 per cent of respondents spent RM 101 to RM 200 as their monthly expenditure at East Coast Mall (ECM). TABLE 2: SHOPPING HABITS OF RESPONDENTS Frequency

Percentage

(a) Average time spent 30 minutes to 1 hour 1.1 hours to 2 hours 2.1 hours to 3 hours 3.1 hours to 4 hours 4 hours and above Total

63 120 88 53 40 364

17.3 33.0 24.2 14.6 11.0 100.0

(b) Number of different stores visited 1 to 3 stores 4 to 6 stores 7 to 9 stores 10 or more stores Unidentified Total

66 141 64 56 37 364

18.1 38.7 17.6 15.4 10.2 100.0

(c) Frequency of visiting Everyday Once in a week Once in two weeks Once in a month Total

4 87 105 168 364

1.1 23.9 28.8 46.2 100.0

(d) Monthly expenditure spent in ECM Below RM 100 RM 101 to RM 200 RM 201 to RM 300 RM 301 to RM 400 RM 400 and above Total

212 101 31 10 10 364

58.2 27.7 8.5 2.7 2.7 100.0

How mall awareness and mall image dimensions influenced Gen Y to re-patronage the shopping mall based on demographic factors? 129

The second objective of this study was to look through the contribution factors of mall patronage with demographic characteristics among Gen.Y. Much research that has been published on malls looks at the effects of individual aspects of the environment, such as tenant mix (e.g., Berman & Evans, 1995), anchor store influence (Finn & Louviere, 1996) and characteristics of consumers such as basic demographics and motivations (Roy, 1994) and profiles of browsers (Jarboe & McDaniel, 1987). Furthermore, Wakefield and Baker (1998) found that tenant variety, the physical environment of the mall and consumers‘ involvement with shopping influenced shoppers‘ excitement, which in turn drove their desire to stay at the mall, their mall re-patronage intentions and their out-shopping (going outside the community) behaviors. The results from previous studies are taken into consideration to study the contribution factors of mall patronage with demographic characteristics among Gen Y. from these results it may help the mall operators look into the niche of the market segmentation and provides the right strategy to cater this segment. An independent-samples t-test was conducted to compare the mall overall environment, product and service quality, mall awareness, mall entertainment, mall convenience and service quality scores for gender. The results are shown in table 3 and indicated that there were significant differences on scores for gender with mall awareness p= 0.011 (two-tailed), mall convenience p= 0.000 (twotailed), and service quality p= 0.000 (two-tailed). However, the magnitude of the differences in the eta squared is very small for the factors of mall awareness, mall convenience, and service quality. In conclusion, gender is influenced by mall awareness, mall convenience, and service quality in repatronage one shopping mall but represents a small effect in differences for gender. Moreover, t-test also was conducted to compare the mall overall environment, product and service quality, mall awareness, mall entertainment, mall convenience and service quality scores for marital status. Table 4 shows that only overall environment and mall entertainment was significantly influenced by marital status. Mall entertainment contributed p= .008 (two-tailed), while overall environment provided p= .025 for marital status. In addition, the magnitude of the difference in the eta squared is very small for the factors of mall entertainment, and overall environment. To sum up the marital status influenced mall entertainment and overall environment in selecting one shopping mall but represented a small effect in differences for marital status.

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TABLE 3: TEST BASED ON DEMOGRAPHIC FACTORS (GENDER AND MARITAL STATUS) Demographic Factors

Marital Status Sig. (2-tailed)

Eta Squared for Marital Status

.101

.025

0.007 (small effect)

Product and Service Quality Mall Awareness

.070 .011

.458 .534

Mall Entertainment

.514

Mall Convenience

.000

Service Quality

.000

Mall Awareness And Mall Images Overall Environment

Gender Sig. (2-tailed)

Eta Squared for Gender

0.02 (small effect)

.008 0.04 (small effect) 0.04 (small effect)

0.001 (small effect)

.186 .218

Analytical ANOVA‘s test was conducted to explore the impact of ethnicity, age, job status, education level, and monthly income on factors influenced in re-patronage of one shopping mall i.e. mall overall environment, product and service quality, mall awareness, mall entertainment, mall convenience and service quality. Table 3 shows that ethnicity did not affect Gen Y decision on repatronage of a shopping mall. Besides, age was found as significant with mall overall environment, mall awareness, mall entertainment, and mall convenience. However, age level was found as not being significant with product and service quality, and service quality. Moreover, job status was only significant with mall convenience and had no significant influences on overall mall environment, product and service quality, mall awareness, mall entertainment, and service quality. Furthermore, education level showed a significant influence with mall awareness, and mall entertainment on repatronage a shopping mall by Gen Y. factors like mall overall environment, product and service quality, mall convenience and service quality did not affect Gen Y on choosing a shopping mall. Monthly income had a significant effect with mall overall environment, product and service quality, mall awareness, mall entertainment, and mall convenience on re-patronage a shopping mall by Gen Y.

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TABLE 4: ANOVA BASED ON DEMOGRAPHIC FACTORS (ETHNICICITY, AGE, JOB STATUS, EDUCATION LEVEL, AND INCOME) Demographic Factors Mall Awareness And Mall Images Overall Environment Product and Service Quality Mall Awareness Mall Entertainment Mall Convenience Service Quality

Ethnicity (Sig.)

Age (Sig.)

Job (Sig.)

Education (Sig.)

Income (Sig.)

.234 .257 .259 .203 .441 .555

.055 .119 .003 .006 .003 .588

.357 .111 .557 .123 .043 .191

.712 .722 .003 .013 .070 .255

.001 .017 .042 .002 .006 .083

Mall Loyalty and Demographic Factors An independent-sample t-test was conducted to compare the mall loyalty scores for gender and marital status. The results shown in table 4 stated that there was a significant difference on scores for gender with mall loyalty p= 0.006 (two-tailed). However, the magnitude of the difference in the eta squared was very small for the factors of mall loyalty. Moreover, marital status had no significant influence on mall loyalty. From these results, mall operators may need to focus more on gender rather than marital status in forming mall loyalty among Gen Y.

TABLE 5: T-TEST BASED ON DEMOGRAPHIC FACTORS (GENDER AND MARITAL STATUS

Mall Loyalty

Gender Sig. (2-tailed) .006

Eta Squared for Gender 0.02 (small effect)

Marital Status Sig. (2-tailed) .731

Eta Squared for Marital Status

Table 6 explained that mall loyalty was significant with monthly income of Gen Y. The results shown in table below indicated that there was a significant different on scores for income with mall loyalty p= 0.029 (two-tailed). However, the other demographic factors i.e. ethnicity, age, job status, and education level did not influence mall loyalty among Gen Y.

TABLE 6: ANOVA BASED ON DEMOGRAPHIC FACTORS (ETHNICITY, AGE, JOB, EDUCATION LEVEL, AND INCOME) 132

Demographic Factors

Mall Loyalty

Ethnicity (Sig.)

Age (Sig.)

Job (Sig.)

Education (Sig.)

.419

.178

1.62

.106

Income (Sig.) .029

LIMITATIONS AND FUTURE RESEARCH Based on the literature, we can conclude that Gen Y in this study was a group which was more attracted to the malls because of several factors that are ambience, superior facilities and variety of stores. Khare, (2010) discussed in his findings that the younger generation especially Gen Y visited shopping malls for entertainment recreational, social and exploration factors. The research study was limited to Gen Y who visited ECM, Kuantan. For future research, the researchers attempt to study other groups of visitors such as Generation X and Baby Boomers in terms of their shopping behavior at the mall. Furthermore, the marketing practitioners and researchers also would take into consideration their rationale for spending their incomes in malls.

CONCLUSION AND IMPLICATION The management of East Coast Mall (ECM) and other shopping malls could manage a strategic plan in their business which includes the marketing mixes to suit with specific target respondents (Gen Y). Hence, knowing their shopping habits would help the management of shopping malls particularly East Coast Mall (ECM) to develop appropriate programs that might attract Gen Y to become loyal towards their shopping mall. Notifying all the shopping habits and factors contributing to repatronage of targeted respondents also could help the shopping mall in selecting the right marketing strategy as a part of the key success factors and become a leader among the competing malls.

REFERENCES

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Ahmed, Z.U., Ghingold, M., and Zainuri,D. (2007), Malaysian shopping mall behavior: an exploratory study, Asia Pacific Journal of Marketing and Logistics,, 19(4), pp. 341-348. Amine, A. (1998), Consumers‘ true brand loyalty: the central role of commitment, Journal of Strategic Marketing,, 6, 305-319. Bellenger, D., Robertson, D. and Greenberg, B. (1977), Shopping centre patronage movies, Journal of Retailing, Vol. 53 No. 2, Summer, pp. 29-38. Benson, P.G., Saraph, J.V. and Schroeder, R.G. (1991), The effects of organizational context on quality management: an empirical investigation, Management Science,, September, pp. 1107-24. Berman, B., & Evans, J. R. (1995). Retail Management, (6th edition), New York: Macmillan Publishing Company. Bloch,P.H,Ridgway ,N.M and Dawson,S.A (1994),The consumer malls as shopping habitat, Journal of Retailing, 72(4), pp.223-247 Carbone, L. P. (1999). Leveraging customer experience in the twenty-first century. In Arthur Anderson retailing issues letter, (Vol. 11, No. 3). Texas: A&M University Center for Retailing Studies. Chaudhuri, A. and Holbrook, M. B. (2001),The Chain of Effects from Brand Trust and Brand Effect to Brand Performance: The Role of Brand Loyalty, Journal of Marketing, 65, 81-93. Chebat, J.C., El Hedhli, K., Sirgy M. J. (2009). How does shopper-based mall equity generate mall loyalty? A conceptual model and empirical evidence, Journal of Retailing and Consumer Services, Vol. 16, pp. 50-60. Finn, A. and Louviere, J. (1996), Shopping center image, consideration, and choice: anchor store contribution, Journal of Business Research, Vol. 35, pp. 241-51. Flynn, B.B., Schroeder, R.G. and Sakakibara, S. (1994), A framework for quality management research and an associated measurement instrument, Journal of Operations Management, Vol. 11 No. 4, pp. 339-66. Foot and Stoffman, (2000), Entre le Boom et L‘Écho. Éditions du Boréal: Collection Info Presse. Frasquet, M. Gil, I. and Molla, A. (2001),Shopping centre selection modeling: a segmentation approach, International Review of Retail, Distribution, and Consumer Research, Vol. 11 No. 1, pp. 23-38 Garvin, D.A. (1984), What does ‗Product Quality‘ really mean? Sloan Management Review, Vol. 26 No. 1, pp. 25-43. Garvin, D.A. (1987), Managing Quality: The Strategic and Competitive Edge, New York, The Free Press.

134

Hawkins D. I & Mothersbaugh D. L. (2010), Consumer Behavior: Building Marketing Strategy, , 11th edition, New York, McGraw-Hill Companies, Inc. Haynes J. & Talpade S. (1996). Does entertainment draw shoppers? The effects of entertainment centres on shopping behavior in malls, Journal of Shopping Centre Research, 3(2): 29-48. Keller, K. L. (2003). Strategic Brand Management: Building, Measuring and Managing Brand Equity, New Jersey, Prentice Hall. Keller, K. L. (2008). Strategic Brand Management : Building , Measuring and Managing Brand Equity, New Jersey, Prentice Hall. Kotler P. and Armstrong G. (2000), Principles of Marketing, Ninth Ed., New Jersey, Prentice Hall International Inc. Kotler P. and Armstrong G. (2006), Principles of Marketing, Eleventh Ed., New Jersey, Prentice Hall, International Inc. Martin Craig A, Turley LW.(2004), Malls and consumption motivation: an exploratory examination of older Generation Y consumers. International Journal of Retail Distribution Management, 2004; 32(10):464–75. Miller D. A Theory of Shopping (1998), Ithaca, NY: Cornell University Press, 1998. Miller D, Jackson P, Thrift N, Holbrook B, Rowlands (1998),M. Shopping Place and Identity, London and New York: Routledge.. Morton Linda P, (2002), Targeting Generation Y. Public Relations, Q : 47(2):46–8. Neuborne Ellen, Kerwin Kathleen (1999).GenerationY. Business Week, :81–8 (February 15). Nevin, J. and Houston, M. (1980), Image as a component of attraction to intra-urban shopping areas, Journal of Retailing, Vol. 56 No. 1, Spring, pp. 77-93. Parasuraman, A., Zeithaml, V.A. and Berry, L.L. (1985), ―A conceptual model of service quality and its implications for future research‖. Journal of Marketing, Vol. 49, No. 4, pp. 41-50. Phillips, L.W., Sternthal, B., (1977). Age differences in information processing: a perspective on the aged consumer. Journal of Marketing Research, 14 (4), 444–457. Quart, Alissa, (2003). Branded: the Buying and Selling of Teenagers. Cambridge, MA., Perseus Publishing. Ramli,N. (2010), Consumer Decision Making Styles in Shopping Behavior among Students : A study Between Gender, Master‘s Degree, College of Business, Universiti Utara Malaysia. Roy, A. (1994), Correlates of mall visit frequency, Journal of Retailing, Vol. 70 No. 2, pp. 139-61. Schiffman L.G. & Kanuk L.L. (2010), Consumer Behavior,10th Edition, Upper Saddle River, New Jersey, Pearson Education, Inc. 135

Solomon M. R. (2011), Consumer Behavior:Buying, Having, and Being, 9th Edition, Upper Saddle River, New Jersey, Pearson Education, Inc. Stoel,L et.al (2011), Mall attributes and shopping value: Differences by gender and generational cohort‖, Journal of Retailing and Consumer Services, Vol. 18, No. 1, pp. 1-9. Taylor, S. and Cosenza, R. (2002), Profiling later aged female teens: mall shopping behavior and clothing choice, Journal of Consumer Marketing, Vol. 19 No. 5, pp. 393-408. Tauber, E.M. (1972), Why do people shop? Journal of Marketing Management, Fall, pp. 58-70. Wakefield K.L and Baker,J (1998), Excitement at the mall: determinants and effects on shopping response, Journal of Retailing,, 74 (4), pp. 515–539. Wolburg Joyce M, Pokrywczynski James (2001). A psychographic analysis of Generation Y college students. Journal of Advertising Research, 41(5):33–53. Wong, K.M., Lu, Y. and Yuan, L.L. (2001), SCATTR: an instrument for measuring shopping centre attractiveness, International Journal of Retail & Distribution Management,Vol. 29, No. 2, pp. 76-86. Yusniza,K and Lee C.H,(2010), Attracting Shoppers to shopping Malls : The Malaysian Perspective, Interdisciplinary, Journal of Contemporary Research in Business, Vol.2, No.3. Zeithaml, V. (1988). Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence. Journal of Marketing, Vol. 52, No. 3. pp. 2-22 Zollo, Peter (2004), Getting Wiser to Teens: More Insights into Marketing to Teenagers, Ithaca, New York, New Strategist Publications.

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CARBON FOOTPRINT CALCULATOR: EXPLORING CARBON EMISSION MEASUREMENT TOOL OF MALAYSION TELECOMMUNICATIONS INDUSTRY Shahrul Nizam Salahudin [email protected] College of Business Management and Accounting, Universiti Tenaga Nasional, 26700 Bandar Muadzam Shah, Pahang, Malaysia Suhaimi Sudin Christine Cheah Zuliawati Mohamed Saad Nazia Newaz UNITEN

ABSTRACT

Increase in carbon emissions will cause serious environmental problems and limit sustainable economic development. There is a need to look into methods of measuring carbon emission that will help in policy and guidelines development. This study proposes a researchable framework of measuring carbon emission in Malaysian Telecommunication industry. Based on literature reviews, this study identified processes within the supply chain of companies that contribute to carbon emissions released. Consequently, a Malaysian Carbon footprint calculator is developed. A careful process of selection criteria for the most appropriate carbon calculator will be determined. Later, data collected from the industry will be used to test and validate this calculator. Keywords: Carbon emissions, carbon footprint calculator, supply chain processes

INTRODUCTION Industry plays an important role in the issues of environmental management since they are part of our society which cannot be isolated from the environment, and in fact, they contribute most of the carbon footprints in the past (Liu, 2010). Malaysian Telecommunication industry are rapidly growing especially on mobile (Rahman, 2011), whereby Malaysia communications and Multimedia Commissions (MCMC, 2011) stated that, number of mobile subscriber stood at 31.671 Millions are increasing by 2.1% and 11.7% of improvements. Consequently Ericsson (2010) claimed that, Telecommunication industries are energy lean where Guerin (2008) undermine that information and communication technology (ICT) consumes large energy which leads towards carbon emissions. Carbon emissions can also adversely affect our climate, and threaten both the natural environment and the survival of the human race and its surrounding ecosystem. The changes in carbon dioxide concentration may effect on atmospheric temperatures (Hennessey, 2000). Besides that, Carbon dioxide is also responsible to the

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enhanced greenhouse effect Kumar (2003) due to this concern, Psomopoulos et.al 2009, stated that analyzing the factor that leads towards carbon emissions is vital whereby, this study identify and measures the carbon footprint. Initiative (GHG Protocol, 2010a), calculator make use three types of scope of carbon emission, which consist of scope 1 emissions (arise from activities for which the company is directly responsible) and scope 2 emissions (emissions are those associated with the purchase of electricity, heat and steam) and scope 3 emissions emitted by other businesses, such as third-party logistics, working on its behalf). Scope 1 emissions and scope 2 emissions are easy to calculate but scope 3 supply chain carbon emissions or known as indirect emissions, is hardly to quantify especially in the supply chain in the industry. (Daviet, 2006). Supply chain emissions are particularly challenging to quantify due to different parties that oversee various aspect of supply chain where having lack of information service that it procures nor does it have the resources in order to investigate the supply chain of each services Thurston (2011).Besides that an indirect emission does not include a significant, and perhaps dominant, source of GHG emissions. Huang et al., (2009). According to McKinnon, (2010) and (McKinnon, 2009) starting the start and end point for carbon measurement within the supply chain can be controversial. This study proposed to identify, which supply chain activities in Malaysian telecommunication industry contributes more on carbon emissions. The issues with, carbon calculators are accompanied by producing vastly inconsistent output even the input given is similar (Padgett et al. 2008). There are also concerns about the transparency and often contradictory of these existing Carbon calculators as well as static and fail to take into account the dynamic behavior of human nature (Farzana et al. 2011). According to Kenney and Gray, 2008) existing calculator models have no standards in relation from where the carbon emissions are sourced from or for what activities the carbon calculator model should cover resulting anomalies, or code of practice associates with these models leading to potentially significant differences and inconsistencies between them. Thus, these studies proposed to compare various types of existing carbon calculator especially on the indicator, and are forecasted to be developing Malaysian carbon footprint calculator.

LITERATURE REVIEW MALAYSIAN TELECOMMUNICATION According to Malaysia communications and Multimedia Commissions (MCMC) for the year of 2011 stated that there were 31.671 Million of mobile subscribers in Malaysia at the end of June 2010. It shows that there is a rise of 2.1% and 11.7% of improvement. Besides that mobile penetration increase from 103.8% in June 2009 to 11.01% in the year of 2010. According to Rahman 2011 and Malaysian Telecommunication report (2011), besides, Malaysian Telecommunication have four main operators which is Maxis with 12.971Million (2011) number of subscriber, Celcom with 10.596 Million (2011) number of subscriber and Digi with 8.104Million (2011) number of subscriber and U mobile, as well as four WiMAX operator including P1, Asia space, REDtone and YTL communication. Moreover, MCMC (2011) reported that no of internet use in the year of 2011 is 16.9, increase at 17.2 on (2012) and forecasted to increase at 17.3 at the year of (2013). MCMC in the report of Malaysian Telecommunications report Q1 2011 stated that 3G subscriber in Malaysia were 7.860mm at June (2010). There is a quarterly increase at 5.4% and as for annual increase 30.1% from the user bases of 7.459mm. in addition MCMC award 4G in 2.6GHz band to nine types of operators which consists of Celcom Axiata, Maxis Broadband, Digi Telecommunication, U-Mobile, Aisaspace, Packet one networks(p1), redtone Marketing, YTL Communications and puncak Semangat promotes advanced mobile services in Malaysia. Furthermore in the report of MCMC (2011), the 1.075 Billion messages sent where, the total number of SMS sent rose to 6.37 Billion, while MMS stood at 9.54 Million. The positive growth support a wide customer base, and high usage of cellular, broadband and 3G services. This was driven by the competitive pricing, innovative bundling of products and services as well as rapid demands for smart phones.

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Rahman (2011) stated that Malaysian Telecommunication industry has been a fast growing sector keeping suitable pace with global advancements, especially on the mobile Telecom market. According to Guerin (2008) claim that ICT industry is consume large energy and a significant of carbon emission source that can enable carbon emission reduction across its own and other sectors of the economy. Currently ICT contributes 2% of global carbon emission and that will increase 3% in future by 2020. According to Ericsson (2010) compared to other sectors such as, travel and transport, building and energy production, the Telecommunication industry is relatively energy lean where 2% of global energy use able to leads towards carbon emission. Mercury security,(2012) stated that International Data Corporation's estimated the (ICT) industry in Malaysia is expected to rapidly grow at 10.1% for the year of 2012, estimated on IT spending reach up till US$8.2 billion at the end of 2012. Population reference bureau (2010) Malaysian population is 28.318 Million whereas the number of population increases in the year of 2011 which stood at 28.9 Million. There are also some researches that support that an increase in the population will leads towards high carbon emissions release (Bongaarts 1992; Dietz & Rosa 1994; Engelman 1994; O'Neill, MacKellar & Lutz 2001; Shi 2003). Malaysian Communications and multimedia Malaysia (MCMC) have claimed in the report of brief Industry trends (2009), that Telecommunication is moving to greener pasture, and shows its concern towards the business impact on the global warming that relate to environmental issues. Increasing on energy consumption, associates with the carbon footprint that leads the telecommunications sector as the largest contributor to global warming. The main objective for going green, in the Green agenda, is to promote environmental sustainability and reducing carbon emissions. Furthermore, Telecommunication Green agenda can be seen in two angles, the first is environmental benefit and secondly is deriving economic cost benefit in the long term.

CLIMATE CHANGE The backbone of climate change are said to be the emission of greenhouse gases (GHG) connected to human activities (Chua and Oh,2010). According to Chua and Oh (2010), stated that uncontrolled, the carbon emission can worsen global warming which lead environmental devastation and health hazards that already hard to control nowadays.The clear effects of emissions are severe and wide ranging, that cause ecosystem disruption, pollution, and irreversible damage to natural resources. It become apparent that climate change is not uniformly same over the globe, thus different countries have different climate change effect in different ways (Lee et.al 2011). According to Pittock (2005), Climate change rate accelerate the contribution towards increased emissions. The most common effect that is being concern is rapid warming of the global climate that has temperature effect on the condition of the earth surface. Thus an alter of the ecosystems operation triggers natural processes such as the additional release of gasses which is carbon dioxide. Climate change will effect and increase the frequency and intensity of extreme weather events that is threatening and may impact communities around the globe (Kalkstein and Smoyer, 1993; Vo¨ro¨smarty et al. 2000; Berkes and Jolly, 2001; McMichael et al. 2006). An increase of greenhouse gas (GHG) emissions in the atmosphere is currently most serious environmental threat, where it may limits economic growth. In addition, icebergs and glaciers are melting at record speeds (Gruber 2010).

International accord

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Malaysia's international accord involvements towards reduction of carbon emissions are Montreal Protocol 1987 and Kyoto Protocol in 1997 Chua & Oh (2010) and Climate Summit in Copenhagen Denmark, 2009 (Gruber 2009). Copenhagen Malaysia In Climate Summit in Copenhagen, Denmark with all participating countries are committed in order to fulfill the protocol's obligations before the commitment period due in 2012 (Chua & Oh 2010). According to COP15, (2009), the Copenhagen Conference took place when political leaders from 200 different countries around the world meet together in order to discuss the challenge of climate change.In December 2009 Prime Minister Datuk Seri Najib Tun Razak ,Malaysia government had announced a voluntary 40% reduction in CO² intensity in relation to Gross Domestic Product (GDP) until 2020 compared with 2005 at COP15 (the 15th Conference of the Parties under the United Nations Framework Convention on Climate Change. Kyoto Protocol More than 160 nations met in Kyoto Japan at December 1997, to negotiate biding limitations on the greenhouse gasses for the develop nations in pursue realizing the framework Convention on climate change of 1992 (UNFCC,1992). The protocol was set in motion with Russia‘s ratification on February 16, 2005. This protocol was developed under the United Nation Framework Convention on Climate Change (UNFCCC) (Bodansky, 1993). Kyoto protocol is been established to mitigate carbon emissions for all developed countries which is (Annex I countries) that have ratified the protocol and are legally bound to reduce the GHG emissions below the level specified for each of them in the protocol whereby these target should met within five years between 20082012. Besides that developing countries that have ratified with the Kyoto protocol are known as Non Annex 1 countries whereby, these countries are not involved in any numerical limitation of GHG emissions (Ong, 2008). According International Energy (2010), the culprits of this carbon emissions issues is not actually the developed countries but developing. Malaysia which is a non-Annex I party to the UNFCC became a signatory to Kyoto Protocol on 12 March 1999 and on 4 September 2002.Kyoto Protocol has been ratified. On 16 February 2005 Kyoto Protocol enter into force. Malaysia engage in CDM projects with any Annex I Party countries in order to reduce the GHG emissions while gaining carbon credits from certified emission reductions. According to (Lee et al. 2009) Malaysia bears no obligation to reduce GHG emissions.

MONTREAL PROTOCOL Montreal protocol concern on the reducing ozone depletion that caused by anthropogenic emissions, such as chlorofluorocarbons with success (UNEP, 2002). However carbon dioxide is a major contribution towards the anthropogenic greenhouse gases (GHG) (Velásquez,2009).Malaysia ratified Vienna Convention and Montreal Protocol on 29 August 1989 to reduce greenhouse gas (GHG) emission (Loo , 2005).Minister of Natural Resources and Environment, Dato‘ Seri Azmi Khalid present that Malaysia some large sources of greenhouse gas emissions are cover by Montreal Protocol to control six greenhouse gases of atmospheric emissions which is carbon dioxide, methane, nitrous oxide, hydro fluorocarbons, per fluorocarbons and sulfur hexafluoride.

TRACKING CARBON FOOTPRINT

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Tracking carbon footprint and carbon measurement, pressure companies to report on the carbon emission along the supply chain (Lash and Wellington, 2007), and a majority of companies have been reluctant to disclose carbon reduction targets and make relevant measures available (Wehrmeyer et al., 2008).Reporting on emissions, provide information on the sources and causes of emissions as well as, provide recommendation on how to mitigate the emissions Kim and Neff (2009). King (1995), stated that, businesses who have limited access to environmental information are likely to make environmental mistakes. The information of carbon emissions which is confined to specialists units will fail throughout the supply chain Lee et.al (2009). SUPPLY CHAIN ACTIVITIES Supply chain of CO2 emissions is for emissions reductions, achieved through requiring industries from upstream to downstream that indicate both direct and indirect CO2 emissions that are associated with supply chain (Minx et al. 2009; Wiedmann, 2009). A corporate effort to mitigate carbon dioxide emissions over the supply chain is vital to achieve significant carbon dioxide emissions reduction (Lee et.al 2011).The common activity in supply chain measurement is to replace inputs with a high potential for emissions by those with lower emissions in order to identify the carbon footprint ( Lee et.al2011). Thus, understanding of the carbon emissions across the supply chains enable the companies to determine major prioritize areas where mitigation is needed. Total CO2 emission of supply chain can be calculated by adding each scope of the carbon measurement framework (Lee et.al 2011). Thus identification of supply chain will leads towards the changes in CO2 emissions and provide information on the critical paths a can be reduced (Oshita, 2011).

SUSTAINABILITY

Business are required to concern on the sustainable business operations including research efforts in the green supply chain management and carbon footprint of supply chains (Lee et.al 2011). According to (Williams and Millington, 2004, p. 100) earth needs to be revised in order to consume less. Dauncey‘s (2009) undermine that sustainability is a condition of existence which enables generations of humans and other species to enjoy social wellbeing, a vibrant economy and a healthy environment, and to experience fulfillment, beauty, and joy without compromising the ability of future generations of humans and other species to enjoy the same. Fascinatingly, many companies believe that across the supply chain sustainability can be achieved (Mahler, 2007). According to Mahler (2007), companies that achieve sustainable businesses practices may able to build the brand name of the companies as well as differentiate their product. Besides that, Barry and Calver, 2009 claim that in the world no businesses can claim to have come remotely close to sustainability. Thus suggested it is necessary to develop sustainability that incorporates with the environmental including flexibility to accommodate change over time (Jones et.al 2009). MALAYSIAN CARBON EMISSIONS

According to World Bank (2010) Malaysian population stood at 28,401,000 Million. Data from World Bank Carbon emission (kt) levels in Malaysia is highly increasing. As in 2007 the carbon emission stood at 194,919 whereas 208,267 in the year of 2008.Thus, there is an increase of 13348 occurs. On the other hand, Carbon Emissions (metric tons per capita in Malaysia stood at 7.2 at 2007 rather than 7.6 at 2008. There is an increase of 0.4 in the level of carbon emissions in Malaysia.

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This worrying level of emissions in Malaysia commissioned the Malaysian government to take part on reducing the emissions releases. There is a sign that Malaysia is actively fighting climate change, ( Gruber 2010). In Malaysia tenth plan (2011–2015), government has an effort to reduce emission by climate adaptation and mitigation measures. Moreover, major efforts on high income economy will lead to the fall of emission intensity in the year of 2020, if the governments pursue decoupling policy on economic growth and GHG emission.

CARBON CALCULATOR

The model of calculation is vital to educate the management and public to reduce CO 2 emissions. According to Padgett et al. (2008), there are three types of instruments that are being use to develop a carbon calculator which is through stakeholder meeting, user interview and conducting non user group discussions. Carbon calculators are not coupled with mitigation measures may able to provide information on carbon emissions contributions that may lead to behavior and policy changes. Numbers of online carbon calculators are growing rapidly (Padgett et al. 2008), where their methods are proliferating where it may create an awareness on the carbon emissions and ways to reduce it and affect the magnitude and type of the emissions reduction efforts as well as offset purchases. The calculator is being design to measure the entire impact from the activities involve by the specialists and industrial level. However the required technical expertise such as, supply chain are being omit (Kim, and Neff,2009). The similarity between the carbon calculators is the function itself where, it may provide knowledge and act as effective communication in order for behavior change. Besides, carbon calculator also works the same when, the characteristic of input is entered and this will reveal an amount of carbon dioxide whereby, the output is emitted as a direct result in the form of carbon footprint ( Padgett et al. 2007). According to Padgett et al. (2007) carbon calculators share the same basic mode of user interaction, where in the entire carbon calculator system users are required to answer a series of related questions on carbon emissions that will results carbon being emitted in the end. Based on the entire answer given by the user, offsets and suggestion are provided in order to reduce carbon emission. Green mountain, Terra pass calculator Padgett et al. 2007 and carbon footprint (Kenny and Gray, 2008) calculator measure on the similar range which is individual and business footprint. Although, these calculators measure the similar range, but then the carbon calculator indicator being used is different. As for the green mountain carbon calculator the indicator being used for the individual and business is the same which is vehicle, electricity, travel and heating. Terra pass calculator measure the individual footprint, through using the indicator of driving, air travel and home including weeding footprint calculator where, the indicator is air travel, car travel and hotel. On the other hand, as for the business range the indicator being used is business carbon footprint with the indicator of site, server, fleet, travel and commute as well as event and conference footprint indicator is air travel, car travel and hotel. In addition, the individual indicator for carbon calculator is house ,flight, car, motorbike ,bus & rail, other fuel and secondary whereas to measure business footprint of carbon the indicator being used is buildings, flights, car and van, vehicle fuel and bus and rail. Moreover, these calculators also have the same features of offsets and providing suggestion in order to reduce carbon emission. Furthermore, the similarity between the nature conservancy calculator and cool climate carbon footprint calculator is where both of these calculators provide offsets in order to balance the carbon emissions. Besides, another similarity is where, only one side of range, which measure household. There are differences between these calculators indicator, where nature conservancy calculator indicator for household measurement is home energy, driving & flying, food and diet and recycling & waste whereas cool climate carbon footprint

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calculator indicator for household is transportation, housing and shopping. Another different side of range that these nature conservancy calculator that measure individual on the other hand the cool climate carbon footprint calculator measure business footprint. The indicator for individual is home energy, driving & flying, food & diet and recycling and waste, whereas, the indicator for business measurement is transportation, facilities and procurement. In spite of that, another calculator which is known as American Forest Calculator, have different range to be measure which is forest compare to other calculators that mainly focus to measure the range of individual, business and household. It also encompasses different types of indicator which is home, car, plane, food and waste. American Forest Calculator similarity across all types of calculator is where it provides offsets. From a special report on Telecom Regulatory Authority of India, (2011), recommend on green telecommunication undermine the supply chain of Telecommunication. Thus the telecommunication carbon indicator consists of Landline Network with component of Exchanges Local, Tandem, TAX, Copper distribution Network and Telephones. Next, mobile network, that consist of main Switching Centers (includes all centralized control sub systems including GGSN ,SGSN,etc ), base Station Controller Centers, base Transceiver Station and mobile phones. Fixed Broadband that consist element of digital Subscriber Line Access Multipliers, customer premise Equipments and Splitters as well as Fibre to the X consisting component of Optical Network Control Unit Equipment, Optical Network Terminating Equipment and Passive / Active Splitters. Furthermore the indicator also consists of Carbon footprint of core networks, Carbon footprint of aggregator‘s networks, Carbon footprint of Transmission network and Carbon footprint of Infrastructure provider‘s network. Based on the Telecom Regulatory Authority of India, (2011) report the formula to calculate carbon footprint through the carbon indicators are, identified in telecommunication industry. Thus, this study proposed to measure carbon footprint in Malaysian Telecommunication industry, by using the entire indicators as a foundation, in order to adapt with Malaysian Telecommunication.

Y CT = a [b1 CL+ b2 CM + b3 CFB+ b4 CFT+ b5CC+ b6 CA+ b7 CTX+ b8 CIP] +e Total Carbon footprint (CT) = Carbon footprint of Landline networks ( CL ) + Carbon footprint of Mobile networks ( CM )+ Carbon footprint of Fixed Broadband networks ( CFB)+ Carbon footprint of FTTx networks ( CFT) + Carbon footprint of core networks ( CC) + Carbon footprint of Aggregators networks (CA) + Carbon footprint of Transmission networks( CTX) + Carbon footprint of Infrastructure providers network (CIP) expressed in Tonnes

FIGURE 1:+MODEL CARBON INDICATORS OF MALAYSIAN TELECOMMUNICATION

Infrastructure Core Networks

Provider’s Aggregator’s

Network (CIP)

(CC)

Networks (CA) Transmission Network (CTX) Landline

Network

(CL) 

Exchanges Local

143 INDICATOR OF TELECOMMUNICATION INDUSTRY

Fixed Broadband (CFB) 

Digital Subscriber Line Access Multipliers

Mobile Network (CM)  Switching Centers (includes all centralized control sub systems including GGSN, SGSN 

Base Station Controller Centers



Base Transceiver Station



Mobile phones



Customer premise Equipments



Splitters

Fibre to the X (CFT) 

Component of Optical Network Control Unit Equipment



Optical Network Terminating Equipment



Passive / Active Splitters

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REFERENCES Barry, M.and Calver, L, (2009). Marks & Spencer describes its journey from corporate social responsibility to sustainability, Marketing Magazine, 27 October, available at:www.marketingmagazine.co.uk/news/948198/Marks–-Spencer-describes-its-journey-corporatesocial-responsibility-sustainability/ (Retrieved 12 December 2009).

Berkes, F.and, Jolly, D, (2001). Adapting to climate change: social-ecological resilience in a Canadian western Arctic community, Conservation Ecology, Vol. 5 No.2, pp.18.

Bodansky, D, (1993).The United Nations Framework Convention on Climate Change: A Commentary,‘ Yale Journal of International Law,18, 451-467.

Bongaarts, J, (1992).Population Growth and Global Warming. Population and Development Review, 299-319.

Chatterton, T.J (2008).Understanding how transport choices are affected by the environment and health: Views expressed in a study on the use of carbon calculators; Public Health Volume 123, Issue 1, January 2009, Pp. e45–e49.

Chin,B.H( 2012),low carbon urban development strategy in Malaysia – the case of Iskandar Malaysia Development corridor; habitat international xxx 1-4 . Doi .10.10.16/j.habitat 2011.12.018 (Retrieved 27 April 2012)

Chua,S.C, Oh,T.H (2010). Review on Malaysia's national energy developments: Key policies, agencies, programmes and international involvements. Renewable and Sustainable Energy Reviews Volume 14, Issue 9, December 2010, Pages 2916–2925.

Comfort,J.C &.Hillier,D. D, (2009).Marketing Sustainable Consumption within Stores: A Case Study of the UK‘s Leading Food Retailers. Sustainability 1,815-826, World Bank Malaysian http://www.worldbank.org/

COP15, (2009).United Nations Climate Change Conference, Copenhagen, Denmark, December 7-18.

Dauncey, G, (2009). Towards sustainability, available at: www.towardssustainability.co.uk/infodir/susquote.html (online) (Retrieved 27 April 2012)

145

Daviet,D (2006). Environmental supply chain management: using life cycle assessment to structure supply chains, International Food & Agribusiness Management Review, 4 , pp. 399–412

Dietz, T., & Rosa, E. A, (1994). Rethinking the Environmental Impacts of Population, Affluence, and Technology. Human Ecology Review, 277-300.

Engelman, R, (1994). Stabilizing the Atmosphere: Population Consumption, and Greenhouse Gases. Washington DC, Population Action International. Journal of Health Science 55(1) 125-127 (2009)

Ericsson,(2010).The Broadband Bridge linking ICT with climate action for a low carbon economy, A report by the broadband commissions, International Telecommunications Union.

Farzana,R, Sheikh, C.O.B, Ahamed, I Liu,H.Z (2011).Design and implementation of an open framework for ubiquitous carbon footprint calculator applications., Sustainable Computing: Informatics and Systems ,Volume 1, Issue 4, December , Pp. 257-274

GHG Protocol, (2010a). Calculation Tools, The Greenhouse Gas Protocol Initiative, Washington,DC, available at: www.ghgprotocol.org/ (online).(Retrieved on 3May 2012) Hennessey, K. (2000), Climate Change, CSIRO Melbourne.

Gruber,G (2011). Combating climate change. Retrieve from http://archives.thestar.com.my/search/?q=dr+guenter+gruber, (online). (Retrieved 15 February 2012)

Huang, Y.A, Lenzen, M., Weber, C.L, Murray, J, and Matthews, H.S, (2009). The role of Input output analysis for the screening of corporate carbon footprints. Economic Systems Research 21 (3), 217e242.

International Energy Agency, (2010) .Working together to ensure reliable, affordable and clean energy. Retrieve from http://www.iea.org/ (online) Wehrmeyer,J.H & Mulugetta, Y,(2008). How warm is the corporate response to climate change? Evidence from Pakistan and the UK", Business Strategy and the Environment, Vol. 18 pp.46-60.

146

Kalkstein, L.S. and Smoyer, K.E, (1993).The impact of climate change on human health: some International implications, Experiential, Vol. 49, p. 96

Kenny,T &,Gray.G2008).Comparative performance of six carbon footprint models for use in Ireland; Centre for the Environment, School of Natural Sciences, Trinity College, University of Dublin, Dublin 2, Ireland, Environmental Impact Assessment Review 29 (2009) 1-6.

Kim,B & Neff,R (2009).Measurement and communication of greenhouse gas emissions from U.S. food consumption via carbon calculators, Ecological Economics 69,186–196.

King, A, (1995).Avoiding ecological surprise: lessons from long standing communities. Academy of Management Review, Vol. 20 No.4, pp.961-85.

Kyoto Protocol; Energy Policy, Volume 37, Issue 11, November, Pp. 4771–477

Lash, J. and Wellington, F, (2007). Competitive advantage on a warming planet, Harvard Business Review, Vol. 85 No.3, pp.94-102.

Lee,C.L , Tan,K.T, Lee,K.T, Abdul,R.M, (2009). A comparative study on the energy policies in Japan and Malaysia in fulfilling their nations‘ obligations towards the

Lee,K.H &Cheong,I.M (2011). Measuring a carbon footprint and environmental practice: the case of Hyundai Motors Co. (HMC), Industrial Management & Data Systems, Vol. 111 Iss: 6, pp.961 – 978

Liu, W, (2010). The Environmental Responsibility of Multinational Corporation, Journal of American Academy of Business, Cambridge, 15(2), 81-88.

Loo,C.K , (2005). Interconnection of embedded generation: the Malaysian experience, 18th International Conference on Electricity Distribution.

Mahler, D, (2007). The sustainable supply chain, Supply Chain Management Review, November, pp. 59-60. European Business Review, Vol. 23 Iss: 4 pp. 392 – 400

147

Malaysian Communication and Multimedia Commission (2011). Retrieved from http://www.skmm.gov.my/index.php?c=public&v=main (online) (Retrieved on 2 February 2012)

McKinnon, A.C, (2009).The potential of economic incentives to reduce CO2 emissions from goods transport, paper prepared for the 1st International Transport Forum on Transport

McKinnon,A.C (2010). Product-level carbon auditing of supply chains Environmental imperative or wasteful distraction, International Journal of Physical Distribution & Logistics Management Vol. 40 No. 1/2, 2010 pp. 42-60 .

McMichael, A.J., Woodruff, R.E., Hales, S, (2006). Climate change and human health: present and future risks, Lancet, Vol. 367 pp.859-69.85 No.3, pp.94-102.

Mercury Securities, (2012). Report on CMDF-Bursa Research Scheme (CBRS)

Minx, J.C, Wiedmann, T, Wood, R., Peters, G.P, Lenzen, M, Owen, A, Scott, K., Barrett, J, Hubacek, K, Baiocchi, G, Paul, A, Dawkins, E, Briggs, J, Guan, D, Suh, S, Ackerman,F, (2009).Input–output analysis and carbon foot printing: an overview of applications. Economic. System. Research. 21 (3), 187–216.

Ong, B,(2008).Carbon credits and its potential in Malaysia, New Straits Times Press, Ltd. Mar 1,

O'Neill, B. C, MacKellar, F. L, & Lutz, W, (2001). Population and Climate Change. Cambridge: Cambridge University Press.

Padgett.P.J Anne C. Steinemann., James H. Clarkea., Michael P. Vandenbergha, (2008), A comparison of carbon calculators., Environmental Impact Assessment Review Volume 28, Issues 2–3, February– April 2008, Pages 106–115

Pittock.P.K2005). Competitive Advantage on a Warming Planet. Harvard Business Review, 85 (2007), pp. 94–102

Psomopoulos,C.S., Bourka,A, (2009). Waste--‐to--‐energy: A review of the status and benefits in USA."WasteManagement, 29 (5):1718‐1724.

148

Rahman,S (2011).Choice Criteria for Mobile Telecom Operator: Empirical Investigation among Malaysian Customers, International Management Review Vol. 7 No. 1,pp. 50-55

Kumar,S. R, (2003). An economic evaluation of policy options available to control industrial air pollutants, Environmental Education and Information, Vol. 14 No. 3, pp. 254-6

Shi, A, (2003).The Impact of Population Pressure on Global Carbon Dioxide Emissions, 1975-1996: Evidence from Pooled Cross-country Data. Ecological Economics, 24-42.

Thurston, (2011).Assessing greenhouse gas emissions from university purchases, International Journal of Sustainability in Higher Education Vol. 12 No. 3, 2011 pp. 225-235.

UNFCCC, (1992).United Nations Framework Convention on Climate Change, United Nations, Bonn, available at: www.unfccc.de (online).(Retrieved on 21 May 2012)

United Nations Environment Programme,(2002) .The Stockholm Convention on Persistent Organic Pollutants. (UNEP/POPS/CONF/2).

Velásquez.V, (2009). State-of-the-Art in E-Commerce Carbon Foot printing; JIBC December 2009, Vol. 14, No. 3

Vörösmarty, C.J., Green, P., Salisbury, J., and Lammers, R.B (2000). Global water resources: vulnerability from climate change and population growth, Science, Vol. 289 pp.284-288.

Williams,W.K and Millington,J.M (2004) The diverse and contested meanings of sustainable development; The Geographical Journal , Vol. 170 , No. 2, June 2004, pp. 99–104

World Population Data Sheet, (2010). Population Reference Bureau. Retrieve from http://www.prb.org/ (online). (Retrieved on 23 March 2012)

149

Oshita, Y(2011).Identifying critical supply chain paths that drive changes in CO2 emissions, Energy Economics ,Faculty of Economics, Kyushu University, 6-19-1 Hakozaki, Higashi-ku, Fukuoka, 8128581, Japan.

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RELATIONSHIP OF FRAUD TRIANGLE MODEL AND ACADEMIC DISHONESTY: SOME MALAYSIAN EVIDENCE

Mohd Rizuan Abdul Kadir Accounting Department, College of Business and Accounting, Universiti Tenaga Nasional, Sultan Haji Ahmad Shah Campus [email protected] Norlaila Mazura Hj. Mohaiyadin Accounting Department, College of Business and Accounting, Universiti Tenaga Nasional, Sultan Haji Ahmad Shah Campus [email protected] Mohamed Ariff Jame‘an Accounting Department, College of Business and Accounting, Universiti Tenaga Nasional, Sultan Haji Ahmad Shah Campus Muzrifah Mohamed Accounting Department, College of Business and Accounting, Universiti Tenaga Nasional, Sultan Haji Ahmad Shah Campus

151

Norsheilla Maulad Jamaluddin Accounting Department, College of Business and Accounting, Universiti Tenaga Nasional, Sultan Haji Ahmad Shah Campus

ABSTRACT Accounting misleading involving the collapse of large corporate firms has brought about a question of adequacy of ethics among accountants. Past researchers mentioned that the current attitudes of the students during their university life can be translated into behaviours they will have during their working life. As future practitioners in the field, their behaviours are of main concerns. This study intends to investigate the significant relationships of fraud triangles elements and academic dishonesty. The sample of respondents involved the final year accounting students from one of the private institutions situated in the east coast part of Malaysia. The Spearmans‟ Rho correlations are used to test the relationships. This study found that there were positive significant relationships between opportunities and rationalisations towards academic dishonesty. The study will provide additional literatures on explaining the student‟s moral behaviour with regards to the fraud triangle model.

INTRODUCTION

Accounting misleading involving the collapse of large corporate firms has brought about a question of adequacy of ethics among accountants. Burke, Polimeni and Slavin (2007) stated that the highprofile corporate accounting scandals at Enron, WorldCom, Adelphia Communications, and Tyco International as well as the largest American embezzlement of taxpayer funds of school district, in Roslyn, NewYork, encourage people to start giving obnoxious perspective towards the accounting profession. According to these failures, the Sarbanes-Oxley (SOX) was enacted on July 2002 particularly to enhance all public company boards in the United States management and public accounting firms (Rittenberg and Miller, 2005). The professions which have always been criticised as fraud involvers were accountants and auditors (Pizzolatto and Bevill, 1996). In particular, accounting students looking as future practitioners in the field, hence their behaviour are of main concerns (Alleyne, Devonish and Cadogan, 2006). Colleges and universities are investigated as the main contributing factor to failure of conduct of corporate executives and professional accountants‘ academic dishonesty in campus (Burke et al. 2007). Academic dishonesty is the beginning point to bigger potential fraud. Even the misgiving of

152

academic dishonesty has jeopardised potential careers (Florida Thech‘s Academy Advising Handbook, 2001). There is a demand for business schools to address academic dishonesty because what students have learned as acceptable behaviour in the classroom will impact their expectations of what are acceptable professionally. This paper adopts the business model fraud triangle introduced by Cressey (1973) that represents the academic dishonesty as dependent variable. The Fraud triangle model was developed by three dimensions; incentives or pressures, opportunities and attitudes or rationalisations and being adopted as an appropriate fraud model in the Statement on Auditing Standard (SAS) No.99: Consideration of Fraud in a Financial Statement Audit (Malgwi and Rakovski, 2009). This study intends to investigate the significant relationships of fraud triangles elements and academic dishonesty. The researchers‘ intention to conduct this study is parallel with the statement of Chapman and Lupton (2004) and Kidwell, Wozniak and Laurel (2003) to state that the issue of academic dishonesty is critical for business schools because it seems to mirror the growing concerns of ethical problems in the business and corporate communities. The contributions of the study include adding on to the literatures on relationships of fraud triangle model and academic dishonesty in Malaysia, guidance to the academicians to develop their syllabus and improve the quality of their students and benefit to the companies on how to manage and provide development training for their future employees.

This study is organised into five different sections in which the first section provides an overview of the issue, objectives as well as the significance of the study. The second section presents the review of previous related literatures, discussion on framework of the study and hypotheses development. Data collection and the information concerning the instrument and the statistical analysis are presented in the third section of this research. The results and data analysis are highlighted in the fourth section. The last section governs the final section of the research and provides the overall conclusion, recommendations and limitations of the research.

LITERATURE REVIEW Academic dishonesty consists of ―cheating‖ and ―plagiarism‖, generally referred as the theft of ideas and other sorts of intellectual property, whether they are published or not (Lars, Robert, Sharon, and Leslis, 2001). Pullen, Ortloff, Casey and Payne (2000) emphasised that ―cheating‖ is the bane of higher education and strikes at the heart of establish values. Park (2003) defined plagiarism as a ―literary theft, stealing the words or ideas or someone else and off as one‘s own by omitting to cite them.‖ McCabe, Trevino and Butterfield (1996) found 66% of the students at several prestigious colleges and universities were reported cheating, 70% have been cheating in tests and 84% were reported cheating on homework assignment. Bowers (1964) reported in his study that 66% of undergraduate business and accounting students from 99 campuses, 8% higher than engineering students, admitted to at least one incident of cheating. McCabe (1997) found that 84% of business students are reported involved in one or more incidents of serious cheating compared to other disciplines. This shows the 153

tendency on how the academic dishonesty will affect their behaviour in the workplace (Grimes, 2004). Previous researches have been conducted with the main objectives to discover the characteristics of students who engage in this academic misconduct problem; they are thought to tend some common characteristics (Becker et al. 2006). The business model fraud triangle introduced by Cressey (1973) seems to be the best model to be tested in determining student dishonesty. The fraud triangle model was developed by three dimensions; incentive, opportunity and rationalisation and being used as appropriate fraud model in SAS 99 (Malgwi and Rakovski, 2009). The first element of fraud occurred among students is incentive or pressure. Researchers found that there are two motives due to the pressure: non-financial and financial. Due to the non-financial motive, Merritt (2002) stated that in order to maintain their performance like the Cumulative Grade Point Average (CGPA), to pass in exam, to complete the assignment and test in order to obtain high mark assessment and pressure make up, it cut off the student to the extent that he or she begins to internalise it and does not want to share it with other students. Kock and Davison (2003) stated that others cheat because they want to be viewed as more successful, respectable, or influential to others. Due to the financial motive, Malgwi and Rakovski (2009) stated that the pressures may come from several risk factors such as student is in danger of failing the course and student may lose financial aid. The more pressure a person has, the greater the possibility that academic dishonesty will occur. All the pressures described may lead to non-ethical behaviour such as cheating in examination. The second element of fraud triangle is opportunities. The opportunities are referring to the capability and circumstances which allowed people to cheat. Buckhoff (2002) stated that the opportunity to commit fraud was probable when student have access to information that allows them to commit and conceal fraud. Opportunities occurred when the student is trusted by the lecturer as an excellent student he or she will tend to grab the opportunity to cheat on other students‘ work or assignment to maintain their popularity (Bonita, 2004). Bonita (2004) also stated that opportunity was created by weak internal controls, poor management oversight, and through the use of position or authority of facilitator and failure to establish adequate procedure to detect fraudulent activity which also increases the opportunities for the fraud to occur. Zimny, Robertson and Bartoszek (2008) stated that cheating is more common in less intimate relationships because the cheating does not involve face-to-face or existence of other person. Scanlon and Neumann (2002) stated that the use of technology has further enhanced the problem of academic dishonesty at both university and college levels. In this case, computers and internet seem like an easier way to obtain the information and used as one‘s own with or without mentioning the source. The third element is rationalisation or attitude which is the essential component in cheating or fraud. According to Kock and Davison (2003), the rationalisation becomes common and justifiable if there is a perception that ―everyone is doing it‖ and involving a person reconciling their behaviour (academic fraud) with the commonly accepted concept of civility and belief. Bonita (2004) stated that rationalisation is a crucial part in most frauds that represent the ability of students to view cheating as consistent with their personal code of ethics. Rationalisation involves a person reconciling his or her behaviour with the commonly accepted notions of decency and trust. Students may rationalise cheating if they believe that their actions are within the acceptable behaviour (Kock and Davidson, 2003). The students may rationalise their cheating behaviour saying that they have studied so hard for the course and deserved to pass but found rationalisation as the least factor that leads to cheating compared to pressure and opportunity 154

(Malgwi and Rakovski, 2009). Bonita (2004), in his research also concluded that rationalisation is one of the top three required elements for a fraud to occur where most students were readily able to rationalise questionable academic behaviour as being acceptable but different with Malgwi and Rakovski (2009). Figure 1 illustrates the research framework of this study. Three independent variables are located on the left side of the figure that represents all three elements of the fraud triangle. These three dimensions mainly refer to the factors that serve as a driver for students to cheat in their academic performance. The dependent variable is located on the right side of the figure that represents the academic dishonesty. The measurement of academic dishonesty employed by the researchers in this study focuses on how frequent students‘ cheat during quizzes. The details of measurements will be discussed in the next section. FIGURE 1: RESEARCH FRAMEWORK

Independent variables

Dependent variables

Incentives/Pressures Academic Dishonesty

Opportunities

Attitudes/Rationalisations

Based on the above framework and previous literatures, the following hypotheses are developed: H1

There is positive significant relationship between incentives or pressures and academic dishonesty

H2

There is positive significant relationship between opportunities and academic dishonesty

H3

There is positive significant relationship between attitudes or rationalisations and academic dishonesty RESEARCH METHODOLOGY

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This study involves all final year accounting students in one of the private institutions located at the east coast part of Malaysia. There were about 189 students who are the final year students of accounting courses. Their contribution in this study is significant as they were the nearest to the job market. With regards to the total of 189 respondents, the minimum sample size required was 127. The sample was categorised as convenience sampling which involves collecting information from population members who are conveniently available to provide this information as parallel with Sekaran (1992). Hence, from the population of final year students, 127 students are qualified to be respondents. The instruments were distributed during the early part of the semester and conducted based on selfadministration. During that time, students were still not busy and there was a higher possibility that the respondent will answer the questionnaire properly. The instrument is adapted from Malgwi and Rakovski (2009) and Becker et al. (2006). The instrument comprises of three sections: Section one contains nominal variables that include the gender, age, race, current CGPA, frequency of students going back to hometown and the number of study hours on each week. Section two contains questions regarding the students involvement in plagiarism during quiz, exam and in completing their assignment. It also includes how students are bothered when someone commits academic fraud. In section three, the elements of fraud triangle by using five point Likert Scale that ranges from Strongly Disagree (1) to Strongly Agree (5) is highlighted. FINDINGS AND DISCUSSION 127 respondents of the survey comprised of 30% of male and 70% of female respondents. Most respondents aged between 21 to 23 years old (93%). The results demonstrated that the Malay students‘ involvement as respondents were higher (77%) as compared to other races. Similarly to gender, the race allotment in the sample differs from the general student population which has slightly more Malays, followed by the Indian (17%), Chinese (4%), and other races (2%). The students‘ CGPA was one of the important demographic backgrounds which may be an indicator to the students‘ cheating behaviour. Our results demonstrated that the highest percentage of respondents came from the current CGPA of 2.50-2.99 which was 44%. Secondly is respondents who earned 3.00-3.49 (27%), followed by respondents with current CGPA below 2.5 (16.5%), and above 3.5, those of the Dean‘s list students contributed to 12.5% of the total respondents. Since the location of the sample is located at rural area, the number of frequency of students going back to hometown above 4 weeks was 34%. There were some respondents who go back every 2 weeks (23%), every week (22%) and every 3 weeks (21%).

TABLE 1; DEMOGRAPHIC PROFILE OF RESPONDENTS

Frequency 1. Gende

Percentage (%)

Frequency 4. Frequency back 156

Percentage (%)

r: Male Female

to hometown: 38 89

30 70

1 118

0.5 93

7 1

6 0.5

98 5 22 2

77 4 17 2

Every week Every 2 weeks Every 3 weeks Above 4 week

2. Age: 18-20 21-23 24-26 Above 27

22 23 21 34

Below 2.00 2.00-2.49 2.50-2.99 3.00-3.49

1 20 56 34

0.5 16 44 27

Above 3.5

16

12.5

5. Current CGPA:

3. Race: Malay Chinese India Others

28 29 27 43

RELIABILITY TEST The Cronbach Alpha test was carried out by the researchers. The test shows that all the factors which measured the academic dishonesty using the fraud triangle dimension are valid. The Cronbach‘s Alpha value was 0.942, it indicates that all factors have coefficient of more than 0.8 which is above the requirement made by Nunnally (1978) and level of 0.7 as suggested by Hair, Anderson, Tatham and Black (1998). DETERMINANTS OF STUDENTS’ BEHAVIOUR IN RELATION TO ACADEMIC DISHONESTY The findings in Table 2 reveal the rank of academic dishonesty among accounting students‘ in final year. The six reasons for academic dishonesty according to the three fraud triangle dimensions are as follows:

TABLE 2: RANKING OF ACADEMIC DISHONESTY BASED ON FRAUD TRIANGLE DIMENSIONS.

Fraud Triangle Dimension: Pressure Ranking 1

I need to get the grade that I wanted 157

Mean 3.6535

Std Dev 1.17769

I want to get a good paying job I need to be competitive in market I want to compete with other I have no enough time to complete my assignment My family member is depend on me

2 3 4 5 6

3.5354 3.4882 3.3228 3.2598 3.1260

1.22017 1.23998 1.20107 1.16981 1.22793

Ranking 1 2 3 4 5 6

Mean 3.4803 3.2598 3.2047 3.1969 3.1811 3.1732

Std Dev 1.01458 1.13538 1.19083 1.09138 1.23711 1.08448

Ranking 1 2 3 5 4 6

Mean 3.5512 3.4488 3.4252 3.3622 3.4016 3.3150

Std Dev 0.94876 1.04432 1.01199 0.94843 0.98609 1.00555

Fraud Triangle Dimension: Opportunity My friends willing to share answers No one is going to find out I can get the question before exam No supervision from my lecturer My lecturer will not take any action I can easily store or retrieve information Fraud Triangle Dimension: Rationalis ation Exam/ course is very hard anyway Everyone is doing it I studied so hard for the course My lecturer is a hard grader My classmate also copied each other I am not hurting anybody

The test of the hypotheses, the relationship between pressures, opportunities and rationalisations towards academic dishonesty are illustrated in Table 3 using the Spearman‘ Rho correlations. Spearman Rho was used since the data are non-parametric data due to the acceptance of the variable was not normally distributed. It is also because of the point where we used the 5-point Likert scale (Chua, 2008). Results indicate that incentives or pressures have no significant relationship with academic dishonesty. Therefore, reject H1. There were positive significant relationship between opportunities and academic dishonesty at the 0.05 significance level with p = 0.045. The model explained that the academic dishonesty rises as students‘ opportunities to cheat rises with a coefficient of 0.178. If the opportunity factors keep increasing to 10%, then the cheating behaviour will directly increase to 17.8%. Therefore, accept H2. Attitudes or rationalisations give higher and most positive significant relationship towards academic dishonesty at a .05 significance level with p = 0.006. This finding explained that the cheating behaviour rises as student's rationalisation of cheating rises with coefficient of 0.244, when rationalisations increase by 10%, it will directly increase the cheating behaviour by 24.4%. Finding also shows that rationalisations were the highest factor for academic dishonesty. Based on the results, accept H3. TABLE 3: RELATIONSHIP BETWEEN PRESSURES, OPPORTUNITIES AND RATIONALISATIOS TOWARDS ACADEMIC DISHONESTY 158

Academic Dishonesty

1.000

.093

.178*

.244**

Pressures

.093

1.000

.372**

.296**

Opportunities

.178*

.372**

1.000

.563**

Rationalisations

.244**

.296**

.563**

1.000

CONCLUSIONS AND RECOMMENDATION This study intends to investigate the significant relationships of fraud triangles model and academic dishonesty. On the incentives or pressures dimension, findings of this study are not consistent with previous studies like Merritt (2002), Kock and Davison (2003) and Malgwi and Rakovski (2009). This matter needs to be further investigated. On the opportunities dimension, finding of this study was consistent with findings by Buckhoff (2002), Bonita (2004), Zimny et al. (2008), Scanlon and Neumann (2002) and Malgwi and Rakovski (2009). On the attitudes or rationalisations dimension, the finding of the study was consistent with findings by Kock and Davison (2003), Bonita (2004) and Malgwi and Rakovski (2009). Furthermore, the results were in line with Bonita (2004) who stated that rationalisation was one of most top three required elements for a fraud to occur where most students were readily able to rationalise questionable academic behaviour as being. The findings also suggested that rationalisation plays the most important part in determining the academic dishonesty among final year accounting students. Through rationalisation, students will create reason to legalise their fraudulent action. According to Murphy (2012) based on the research in neuroscience, the brain will react negatively to the unethical conduct and rationalisation is used to enable people to calm the negative emotion generated by the brain. By rationalising, people are able to maintain their code of ethics and avoid self guilty. With rationalisation, the pressures will be absorbed and opportunities taken resulting to unethical behaviour by people. This is the main reason why Bonita (2004) stated that rationalisation was a crucial part in most frauds. It is recommended that the universities initiate to develop a syllabus that stresses on the importance of avoiding academic dishonesty so that it can promote the awareness to the students about this issue. Students should be trained on the importance to do the right things through the right ways. Training programs and campaigns must also be organised to ensure that students realise the adverse effect of involving themselves in unethical behaviour. To overcome the opportunities, it is recommended that proper internal controls must be enforced. Each rules and regulations must be implemented according to the specific requirements set out by the university. The lecturers or invigilators must ensure serious supervision during examination so that the students will not get any opportunity to cheat. There are few limitations of this study. The survey participation was limited to the final year accounting students in one of the private institutions located at the east coast part of Malaysia. The results may not apply to other geographical regions or other sub-groups of students. Although the survey was anonymous and voluntary, students completed the survey in the classroom. Students may have self-reported less academic dishonesty due to the physical proximity of other students and the sensitive nature of the topic. The sensitive nature of the topic increases the possibility that 159

respondents will not provide true answers. The social desirability bias claims that survey respondents sometimes respond to surveys in a manner that make themselves look more socially desirable.

REFERENCES Alleyne, P., Devonish, D., Nurse, J and Cadagan, C. (2006). Perception of moral Intensity Among Undergraduate Accounting Students in Barbados. Journal of Educational Leadership Journal, Vol. 10 (1), pp. 37-54. Becker, D., Connolly, J., Lentz, P., and Morrison, J. (2006). Using the business fraud triangle to predict academic dishonesty among business students. Academy of Educational Leadership Journal, 10(1), pp. 37-54. Bonita, K.P. (2004). Application of White-Collar Crime Research to Academic Fraud: A Focus on Rationalizations of Academic Students. Journal of College Teaching & Learning, Vol.1, No.5, pp. 51 – 64. Bowers, W. J. (1964). Student Dishonesty and its control in College, New York: Bureau of Applied Social Research, Columbia University. Buckhoff, T. A. (2002). Preventing Employee Fraud by Minimizing Opportunity, The CPA Journal, 72 (May), pp. 64 – 65. Burke, J.A., Polimeni, R.S. and Slavin, N.S. (2007). Academic Dishonesty: A Crisis on Campus Forging Ethical Professionals Begins in the Classroom. The CPA Journal. (May), pp. 58 – 65. Consideration of fraud in a financial statement audit (2002). Statement on Auditing Standards No. 99. New York: AICPA. Chapman, K.J. and Lupton, R.A (2004). Academic dishonesty in a global educational market: a comparison of Hong Kong and American university business students, The International Journal of Educational Management, 18 (7), pp. 425–435. Chua, Y. P. (2008). Research Statistics : Data Analysis for Ordinal and Nominal Scales, Shah Alam: McGraw-Hill Education. Cressey, D. R. (1973). Other People‟s Money, Montclair: Patterson Smith. pp. 30. Florida Institute of Technology, Academic Support Center. (2001). Academic Advising Handbook, pp.62.68. Grimes, P.W. (2004). Dishonesty in academics and business: a cross-cultural evaluation of student attitudes. Journal of Business Ethics, Vol. 49 No. 2, pp. 273-90. Hair, J.F., Anderson, R.E., Tatham, R.L. and Black, W.C. (1998). Multivariate Analysis,. New York, McMillan. Kidwell, L. A., Wozniak, K. & Laurel, J.P. (2003). Student Reports and Faculty Perceptions of Academic Dishonesty. Teaching Business Ethics, 7 (3), pp. 205-214.

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Kock, N. & R. Davison (2003). Dealing with plagiarism in the information systems research community: A look at factors that drive plagiarism and ways to address them. MIS Quarterly, 27(4), pp. 511-532. Lars R.J., Robert T., Sharon I. and Leslie F. (2001). Academic Dishonesty ,Cheating, and Plagiarism,. Melbourne, Florida, USA, Florida Institute of Technology .. Malgwi, C. A. & Rakovski, C. C. (2009). Combating Academic Fraud: Are Students Reticent about Uncovering the Covert? Journal of Academic Ethics, 7(3), pp. 207-221. McCabe, D. L., Trevino, L. K., & Butterfield, K. D. (1996). The influence of collegiate and corporate codes of conduct onethics-related behavior in the workplace. Business Ethics Quarterly, 4, pp. 471–476. McCabe, D. L. (1997). Classroom cheating among natural science and engineering majors. Science & Engineering Ethics, 3: 433–445. Merritt, J. (2002, December 9). You mean cheating is wrong? Business Week, p. 8. Murphy, P. (2012). Rationalizing fraud. http://qsb.ca/magazine/summer-2011/features/rationalizingfraud. Retrieved 18 March, 2012. Nunnally, J. C. (1978). Psychometric Theory, (2nd Ed.). New York: McGraw-Hill. Park, C. (2003). In other (people‘s) Words: plagiarism b university students-literature and lessons. Assessment & Evaluation in Higher Education, 28 (5), pp. 471-488. Pullen, R., Ortloff, V., Casey, S., & Payne, J.B., (2000). Analysis of academic misconduct using unobtrusive research: A study of discarded cheat sheet. College Student Journal, 34, pp. 616. Pizzolatto, A.B. & Bevill, S. (1996). Business ethics: a classroom priority? Journal of Ethics, 15, pp. 153-8.

Business

Rittenberg, L.E. & Miller, P.K. (2005). Sarbanes-OxleY Section 404 Work: Looking at the Benefits. The IIA Research Foundation, pp. 1-42. Scanlon, P. M., & Neumann, D. R. (2002). Internet plagiarism among college students. Journal of College Student Development, 43(3), 374-385. Sekaran U. (1992). Research Methods for Business: A Skill-Building Approach,. 2ndEdition. New York, NY: John Wiley & Sons, Inc. Zimny, S.T., Robertson, D.U. & Bartoszek, T. (2008). Academic and Personal Dishonesty in College Students. North American Journal of Psychology, 10 (2), pp. 291-312.

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FIRM CHARACTERISTICS AND ITS EFFECT ON STOCK RETURN

Nor Edi Azhar Binti Mohamad Finance and Economic Department,College of Business Management & Accounting, Universiti Tenaga Nasional, Sultan Haji Ahmad Shah Campus, 26700 Muadzam Shah, Pahang, Malaysia Tel(o):(+609)455 2020 ext:3324; Fax :(+609)4552006 E-mail:[email protected]

Thilagavathi A/P Veloo Finance and Economic Department,College of Business Management & Accounting, Universiti Tenaga Nasional, Sultan Haji Ahmad Shah Campus, 26700 Muadzam Shah, Pahang. E-mail: [email protected]

ABSTRACT

The main purpose of this study is to investigate the relationships between firm characteristic using financial ratios with stock market returns represented by the Capital Asset Pricing Model (CAPM). A sample of companies that represent the FTSE Bursa Malaysia KLCI was selected for 10 years observation from 2001-2010. Analytical and statistical methods are applied to the developed hypotheses to find an association between firm characteristic and the CAPM. The study found that there is a significant relationship between firms characteristics represented by the proxy of Book-tomarket ratio, dividend yield and return on assets with CAPM. Keywords: Capital Asset pricing model (CAPM), Book –to- Market Ratio, Price to Earnings Ratio, Dividend Yield, Return on Assets.

INTRODUCTION The Capital Asset Pricing Model (CAPM) is the most influential and widely used factor pricing model since it offers influential predictions about how to measure risk and the relationship between expected return and risk. Developed by Sharpe (1964) and Linter (1965), CAPM was the first theoretical model that explains the non-diversifiable market risk‘s impact on return which estimates the expected return of a stock. Therefore non-diversifiable risk is the only risk factor that is used in the model, which is represented by beta in the CAPM model. Some researchers have argued that other variables such as book-to-market ratio and price-to-earnings ratio exist that could significantly explain the expected return. Fama and French (2003) find that there is a significant relationship between book- to- market value and stock return and also an association with price- to- earnings ratio. Drew et al (2003) indicate that market beta alone is not sufficient to describe the variation in average equity return. They find that there is a statistically significant non-beta risk associated with the book- to- market equity. According to Pandey and Chee (2004), market beta alone as well as 162

jointly with other variables has a consistent ability to explain the stock returns and size has the most dominant and constant role in stock return. According to CAPM, beta is the only variable that significantly affects return and the most frequently applied model for prediction of stock returns. However apart from the CAPM, there are empirical studies carried out on factors and variables capable of predicting the stock return such as price- to- earnings ratio and book- to- market ratio. Extensive empirical research on CAPM was carried out worldwide by academia, nevertheless, the impact of firm characteristics using various financial ratios towards CAPM from a Malaysia perspective might be vaguely difference due to the divergence in the business environment from other countries. Since earlier studies were built on western data and specific research studies exclusively on the dynamic relationship between CAPM with market ratio, profitability ratio and other fundamental factors for the Malaysian stock market are scanty, thus this study is conducted in an attempt to bridge the gap in the literature by offering empirical evidence to the extent of which the result in Malaysia would be parallel to past studies. Considering Malaysian stock market as emerging markets which can be differentiated from developed markets with respect to their various natures and inherent dynamics, therefore, the objective of our study is to discover the relationship between CAPM with firm characteristics in a sample of companies that represents the FTSE Bursa Malaysia KLCI component listed in the Main Board of Bursa Malaysia.

LITERATURE REVIEW

Several researchers have examined the relationships between stock returns and selected characteristics which include a variety of findings. Some studies have concluded that company fundamentals such as book- to -market ratio and price- to- earnings ratio are major factors that affect stock returns. Others indicated that size, fixed asset ratio, liability ratio and intangible assets, and dividend yield are the most influencing factors of stock returns. There are a number of empirical research and development research on CAPM which was one of the important topics as founded by Fama and French (1992), which indicate the relationship between Beta (β) and the average return was weak over the era from 1941 to 1990 and was nearly nonexistent from 1963 to 1990.The second, most important argument made by Ross, Westerfield & Jaffe (2005) is that the average return on a security is negatively related to both the firm‘s price- to- earnings ratio (P/E) and the firm‘s marketto- book value (M/B) ratio. A number of researchers pointed out that the book- to- market ratio could be an additional risk factor. Stocks with a high BTM ratio earned higher returns than stocks with a low BTM ratio. The difference between the high BTM ratio stocks‘s earning and low BTM ratio stocks‘ earning is the value premium findings by Daniel, Titman and Wei (2001), and Fama and French (1992). As discussed by Fama and French, (1992), there is a strong relationship between the average returns on stocks and size, but there is no reliable relationship between average returns and β. It has been further argued that there is a strong cross –section influence between average returns and book-tomarket equity. If anything, this book-to- market affect is more powerful that the size effect. Findings also show that the combination of size and book-to-market equity absorbs the apparent roles of leverage and E/P in stock returns. Another research that was done by Chen, Kan, and Anderson, (2007) shows the results which produced strong evidence that size and BTM ratio could well be explained by alternative variables. Additionally, the alternative variables are better at explaining the size and BMT effects in China‘s stock market. The findings also reveal that market return is negatively related to market size and positively related to BTM ratio. 163

A study of the relationship between average stock return with book –to- market ratio and price- toearnings ratio by Najed, (2008) also finds that the BTM ratio has a significant relationship with stock returns. From his perspective, Malaysia is a potential market from which to get profit. Thus, BTM ratio is an important ratio to predict stock return for both investors and big organizations who are seeking higher returns. Senthilkumar (2009) examines the relationship between expected stock return and size and market- to- book ratio in five selected industries of Indian emerging markets and found that although small firms have to a certain extent higher average returns than large firms in selected industries of Indian stock returns, the market- to- book variable seems to have a consistently stronger role in average returns. Sezgin (2010) investigates the relationship among market stock return, dividend yields and price- toearnings ratio. He states that the P/E ratio is widely used, particularly by practitioners, as a measure of relative stock valuation. The P/E ratio is an indicator which indicates the current mood of investors and how much they are willing to pay per unit of company earnings. The Granger test is applied to determine existence and direction of causality among variables. His studies revealed P/E also grows when both the stock price and the earnings per share increase and shows there is a significant relationship among the variables. Mehmet Aga and Berna Kocaman (2006) found from regression results, for each of the stock‘s price- to- earnings ratio (PE) ratio appears to be a significant explanatory variable for the stock returns. The lags that are included in the model for each of the stocks differ and the R-squares are high for each of the model. While, Najed (2008) found that PE ratio is not significantly related to stock return which is consistent with Fama & French (1992) found that there is no significant relationship between price- to- earnings ratio and the stock return

Dividend policy is an important consideration because of the likely impact on the risk-return characteristics of individual stocks. Gombola, and Ying, (1993) compared the relationship between dividend yields and stock returns in bull and bear markets. Their findings show that average monthly stock return is positively related to dividend yield. Apart from that in particular, high yield stocks are shown to perform better during a bear market than a constant- coefficient market model would predict. The results also revealed the relationship between return and yield could be specific to any period under examination. A study by Kwon,Shin, and Bacon, (1997), investigated the relationship between stock market returns and macroeconomic variables in the Korean stock market, using regression models. Based on their findings, they conclude that the Korean market is more sensitive to real economic activities rather than external factors such as interest rates. Their findings reveal that dividend yield significantly affected the stock return. A study by Fargher and Weigand, (2009) examined the cross-sectional differences in the profits, return and risk of high- and low-market-tobook ratios (M/B) stocks before and after the initiation of regular cash dividend payments. Their findings revealed that total stock return volatility is lower after dividend initiation, although the decrease in risk occurs only among the low M/B quartiles. Several studies specifically investigate the components of the economics variable towards stock return. One of the studies done by Liqun and Andrew (2005) revealed that the exchange rate and GDP seem to affect returns of all portfolios, while the inflation rate, exchange rate, and money supply were having a negative relationship with returns for portfolios of big and medium companies. Tarika , Seema and Varsha (2010) investigated the cause and effect relationship of portfolios GDP with stock returns in Taiwan 50 indexes and indicated that the exchange rate and GDP seem to affect positively all of the portfolio returns.

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Kwon, Shin, and Bacon (1997) in their study found that the investment perception in the Korean financial markets is quite different from the perception found in U.S and Japanese markets. The U.S and Japanese stock market are quite sensitive to inflationary variables such as changes in unexpected inflation, expected inflation and interest premium. Their findings also reveal that the Korean market is more sensitive to international trading activities rather than inflation or interest rate variables.

Another research done by Muhammad Ishfag, Ramiz and Awais (2010) stated in their findings that the macro economic variables always have a significant impact on a stock market. Their findings also state that a decline in interest rate gives a positive message to the stock market and stock returns increase eventually while changes in exchange rates provide a positive impact.

DATA AND METHODOLOGY

The limitation in this research is that the sample selection which is only focused on the largest 30 companies listed on the Main Board by full market capitalisation that meet the eligibility requirements of the FTSE Bursa Malaysia Ground Rule. Starting July 6, 2009, the enhanced benchmark index for the local equity market, the FTSE Bursa Malaysia KLCI, is based on the freefloating market capitalisation methodology and its constituents will be liquidity-screened. Instead of tracking 100 stocks as done by its predecessor, the FTSE Bursa Malaysia KLCI is made up of the 30 largest listed companies by market value, with at least a 15% free float. However due to limited data available only 26 companies were selected yearly for 10 years which is from January 2001 until December 2010. The selection of the variables (dependent and independent) is primarily guided by previous empirical studies and the availability of data. For this study, the internal factors which are chosen from market ratio are book- to- market ratio, price- to- earnings ratio and dividend yield; the profitability ratio is represented by return on assets and external factors are the interest rate and the Gross Domestic Product (GDP). For the measurement of stock returns we use the Capital Asset Pricing Model (CAPM) framework that was developed by Sharpe (1964) displayed as follows: R  R F  β I ( RM  R F ) β I is the company' s beta RF is the risk free rate RM is the market risk

(1)

We use the returns on the Kuala Lumpur Composite Index (KLCI) as a proxy for returns on the market portfolio to represent the Malaysian perspective of market performance and the risk-free rate of return that was proxied by the Malaysia Government Security bills. The beta of asset in which can also be expressed as below where ra measures the rate of return of the asset, rp measures the rate of return of the portfolio, and cov (ra, rp) is the covariance between the rates of return. (2) Based on the theoretical and empirical evidence from the literature, we test the following hypotheses: H1: There is a significant relationship between average stock return and firm characteristics 165

Next, the relationship between the CAPM and firm characteristic indicators was estimated using the following regression equations:

CAPM

i

    ( BMR )   ( PE )   ( DY )   ( ROA )   ( IR )   (GDP )   i 1 1 2 2 3 3 3 3 4 4 4 4

(3) Where: CAPMi  the required return of the ith company‘s of the ith year BMRi  the book to market ratio of the ith company‘s of the ith year PEi  the price earnings ratio of the ith company‘s of the ith year DYi  the dividend Yield of the ith company‘s of the ith year ROAi  the return on asset of the ith company‘s of the ith year

IRi  the interest rate of the ith company‘s of the ith year GDPi  the gross domestic product of the ith company‘s of the ith year

EMPIRICAL RESULTS Correlation Analysis TABLE 1 : CORRELTION ANALYSIS AMONG VARIABLES

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Table 1 shows the correlation analysis between independent variables for checking multicollinearity. From this analysis, there is no multicollinearity between all independent variables though the variable is negatively and positively correlated but it is considered low. Therefore, it is not large enough to cause any concern in the regression model.

Regression Analysis To test the effects of firm characteristic on stock return, a regression analysis are given using 260 firm-years observations and the results are presented in table 7. The result of the VIF collinearity statistics in table 2 shows values of less than 10, which means there is no collinearity between the variables. The regression results for BTMR, DIV and ROA indicate a 1% confidence level having a positive association with CAPM indicating any increase in CAPM can be explained by an increased in BTMR, DIV and ROA thus supporting hypotheses 1. This finding of BTMR is consistent with the previous study by Najed (2008). From his perspective, Malaysia is a potential market to get high profit, thus BTMR play an important ratio to predict stock returns for both investors and big organization. While the result on DIV corroborates with Kwon, Shin, and Bacon (1997), who investigated the relationship between stock market returns and macroeconomic variables such as dividend yield in the Korean market. Their findings reveal that dividend yield significantly affected the stock return. TABLE 2 : REGRESSION ANALYSIS OF CAPM AND INDEPENDENT VARIABLES 167

Variable

Beta Coefficients

t-value

Sig-value

(Constant) -2.224 0.027 BTMR 0.151 2.754 0.006*** DIV 0.399 7.042 0.000*** PE 0.005 0.084 0.933 INT.RATE -0.104 -1.900 0.059* ROA 0.181 3.234 0.001*** GDP 0.123 2.233 0.026** 2 R 0.260 F-Value 14.777*** Variance Inflation Factor: VIF = 1/ (1-R2) *, ** and *** Significant at 10%, 5%and 1% levels, respectively.

Collinearity Statistics Tolerance VIF 0.980 0.914 0.969 0.980 0.929 0.963

1.021 1.094 1.032 1.021 1.076 1.039

As for PE in relation to CAPM in Malaysia is concerned, this disclosed a positive insignificant association with CAPM implying that the increase or decrease of PE will not affect the CAPM. Thus the result did not support our Hypothesis 1 indicating changes in CAPM cannot be explained by the changes in PE. Our result is similar to the study done by Najed (2008) which also indicated that PE has an insignificant impact on stock returns.

The regression results for INT.RATE indicate a 10% confidence level having a negative association with CAPM, while GDP is at the 5% confidence level having a positive association with CAPM. This indicates that any increase in interest rates can be explained by a reduction in CAPM while any increase in CAPM can be explained by an increase in GDP thus supporting hypotheses 1. We mentioned here that the study done by Tarika Seema and Varsha (2010) which indicated similar results for GDP. This confirms the functions of GDP as an important economic indicator in its own right with the ability to effect the stock market return and can be used by investors to measure future economic prospects. Thus any significant change in the GDP, either up or down can have an immense consequence on investing sentiment. The regression results support hypotheses 1as depicted by table 3, the F statistic is substantiated at the 1% significance level for CAPM (F=14.777) implying the null hypotheses that the regressions coefficients are all zero can be rejected at the 1% level of significance. Though, the R squared (0.26) statistically shows weak relationships for the hypotheses tested, however, the estimated regressions is efficient for predictions. Thus, the hypotheses 1 can be accepted implying that there are associations between firm‘s characteristics with the stock returns of listed companies in Malaysia

CONCLUSION In this paper we make an empirical research on the associations between firms‘ characteristics with stock returns. The study employed one model specification in order to test the postulated hypotheses, using the stock return measure of CAPM along with other independent variables for 26 selected listed companies from the FTSEKLCI index in Bursa Malaysian for the period of 2001 until 2010. On the basis of the findings of the research, it can be concluded that there are significant relationships between firms‘ characteristics with stock returns as our results suggest that the firms‘ 168

characteristics components and stock returns in Malaysia disclose both positive and negative associations. The study reveals that out of six components selected for the study, BTMR,DIV,ROA and GDP show positive significant relationships with CAPM .Whereas, INT RATE illustrates a negative significant relationship with CAPM, whilst, PE is positively significant with CAPM.

REFERENCES

Chen .J, Kan K.L and Anderson .H (2007): Size, Book/Market Ratio and Risk Factor Returns: Evidence from China a-Share Market Managerial Finance Vol. 33 No. 8, 2007 pp. 574-594 Daniel, K, Titman, S, and Wei, K C.J. (2001).Explaining the cross-section of Japan: factors or characteristics. Journal of Finance, 61(2), 743-766.

stock

returns in

Drew, M. E., Naughton, T. and Veeraraghavan, M (2003).‖Firm Size Book to Market Equity and Security Returns: Evidence from the Shanghai Stock Exchange.‖Australian Journal of Management Vol. 28, pp 119-139 Emrah Ozbay (2009) the Relationship between Stock Returns and Macroeconomic Factors: Evidence from Turkey. Retrieved from:http://www.cmb.gov.tr/displayfile.aspx?action=displayfile&pageid=61&fn=61.pdf Retrieved April 13, 2012 Fama, E. F. and K.R. French (2003) The Capital Asset Pricing Model: Theory and Evidence. The Journal of Political Economy, Vol. 81, pp. 607-636. Fama, E. F. and K.R. French (1992), The Cross Section of Expected Stock Returns, Journal of Finance, 47, 427-465. Fargher, N.L and Weigand, R.A (2009) Cross-Sectional Differences in the Profits, Returns and Risk of Firms Initiating Dividends. Managerial Finance Vol. 35 No. 6, pp. 509-530 Gombola, Michael J. and Ying L.Y (2009), Dividend Yields and Stock Returns: Evidence of Time Variation between bull and bear markets. The Financial Review; Aug 1993; 28, 3; pg. 303

Kwon, C.S; Shin T.S. and Bacon, F.W. (1997), The Effect Of Macroeconomic Variables On Stock Market Returns In Developing Markets. Multinational Business Review; fall 1997; 5, 2; p. 63-70. Lintner, J (1965), The valuation of risky assets and the selection of risky investments in stock portfolios and capital budgets, in Review of Economics and Statistics, 47, 13-37. Liu,L. and . Rettenmaier, A. J. (2005) Stock Returns and Economic Growth. Retrieved from: http://www.ncpa.org/pdfs/ba519.pdf on March 5, 2012

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Mehmet A. Kocaman, B. (2006): An Empirical Investigation of the Relationship between Inflation, P/E Ratios and Stock Price Behaviors Using a New Series Called Index-20 for Istanbul Stock Exchange International Research Journal of Finance and Economics ISSN Issue 6 Pp, 133-165

Muhammad Ishfaq Ahmad, Ramiz Ur Rehman, Awais Raoof (2010): Do Interest Rate, Exchange Rate Effect Stock Returns? A Pakistani Perspective International Research Journal of Finance and Economics ISSN Issue 50,Pp.146-150 Najed Massad Sulaiman Alrawashdeh (2008): The Relation between Average Stock Return to Earning Ratio and Book to Market Ratio in FTSEBM. Retrieved from: http://www.cass.city.ac.uk/__data/assets/pdf_file/0011/76916/Yu-141-REVISED.pdf Retrieved on April 15, 2012 Paavola. M, (2006), Tests of the Arbitrage Pricing Theory Using Macroeconomic Variables in the Russian Equity Market. Retrieved from: http://www.doria.fi/bitstream/handle/10024/30869/TMP.objres.246.pdf?sequence=1 Retrieved on March 5, 2012 Pandey I.M and Chee H.K, The Expected Stock Returns Of Malaysian Firms: A Panel Data Analysis. Retrieved from: http://www.iimahd.ernet.in/publications/data/2001-09-01IMPandey.pdf Retrieved on April 15, 2012 Ross, S.A. Westerfield R. W. and Jaffe, J. (2005), Corporate Finance, New York, McGraw Hill. Senthilkumar G. (2009): Behaviour of Stock Return in Size and Market-To-Book Ratio – Evidence from Selected Indian Industries ,International Research Journal of Finance and Economics Issue 33 ,pp142-153 Sezgin, F.H (2010) , An Empirical Investigation of the Relationship among P/E Ratio, Stock Return and Dividend Yields For Istanbul Stock Exchange International Journal of Economics and Finance Studies Vol 2, No 1.pp 15-23. Sharpe, W.F (1964), Capital Asset Prices: A Theory of Market Equilibrium under Conditions of Risk. The Journal of Finance, Vol. 19, No. 3. pp. 425-442 Tarika S, Seema M and Varsha, M.S (2010) Macroeconomic Factors and Stock Returns: Evidence from Taiwan Journal of Economics and International Finance Vol. 2(4), pp.217-227

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IMPACT OF BLOCKHOLDER OWNERSHIP AND DIVIDEND PAYOUT ON GOVERNMENT-LINKED COMPANIES’ (GLCs’) VALUE IN MALAYSIA

Nor Razuana Binti Amram Department of Finance & Economics Universiti Tenaga Nasional (UNITEN) 26700 Muadzam Shah, Pahang, Malaysia. Norrazuana @uniten.edu.my Prof. Madya Dr. Angappan @ Chockalingam A/L Regupathi UUM College of Business Universiti Utara Malaysia

ABSTRACT

Government-linked companies (GLCs) play an important role in the development of the Malaysian economy. Good corporate governance can help a company obtain external financing, pay out higher dividends and improve the efficiency of its investments (La Portal et al. (2000)). Therefore, this paper examines the relationship between blockholder ownership and dividend payout towards the company value among government linked companies (GLCs) in Malaysia. This study is based on a sample of 30 companies over a period from 2004 to 2009. Statistical techniques of correlation and regression are used to explore the relationship between blockholder ownership, dividend payout and company value. The finding indicates that there is a significant relationship between dividend payout and firm value.

Keywords: Government –linked companies, (GLCs), Blockholder ownership, Dividend payout. . INTRODUCTION

Malaysia has implemented some reforms in corporate governance in the form of the Malaysian Code on Corporate Governance 2001 (MCCG 2001). Some regulations (e.g. the revamp of Listing Requirements of Bursa Malaysia and securities law amendments) have been amended, and some institutional reforms (e.g. the establishment of Minority Shareholders Watchdog Group (MSWG)) were introduced to comply with industry best practices elsewhere. 171

Enron and WorldCom in the U.S. collapsed after massive restatement of their financial statements. New York Times ―After 10 years, corporate oversight is still dismal,‖ (January 26, 2003). The events of the East Asian Financial crisis in late 1997 showed the failure of corporate governance systems internationally. Many scandals have also been reported in Malaysia, such as Perwaja Steel, Malaysia Airlines, Technology Resources Industries, Sime Darby and Bumiputra Malaysia Finance (Rashidah, 2006).

The present study basically attempts to augment the existing evidence on the association between firms‘ value and their governance mechanisms, but it takes into consideration the specific characteristics of Malaysian government-linked companies (GLCs) which are used as the sample in the study. Two governance mechanisms that are examined in the study are blockholder ownership and dividend payout. The objective of this study is to examine the relationship between blockholder ownership and dividend payout towards a firm‘s value.

LITERATURE REVIEW

According to the Putrajaya Committee on GLC High Performance (2006), Government Linked Companies (GLCs) are defined as companies in which the Malaysian government has a direct controlling stake. Its modus operandi is commercial in nature. The controlling stake refers to the power of the government to appoint members of the board of directors and to be involved in making major decisions, for example, awarding of contracts, restructuring, financing, acquisition, and divestment. The Malaysian government‘s control of GLCs is achieved through Government Investment Linked Companies (GLICs), which have invested their funds in GLCs. Currently there are 6 GLICs, namely, Employees Provident Fund (EPF), Lembaga Tabung Angkatan Tentera (LTAT), Lembaga Tabung Haji (LTH), Permodalan Nasional Bhd (PNB), Ministry of Finance Ltd. (MOF) and Khazanah National. GLICs are the investment arms of the government that allocates government funds to the GLCs. In addition to having ownership in GLCs, the Malaysian government also has influence in the appointment of members of the board of directors and managers for senior positions.

Furthermore, in the Ninth Malaysia Plan, the government has intensified its effort to enhance the integrity, transparency and accountability of the public and private sectors and further improve the level of good governance in order to facilitate growth of investment in the specific sectors and in the country, generally. Based on The Edge Malaysia report on 6 April 2009, Tan Sri Azman Mokhtar,Managing Director of Khazanah Nasional Bhd said, ―Some of the companies were not strong (as they are today) and in all probability would not have survived (the current downturn)‖. (The Edge, Malaysia, 2009)

The publicly listed GLCs account for the least one-third of the market capitalization on Bursa Malaysia and half of the market capitalization of the benchmark Kuala Lumpur composite index. The prosperity of the GLCs certainly attracts more investors to Bursa and boost the value of the 172

government‘s held capital, as well in providing it with higher dividend income from improved profitability. Generally, only companies that are profitable pay dividends. A few companies in Malaysia have a very high dividend payout ratio (DPR). It is not surprising to find that some companies also pay out dividends even though they reported a loss for that year. This is due to the unwillingness of companies to cut or skip dividends, as research findings have shown that investors, in both developed and emerging markets, react negatively to a dividend decrease (Norhayati, 2005).

Theoretically, blockholder ownership is the percentage held by substantial shareholders, defined as holding at least 5 percent or more of a firm‘s outstanding common stocks. These owners are often able to influence the company with voting rights awarded with their holding. Recent research has emphasized blockholders as they are thought to monitor a firm's operations (Morck, Shleifer, and Vishny (1988)), reduce agency costs and increase firm value (McConnell and Ser-vaes (1990), Barclay and Holderness (1991), and Bethel, Liebeskind, and Opler (1998).

Classic literature (Jensen and Meckling, (1976); Morck, Shleifer, and Vishny, (1988); Stulz, (1988), indicate that greater managerial ownership benefits shareholders because it increases managers‘ incentives to increase firm value. But when managerial ownership becomes too large, it enables managers to entrench themselves, so that firm value falls as managerial ownership increases beyond a certain point. Because of these countervailing forces, the relationship between firm value and managerial ownership is not monotonic, and there is an optimal level of ownership. However, an increase in managerial ownership at low levels increases firm value.

The theory of dividend and its effect on the value of the firm is possibly one of the most important, but puzzling theories in the field of finance. Academics have developed many theoretical models describing the factors that managers should consider when making dividend policy decisions. Dividend policy means the payout policy that managers follow in deciding the size and pattern of cash distributions to shareholders over time. In a seminal article, Miller and Modigliani (1961) argued that given perfect capital markets, the dividend decision does not affect firm‘s value and is, therefore, irrelevant. However, given the reality of less than perfect conditions, most financial practitioners and many academicians believe otherwise. They have offered many theories about how dividends affect a firm‘s value and how managers should make dividend policy decisions.

Dividends are the portion of corporate profits paid out to shareholders. When a company earns a profit or has surplus, that money can be put to two uses; it can either be re-invested in the business (called retained earnings), or it can be paid to the shareholders as dividends. Many corporations retain a portion of their earnings and pay the remainder as a dividend. Dividends are decided upon and declared by the board of directors. This may involve comparing the cost of paying dividends with the cost of retaining earnings.

In Malaysia, studies on dividend policy are limited. Annuar and Shamsher (1993) and Mansor (1993) remain two early studies in this regard. The authors stated that Malaysian companies have to pay corporate tax on pre-tax profits that are retained. As such, it can be expensive for a Malaysian company to retain earnings. Therefore, in such a tax environment, companies should pay high dividends to benefit from the full imputation of tax system. Nevertheless, paying out high dividends is not a typical characteristic of Malaysian companies. There is a reason for this. Mokhtar et al. 173

(2006) highlighted that there were rational speculative bubbles in the Malaysian stock market before and after the 1997 financial crisis. When the majority of investors are short term (speculative), they are not interested in dividends.

Despite the fact that GLCs make up the backbone of the Malaysian companies, they are severely criticized. One of the criticisms is that many Malaysia GLCs are cash-rich but poorly run (―Revamp of Malaysian Government-linked Companies,‖ 2004, May 14) (Source: G20 Financial Reports, Bloomberg consensus estimates, PCG analysis). Furthermore, it is reported that over the last five years, the total return to shareholders of public listed GLCs is below overall market performance by 21 percent (Abdullah, 2004). A recent analysis of the GLCs‘ performance in 2005 done by Amresearch reveals these disappointing facts; (1) only six out of 24 GLCs under Khazanah yielded positive total shareholder return in 2005, with only five showing year-on-year gains in their share prices; (2) only five GLCs outperformed the Composite Index during the period from January to December 19, 2005; (3) only eight GLCs had recorded higher earnings in the nine months ended September 2005, compared with the previous corresponding period (Tee and Nathan, 2005). Another study, as reported in the Economist, found that GLCs are more highly indebted than average, generate less profit per worker and also earn a lower return on equity (An Attempt to Revive, 2005, August 18).

Meanwhile in China, Tian and Estrin (2005) found that government ownership reduced corporate value due to political interference. Also Xu and Wang (1999), government enterprises performed worse in terms of profitability than non-government enterprises. Wei and Zhang (2005) examine the performance of domestic Chinese companies, belonging to various ownership categories versus foreign-invested enterprises (FIEs) based on two nation-wide surveys conducted by the National Bureau of Statistics in 1998 and 2002. It was found that both domestic non-state-owned companies and foreign-invested enterprises performed better than state-owned enterprises.

RESEARCH METHODOLOGY

SAMPLE AND DATA COLLECTION

Parallel with the substantial shareholding characterisation, the search of Malaysian GLCs is done using the company database provided by the Kuala Lumpur Stock Exchange- Research Institute of Investment Analyst Malaysia Information System (KLSE-RIS). Focus has only been made on publicly listed companies due to their reliable and publicly available financial and accounting data. The list of companies obtained from the KLSE-RIS is used as initial sample, consists of 33 companies. As the list provided by KLSE-RIS is based on the latest shareholding, the companies‘ 2009 annual reports. are then examined to check whether Minister of Finance Incorporated, Khazanah Nasional Berhad, Permodalan Nasional Berhad, Amanah Raya Berhad or Atatutory bodies (i.e. Employment Provident Fund, Kumpulan Wang Amanah Pencen, Lembaga Tabung Angkatan Tentera and Lembaga Urusan dan Tabung Haji) were really substantial shareholders of the companies in 2009. From the screening process, 30 companies match the criteria needed and thus were selected as the final sample. These 30 companies operate in different industries namely trading 174

or services; infrastructure; industrial products; finance; technology; consumer products; plantation; property; and construction. Data needed for the study is collected from the companies‘ 2004-2009 annual reports. These annual report are obtained either from the companies‘ websites, KLSE website, Datastream, and KLSE library. VARIABLES’ MEASUREMENT

This study investigated two different types of variables; the independent and dependent variables. The independent variables are the factors that are hypothesized to cause certain effects upon the dependent variable. The dependent variables are the quantities that are affected by the independent variables. The discussion on the variables‘ measurement was categorized into two sections; (1) the dependent variable is the firm value measure by Tobin‘s Q (2) the independent variables in this study are blockholder ownership and dividend payout.

DEPENDENT VARIABLES

Dependent variables that are examined in the present study are measure of firm value. Firm value is measured by dividing the sum of the market value of equity and the book value of the total debt by the book value of assets. I use this approximation denoted as the ―simple Q‖ by Loderer and Martin (1997) since a Q measure of equity at replacement costs was not available. However, Chung and Pruitt (1994) found that the correlation between the ―simple Q‖ and a measure of Q that attempts to use market values throughout is as high as 0.97. To correct for a right-skewed distribution of the firm value variable, log values were used. The present study employed Chung and Pruitt‘s (1994) alternative formula for approximating Tobin‘s Q: Tobin‘s Q= (Market price-year end * Common shares outstanding + Book value of total debt) Book value of total assets

INDEPENDENT VARIABLES

As highlighted two independent variables which represent in present study namely blockholder ownership and dividend payout. The independent variables are measured as follow:

i. Blockholder Ownership

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Blockholder ownership was measured by the fraction of closely held shares (Worldscope/Disclosure, 1997) including shares held by owners who hold more than 5%;shares held by officers, directors and their families, shares held in trust, shares held by another corporation (except in a fiduciary duty by banks) or shares held by pension/benefit plans.

ii. Dividend Payout The dividend payout ratio (DPR) was measured by taking EPS divided by EPS. The payout ratio provided an idea of how well earnings support the dividend payments. More mature companies tend to have a higher payout ratio. Normah et al. (2006) found the highest dividend payout average for the years 2003 – 2005 of 212 companies surveyed was about 83 percent.

TABLE 1: FRAMEWORK

In order to summarize then discussion in this section, Table 1 provides all the variables included in the analysis as well as their measurements (appendix).

DATA ANALYSIS TECHNIQUES

A number of data analysis techniques were applied in the present study. Firstly, descriptive statistics regarding the variables including mean, median, standard deviation, minimum and maximum value, as well as skewness and kurtosis were computed to analyse the trends and normality blockholder ownership and dividend payout as practiced by GLCs. In addition, Pearson correlation coefficient was used to examine the relationship between dependent and independent variables. The Pearson correlation coefficient measures the degree or strength of linear association between two variables (Hair, Bush and Ortinau, (2003). Usually, a range of coefficient between 0.81 and 1.00 is considered very strong (while for a range between 0.00 and 0.20, there is a possibility that the null hypothesis will be rejected) (Hair et al., 2003).

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Besides measuring the association between the two variables tested, correlation coefficient can also be used to identify the problem of multicollinearity. This problem is defined as a situation in which several independent variables are highly correlated with each other and as a consequence, it results in difficulty in estimating separate or independent regression coefficients for the correlated variables (Hair et al.,(2003).

Thus, it is suggested that when the correlation between the independent variables were too high, so one of the highly correlated should be removed (Hair et al. (2003). To have a more meaningful result, ordinary least squares regression analysis was used to test for the hypothesized relationships. Basically, regression analysis is used to (1) determine whether the independent variables explain a significant variation in the dependent variable (i.e. whether a relationship exists) (2) determine how much of the variation in the dependent variable can be explained by the independent variables (i.e. strength of the relationship) (3) determine the structure or form of the relationship (i.e. the mathematical equation relating the independent and independent variables); and (4) predict the value of the dependent variable (Malthotra, (2002). A regression coefficient indicates the importance of independent variables in explaining a dependent variable, where large coefficients are good predictors and small coefficient are week predictors (Hair et al., 2003).

HYPOTHESIS

Ownership is also found to effect firm value in Japanese firms. Hiraki et al. (2003) (analyse Japanese manufacturing companies listed on Tokyo Stock Exchange (TSE) first section over the 1985-1998 period. From their analysis, it was evident that managerial ownership was monotonically and positively related to firm value (Tobin‘s Q). This result is supported by Chen et al., (2003). Their study also took place in Japan where 123 firms from 1987 to 1995 are selected as a sample. At first, they find that at low levels, ownership negatively affects firm value. However, at a high level of ownership, the relationship between the mechanism and firm value turns positive, thereby suggesting a non-monotonic relationship. Yet, the U-shaped result disappears when they include firm fixed effects in the model, thus supporting the previous finding by Hiraki et al., (2003) that a positive and linear relation exists between managerial ownership and firm value. Dividend payout has been the primary puzzle in the economics of corporate finance since the work of Black (1976).

Gugler and Klaus (2003) find a positive relationship between the second largest shareholder and dividend payouts in German firms. Thomsen and Pedersen, (2000), contributed to the literature by examining how dividend and ownership moderates the relationship with firm value. The authors found a negative effect of the level of blockholder ownership on firm value. This effect was at least partly attributable to interaction effects with dividend in that firm value was less negatively affected in European companies with high payout ratios.

Thus, the hypothesis is stated as follow: Correlation: H01= Q has relationship with blockholder ownership. H02= Q has relationship with dividend payout.

177

Regression: H03= Q has significant relationship with blockholder ownership and dividend payout.

FINDINGS

DESCRIPTIVE STATISTICS

TABLE 2: DESCRIPTIVE STATISTICS

Q Mean Std. Error of Mean Median Std. Deviation Variance Skewness Kurtosis Minimum Maximum

2.6588 .04595 2.7369 .61652 .380 -1.424 11.153 -1.42 4.64

chs 30.0804 1.65187 24.4800 22.16212 491.160 .511 -.999 1.16 74.25

dividendpayout .0955 .00735 .0765 .09864 .010 1.732 5.041 .00 .65

Table 2 reports descriptive statistics for sample variables including means, medians, standard deviations, minimum and maximum values. In term of firm value, the mean for Tobin‘s Q is 2.6588. However, the standard deviation for Tobin‘s Q is 0.61652. The minimum value for Tobin‘s Q is negative (i.e. -1.42). This is definitely is not a good sign for GLCs performance even though it does not apply to all samples GLCs. Tobin‘s Q is related to the overall value tagged on the firm by the market which involves among others the current plans and strategies (Kiel and Nicholson, (2003). Beside the market confided on the sample firms to the government may also contribute to the better perception of the market towards the firms. Yet, the market perception towards the sample GLCs is not homogeneous. This can be seen from the difference between the minimum and maximum value of Tobin‘s Q which is quite substantial.

With regards to blockholder ownership in the sample GLCs, second majority of share ownership in most of the sample GLCs is controlled by the blockholders which refers to the outside or institutional shareholders who hold 5 percent of the firms‘ shares, excluding the government. In this study, the mean percentage of blockholder ownership is 30.0804 percent on average, with 1.16 percent as the minimum and 74.25 percent as the maximum.

As GLCs are normally big companies, it is not surprising that the amount of dividend payout is huge, where the maximum is RM 0.65. On average, the GLCs in the sample have dividend payouts worth RM 0.0955. Included in Table 2 are the results of skewness and kurtosis. As a rule of thumb, according to de Vaus (2002), a skewness in the range 0f -1 and +1 indicates a symmetrical or normal 178

distribution. In this study, two variables are found to have non-symmetrical distributions namely Tobin‘s Q and dividend payout.

CORRELATION

TABLE 3: CORRELATIONS

1. Tobin‘s Q

Correlation Sig 2.Blockholder ownership Correlation Sig 3. Dividend payout Correlation Sig * Correlation is significant at the 0.05 level (2-tailed).

1 1

2

.095 .206 .183(*) .014

1 295(**) .000

3

1

Pearson correlation coefficients (PCC) are used in the study to examine the relationship that might exist between variables. From the analysis, Table 3 shows the correlation of the variables (firm value measured by Tobin‘s Q, blockholder ownership and dividend payout). The correlation between dividend payout and Tobin‘s Q is 0.295, implying correlation and significance.The correlation of this dependent variable (firm value) between independent variables (dividend payout) is significant at the 0.05. Therefore, we accept the null hypothesis at 95% confidence level.

REGRESSION ANALYSIS

To test for the hypothesized relationships in this study, OLS regression analysis was used. Basically, there are two hypotheses there are tested:

H03= Q has a significant relationship with blockholder ownership and dividend payout.

TABLE 4: SUMMARY

Model 1

R .188(a)

R Square .035

Adjusted R Square .024

Std. Error of the Estimate .60892

a Predictors: (Constant), dividendpayout, chs b Dependent Variable: Q 179

From Table 4 the coefficient of correlation (R=0.188) shows a relatively low linear correlation between firm value and the independent variables. The value of 0.8 or above is preferred because it indicates a strong relationship between variables. The level adjusted R² is 3.5% of the variance of the dependent variable is explained by the variance of the independent variables.

TABLE 5: ANOVA

Model 1

Sum of Mean Squares df Square F Regression 2.408 2 1.204 3.247 Residual 65.629 177 .371 Total 68.037 179 a Predictors: (Constant), dividendpayout, chs b Dependent Variable: Q

Sig. .041(a)

Based on the Table 5, we can see that the F statistic is 3.247 substantial at a significance level, implying that the null hypothesis that are the regression coefficients are zeros. Therefore, we can say that the null hypothesis is rejected at the 95% level of confidence; there is a significant impact between the dependent variable (firm value) and the independent variable (dividend payout).

TABLE 6 : COEFFICIENTS

Mo del

1

(Constant) chs dividendpayout

Unstandardized Standardized Coefficients Coefficients Std. B Error Beta 2.520 .081 .001 .002 .045 1.063 .483 .170 a Dependent Variable: Q

T B 31.006 .577 2.201

Sig. Std. Error .000 .565 .029

The results also indicate a positive and significant (pRM2001

211 22 15 2 211 8 13 18 44 33 143 30

84.4 8 6 0.8 84.4 3.2 5.2 7.2 17.6 13.2 57.2 12

Based on table 3, male‘s respondent shows more participation in thus study which is 156 respondents which is 62.4% is aware about this scheme. Female respondent (37.6%) is lower which consists of 94 respondents only. Most (40.8%) of the respondents are among 56 and above years old. 28.2% respondents are among 41 to 55 years old. There are 19.2% respondents who were aged between 26 to 40 years old. A respondent in the age range of 18 to 25 years old is only 11.2% which contributes to the lowest age range of respondents. It also indicated that the highest of the respondents are come from Malay people which are 276

consisting of 211 respondents (84.4%). There are 22 (8.8%) Chinese respondents and 15 (6.0%) respondents are Indian people. Other race is the lowest in which consists of 2 (1.2%) respondents only.

It also showed that the respondents are mostly among the Muslims which are 211 respondents with 84.4% compare to the other religion. For non-Muslims, there is 3.2% for the religion of Buddhist with 8 respondent, 5.2% are among the Hindu with 13 respondents and 7.2% is for Christian religions with 18 respondent. Accordingly, it shows that there is 17.6% is for the salary group of below RM1,000, 13.2% is for the salary group of RM1,001 to RM1,500, 57.2% for the salary group of RM1,501 to RM2,000 and 12.0%, which is the lowest is for the salary group of above RM2,001. In other words, the results show that most of respondents had RM1, 501 to RM2, 000 as their monthly income that potentially claimed to be the users for traditional-based pawnshop. The gap is because the cost of living is currently increased, where goods are become less with a RM1.00 due to price pressure.

Model 1

TABLE 4. MODEL SUMMARY. R R Square Adjusted R Square .896

a

.802

Std. Error of the Estimate

.799

.29130

a. Predictors: (Constant), LowIncome, Locality, PriceSystem, CustomerService b. Dependent Variable: CustomerAwareness

TABLE 5. ANOVA. Model 1

Regression Residual

Sum of Squares df 84.438 4 20.790 245

Total

105.228

Mean Square 21.110 .085

F 248.763

Sig. a .000

249

a. Predictors: (Constant), Low Income, Locality, Price System, Customer Service b. Dependent Variable: Customer Awareness

TABLE 6. COEFFICIENTS Model Unstandardized Standardized Coefficients Coefficients B Std. Error Beta 1 (Constant) .099 .207 Pricing System .486 .099 .549 Customer Service .449 .125 .475 Locality .160 .053 .088 Low Income -.118 .078 -.147

277

t .480 4.904 3.588 3.004 -1.520

Sig. .632 .000 .000 .003 .130

Table 4 and 5 indicates whether the proportion of variance explained in the table of model summary is significant or otherwise. Furthermore, it is show whether the overall effect of four independent variables on performance is significant. This overall model explained that of variance in overall performance of Ar-Rahnu Scheme in Sungai Buloh, which has revealed to be statistically significant , F (4, 245) = 248.763, p < 0.001. From the above table, important to be emphasized that the significant (p –value) is 0.000 which is below than 0.05 level. Thus, we can conclude that overall model is significant.

Based on Table 6, it shows which one among the four variable influences most the variance in awareness on Ar-Rahnu Scheme in Sungai Buloh that is to say the most factors. The column Beta shows that the highest value in the beta under column unstandardized coefficients is 0.486 for price system among customer awareness which is significant 0.000 levels. This indicates that pricing system is the most factors that have significant impact toward the awareness among Ar-Rahnu customers in Sungai Buloh, Selangor. Other factors like customer servive and locality also gave impact on the customer awareness toward ArRahnu shceme with the value of Beta is 0.449 significant at 0.000 and 0.160 significant at 0.003, respectively. Only one factor that has no significant impact on the customer awareness, that is low income, it shows that the value of Beta is -0.118 and not significant at level of 0.130. It can be concluded that the pricing system, customer service and locality are the three factors that contributes to the awareness of Ar-Rahnu Scheme in Sungai Buloh. Therefore, hypothesis 1, hypothesis 2 and hypothesis 3 are accepted and hypothesis 4 is rejected.

CONCLUSION

This study develops the theoretical framework, which explain the factor that impact public awareness towards Ar-Rahnu Scheme. From the results shown, management of Ar-Rahnu Scheme and bank that involve in providing this scheme or product can use the results to find a new strategy that can attract public to subscribe or use this Ar-Rahnu Scheme. With this result also, the customer will be more aware of Ar-Rahnu Scheme compare using conventional pawnshop.

In order to introduce Ar-Rahnu Scheme, analysis make from four important factors affecting the acceptance which are pricing system, customer service, locality and low income were use as parameters to identify the most important factor that impact public awareness towards ArRahnu Scheme in Sungai Buloh. These factors were tested using the multiple regressions to find out the main impact of these factors toward customer awareness. The finding concludes that factor that has the higher impact towards the Ar-Rahnu Scheme is pricing system whereby it is clearly shows that customer prefer to use this scheme because of the price system in which the safe-keeping fee imposed by Ar-Rahnu is cheaper than conventional pawnshop. The high interest rates make it difficult for the consumers to reclaim their goods or jewelers. Therefore researcher would like to recommend that, perhaps related parties toward Ar-Rahnu business may produce one policy in order to ensure each Ar-Rahnu shop 278

will impose the safekeeping-fee in which not exceeds the maximum standard as determined in the existence act.

While in thriving the Ar-Rahnu Scheme, there is a need to strength the customer service, were appear to be second impact factors influencing public to aware the Ar-Rahnu Scheme. Indeed, this result offers points for local authority and businesses to consider. Firstly, the transaction doing Ar-Rahnu Scheme should be efficient and fast. Second, it should be free from any issues of discrimination. To be a booming system, the Islamic-based pawnshop needs to be fairly regardless of their race. Lastly, confidential record of the transaction between customer and the business know the record.

This study also use locality as the factor that impact public awareness towards Ar-Rahnu Scheme. The result shows a positive relationship between locality and awareness of ArRahnu Scheme. This measure relatively has a weak influence on acceptance but the researchers believe that if local authorities to set up the business, location information must be met at least people know where it is and it not located in remote areas. In addition, if an individual wants to open an Islamic-based pawn shop, they should open at the place where it is easy to be accessed by customer. Thus, it will lead the public customer more aware with the existing of Ar-Rahnu around them.

REFERENCES

Appannan S. and Doris G. (2011), A Study On Islamic Pawn Broking Awareness and Factors Influencing the Scheme in Sungai Petani, Kedah, 2nd International Conference on Business and Economic Research (2nd Icber 2011) Proceedings. Azila A. R. (2004), Malaysia Practice of Ar Rahnu scheme, International Islamic Conference. Bhatt, P. and Sinnakkannu, J. (2008), Ar-Rahnu (Islamic Pawning Broking) Opportunities and Challenges in Malaysia, 6th International Islamic Finance Conference 2008 Peer Reviewed Paper. Hanudin A., Rosita C. (2011), Determinants for ar-Rahnu usage intentions: An empirical investigation, African Journal of Business Management Vol. 5(20), pp. 8181-8191. Hanudin A., Rosita C., Hazmi D., and Rostinah S., (2007), An Ar-Rahnu Shop Acceptance Model (ARSAM), Labuan e-Journal of Muamalat and Society, Vol. 1, pp. 88 – 101. Ismail, A.G. and Ahmad, N.Z., (1997), Pawnshop as an instrument of microenterprise credit in Malaysia, Journal of Social Economics, Vol. 24(11), pp. 1343-1352. Lao, J.J. (2005), Unexplained pawn pricing behavior: A study of Las Vegas pawnshops. MIT Undergraduate Research Journal, Vol. 12, pp. 45-53. 279

Maamor, S. & Ismail, A. G., (2010), The Efficiency of Ar-rahnu and Its Determinant. Journal of Islamic Economics, Banking and Finance. (Forthcoming, Vol 6, No.1.) Mohammed, N., Daud, N.M.M., & Sanusi, N.A. (2005), Analisis skim ar-Rahnu: Satu kajian perbandingan dengan pajak gadai konvensional. Prosiding Seminar Kewangan dan Ekonomi Islam: Pengukuhan dan Transformasi Ekonomi dan Kewangan Islam, 29-30 Ogos, EssetBangi, Selangor Darul Ehsan, 211-220. Mohammed, N. & Sanusi, N.A., (2007), The Demand of Pawnbroking Services: Evidence from Malaysia, In proceeding of the International Conference on Business and Information 2007, Intercontinental Tokyo Bay Hotel, Tokyo, 10-13 July. Sam, M. F. M., Tahir, M. N. H., & Latif, N. K. A., (2010), The Awareness and The Acceptance of Islamic Pawnshops, International Journal of Research and Reviews in Applied Sciences, Volume 2, Issue 2, February 2010, ISSN: 2076-734X, EISSN: 2076-7366. Sanusi, N.A. & Mohammed, N., (2007), Permintaan Perkhidmatan Pajak Gadai: Perspektif Pengguna. (Demand of Pawn Shop Service: Consumers Perspective), Malaysian Journal of Consumer and Family Economic, Vol. 10, pp. 20-29. Sanusi, N.A., & Johari, M.S. (2006). ―Prestasi perkhidmatan ar-Rahnu: Kajian kes MGIT”. Proceedings of National Seminar in Islamic Banking and Finance: Islamic Wealth Management, Prospects, Issues and Challenges, 29-30 August, Serdang, Selangor Darul Ehsan. Taap, M.A., Chong, S.C., Kumar, M., Fong, T.K., (2011), Measuring service quality of conventional and Islamic banks: a comparative analysis, International Journal of Quality and Reliability Management, Vol. 28(8), pp. 822-840. Zainon (2006), Ar-Rahnu is the First Islamic Pawnbroking in the World, Utusan Malaysia.

280

THE RELATIONSHIP BETWEEN EXCHANGE RATE AND ECONOMIC GROWTH IN MALAYSIA: IDENTIFYING MAJOR CONTRIBUTING FACTORS

Norfhadzilahwati Rahim Universiti Tenaga Nasional, Department Finance & Economics, Muadzam Shah, Pahang, Malaysia [email protected] Tel: 609 – 455 2020 ext 3376 Hamidah Ramlan Universiti Tenaga Nasional, Department Finance & Economics, Muadzam Shah, Pahang, Malaysia [email protected] Tel: 609 – 455 2020 ext 3149

ABSTRACT This study investigates the relationship between the exchange rate and Malaysia‟s economic growth. In particular, the study analyses the relationship between the exchange rate and economic growth. The determinant factors studied are GDP, GNI, Current Account, Malaysian exports and imports for the period 2002 to 2011. Using regression and correlation analysis this paper examines the relationship between the exchange rate and economic growth. Therefore, this study proposes the importance of the exchange rate as a factor to accelerate the economic development of Malaysia. Thus, it must be ensured that the Malaysian economy remains having healthy and sustainable growth to maintain investor confidence. Keywords: Exchange rate, Economic Growth, Regression Analysis, Malaysia. INTRODUCTION

The exchange rate and economic growth have been the subject of many studies for many years from the past to the present. The exchange rate will have an effect on economic growth on such measures as gross domestic product, gross national income, current account, exports and imports. McPherson and Rakovski (2000) stated that determining the impact of exchange rates on the rate of economic growth is difficult because most of the important macroeconomic effects are indirect. The researchers also found that the interaction of the exchange rate (the local price of foreign exchange), inflation (the change in domestic prices), and economic growth (the change in real income) are especially important. Research by Bodnar and Gentry (1993) examined three channels through which exchange rate fluctuations affect firms‘ values, cash or profits. These include their effects on i) Domestic exporters‘ terms of competition with foreign firms. 281

ii) Input Prices. iii) Firms‘ assets denominated in foreign currencies.

The main focus of this paper is on how the exchange rate could have affected the economic growth in Malaysia. Thus, the depreciation or appreciation of exchange rates has some effect on economic growth. Then, from this research we can also find what factors have the greatest affect on economic growth and how does economic growth fluctuate with changes in the exchange rate. Other researchers have indicated that when the exchange rate depreciates it imply causes strong relative-price changes which increase the demand for exports. The increased profitability of domestic producers caused by the depreciation of the exchange rate would lead firms to expand investment in capacity as well as in new plant and equipment (Kannan, 2009).

In this research, we examine the implications of exchange rates towards the various factors on economic growth in Malaysia. The study analyses the relationship of exchange rates and economic growth. The determinant factors studied are GDP, GNI, Current Account, Exports and Imports for the period, 2002 to 2011.

PROJECT OBJECTIVES

The purpose of this research is to examine the relationship between Exchange Rates and Economic Growth in Malaysia. Besides that, the study also measures the major factors that contribute to changes in Exchange Rates.

EXPECTED OUTCOMES

This study enables us to know the relationship between Exchange Rates and Economic Growth in Malaysia. On the other hand, this study also enables investors, researchers and companies to get information about changes in Economic Growth that have an impact on Malaysian to Exchange Rates.

PROJECT BENEFITS

The findings of this paper may serve as useful inputs for researchers by ensuring that the Malaysian economy remains at a level of healthy and sustainable growth to maintain investor confidence in the economy. This project may provide information for investors, researchers and companies towards the importance of exchange rates as a factor to accelerate the economic development of Malaysia. 282

LITERATURE REVIEW

Avellan (2003) found that not only do multiple exchange rates decrease economic growth but also that poor economic performance, liability dollarization, liquidity risk and a high debt service lead countries to segment the foreign exchange market and the result is similar with Alesina et al (1993). The researcher also stated that the countries which are trying to maintain economic activity by segmenting the foreign exchange market, may wind up depressing it instead. Ito et al. (1999), shows the positive relationship between the economic growth rate and changes in the real exchange rate for the APEC countries for the period 1973-95 (except for Chile, where the sample period is 1975-95).

Tarawalie (2010) examines the impact of the real effective exchange rate on economic growth in Sierra Leone. First an analytical framework is developed to identify the determinants of the real effective exchange rate. Using quarterly data and employing recent econometric techniques, the relationship between the real effective exchange rate and economic growth is then investigated. A bivariate Granger causality test was also employed as part of the methodology to examine the causal relationship between the real exchange rate and economic growth. The empirical results suggest that the real effective exchange rate correlates positively with economic growth, with a statistically significant coefficient. The results also indicate that monetary policy is relatively more effective than fiscal policy in the long run, and evidence of the real effective exchange rate causing economic growth was profound. In addition, the results showed that terms of trade, exchange rate devaluation, investment to GDP ratio and an excessive supply of domestic credit were the main determinants of the real exchange raterin Sierra Leone.

The economic research shows that new global patterns of trade have rendered the effects of exchange rates on trade even more complex. Exchange rates play a vital role in a country's level of trade, which is critical to every free market economy in the world. For this reason, exchange rates are among the most watched, analyzed and governmentally manipulated economic measures. A higher exchange rate can be expected to lower the country's balance of trade, while a lower exchange rate would increase it. (Auboin and Ruta, 2011).

One would expect firms in a more open economy to be more sensitive to movements in exchange rates. The studies discussed above focused on big and developed economies, such as the U.S. and Japan. Nydahl (1999) studied firms in a small open economy. He investigated the relationship between stock returns and exchange-rate fluctuations of Swedish firms via regression with a lagged term. About 26% firms in the sample had significant exposure to exchange-rate fluctuations, which is a higher percentage than earlier results for U.S. firms. Meanwhile, he also found the level of foreign or total sales significantly increases exposure and the level that firms engage in hedging activities decreases exposure.

Kogid et al.(2010) indicate that consumption expenditure and exports play an important role in boosting economic growth in Malaysia. The other results show that the effect and role of government expenditure, the exchange rate and foreign direct investment on economic 283

growth may be less important in spurring continuous economic growth and should not be ignored. This research also found that the comparisons with previous studies are mixed and that economic growth is significantly influenced by various factors.

The exchange rate appreciations have historically been associated with expansions in aggregate investment and this effect is due to the increasing share of imported capital goods in total investment. So, when the exchange rates depreciate it will help boost exports through lower relative prices. The researcher also found that it also will have negative consequences with regards to the impact through imported intermediate goods or imported capital goods. (Kannan, 2009)

Eichengreen (2008) suggests that we should think about the real exchange rate as a facilitating condition. Then, it cannot sustain economic growth in and by itself but that an appropriate real exchange rate policy can be an important enabling condition for a country seeking to capitalize on opportunities for growth. In addition, the researcher explained that a relatively undervalued real exchange rate can have costs as well as benefits and that the cost/benefit ratio will tend to rise with the general level of economic and financial development. Using the real exchange rate to provide an incentive to shift resources into manufacturing provides a boost to national income in so far as there are conditions making for higher productivity in manufacturing than in agriculture. Keeping the exchange rate at competitive levels and avoiding excessive volatility are important for economic growth.

Rodrik (2008) shows that undervaluation of the currency (a high real exchange rate) stimulates economic growth. He explains that tradable goods suffer disproportionately from the government or market failures that keep poor countries from converging towards higherincome levels. Then, the researcher also gives some conclusion that real exchange rate depreciations can be good for growth and they have a growth-promoting effect. Koutmos and Martin (2003) analysed exchange rate exposure in nine aggregate sectors of major economies (materials, consumer cyclical, consumer non-cyclical, energy, financial, industrial, technology, utilities and conglomerates) and confirmed the existence of exposure in approximately 40 percent of the country-sector models (Germany, Japan, the United Kingdom, and the United State) .

The researcher found that the relationship between the choice of de facto exchange rate regime and the subsequent economic growth rate for developing Asian and advanced European economies, highlights two interesting regularities. In European countries, the choice of an exchange rate regime does not matter for economic growth although a more flexible exchange regime is weakly associated with a slightly higher growth rate. But in developing and emerging Asian economies the exchange rate regime does matter for economic growth rate but is nonlinear because fixed and managed float regimes are associated with higher growth rates than other regimes that may fall, between or outside of, fixed and managed float regimes in terms of flexibility. Then, the researcher suggest that it does not matter for advanced European economies but developing and emerging Asian economies should pay more attention to their choice of exchange rate regimes, taking into 284

consideration their the level of development, capital market development, capital account and other important factors because not only if but also how the optimal choice of this regime affects an economy‘s growth rate critically depends on the level of development of the economy. (Huang and Malhotra, 2004)

The real exchange rate and real income are not significantly cointegrated in the long run because the exchange rate and income may not drift apart and in the short run their relationship is weak and indirect because in Kenya‘s rate of economic growth has been directly affected by fiscal and monetary policies, the availability of foreign aid and other economic variables, particularly the growth of exports. Together, these factors have tended to sustain a pattern of real exchange rate over-valuation, which has been unfavorable for growth. Then, the improvements in exchange rate management alone are not adequate for the revival of growth in Kenya, but have to be part of a broader program of economic reform. The results also found that the improvement in exchange rate management in Kenya can influence the rate of income growth, but only in the context of a broad-based structural adjustment and reform. (McPherson and Rakovski (2000)

While most theoretical models of open economies rely on a causal relationship between real exchange rates and the current account are limited, if any, contemporary evidence exists on the empirical validity of this relationship. More recently Cline (2003) estimates Japan‘s current account finding that a 1% increase in the yen real exchange rate can affect the current account anywhere between 1.3 to 4.4 billions of dollars. In the same framework a 1% change in the domestic growth rate can affect the current account by 3.4 to 6.3 billions of dollars. Moreover, various analysts have blamed, partially at least, the US current account imbalances on the exchange rate policies of its trading partners (e.g., Bergsten, 2004). Finally, in a recent contribution Obstfeld and Rogoff (2005), in discussing the US current account imbalances suggest that any kind of adjustment requires, as a necessary corollary, sizeable exchange rate shifts. In particular, Obstfeld and Rogoff (2005) develop a three-region economic model to consider the hypothesized reduction in global current account imbalances might impact the major currencies in real terms. Even under relatively benign scenarios of policy actions (letting the Asian exchange rates to float leading to raising U.S. saving) significant exchange rate shifts emerge as a necessary feature of adjustment. For example, their baseline estimate suggests that a halving of the U.S. current account deficit entails nearly a 20% dollar real depreciation against Asian currencies and a slightly smaller depreciation against European currencies. The researchers also found that the above relationship is substantial in size and subject to pronounced non-linear effects. They identify two groups of countries since the abandonment of European national currencies: those with persistent real exchange rate depreciation leading to current account improvement; and those with systematic real appreciation and deteriorating current accounts. (Georgios, 2006)

Aghion et al. (2006) find that countries suffering from real overvaluation experience have slower productivity growth. This effect shrinks in magnitude, as noted above, as countries become financially more developed. While Ghosh et al. (1997) found no relationship between observed exchange rate variability and economic growth for a sample of 136 countries over the period 1960–89, Bailliu et al. (2001) reported a positive association between the degree of exchange rate flexibility and economic growth. That this association is 285

positive rather than negative leads one to suspect that this result reflects the influence of other factors correlated with both exchange rate flexibility and growth: political stability, institutional strength, and financial market development.

Arunachalaramanan and Golait (2011) examine the effect of a revaluation of the Chinese RMB on India‘s bilateral trade balance with China. They find that an appreciation of the RMB against the Rupee would not improve the bilateral trade balance from the Indian perspective. The authors argued that there are two main reasons that explain their result. First, the long-run price-elasticity of demand for Indian goods in China is lower than that for Chinese goods in India.

Product-level analysis has been one feature of the work conducted by Bahmani-Oskoosee and Wang (2007), who examined the impact of exchange rates on trade flows between the United States and its trading partners, notably with China, Japan, Korea (Rep. of), Thailand and other countries. Trade flows were broken down to the individual commodity level. In this work, the use of trade data at the commodity level (two or three-digit industry trade data) permits the identification of industries that have been sensitive to exchange rate changes. The paper studying US-China trade over the period 1978-2002 found that the evolution of the bilateral real exchange rate had an impact on many of the 88 industries tested, although wide differences existed among products. It seems that the appreciation of the dollar against the Yuan decreased US export earnings in 18 industries, while it increased import values in 40 industries. The asymmetrical impact of the exchange rate seems in this case to be attributable to lower price elasticity of Chinese demand to US manufacturing products rather than of US demand to Chinese manufacturing exports.

METHODOLOGY

In this study, there are two main variables, and the proxies that represent the both variables as below: FIGURE 1: RESEARCH FRAMEWORK

Dependent Variables Economic Growth Independent Variables Exchange Rate

    

286

GDP Growth (GDP) GNI Per capita (GNI) Current Account (CA) Export (Ex) Import (Im)

H1: Exchange Rate significantly influences GDP Growth in Malaysia. H2: Exchange Rate significantly influences GNI Per capita in Malaysia. H3: Exchange Rate significantly influences Current Account in Malaysia. H4: Exchange Rate significantly influences the exports of Malaysia. H5: Exchange Rate significantly influences the imports of Malaysia.

EXCHANGE RATE

The Exchange Rate is defined as follows: The price of which the currency of a country can be exchanged for another county‘s currency. Factors that influence exchange rate include interest rate, inflation rate, trade balance, political stability, internal harmony, high degree of transparency in the conduct of leaders and administrators, general state of economy, and quality of governance. (Bisnessdictionary.com)

ECONOMIC GROWTH

The Economic growth variables are defined as follows: 

Gross Domestic Product (GDP) Growth GDP is the total value of all goods and services produced in a certain period after deducting the cost of goods and services used up in the process of production. This value is before deducting allowances for consumption of fixed capital which is the sum of value added of resident producer in producers‘ price plus import duties. (Department of Statistics, Malaysia, 2012)



Gross National Income (GNI) Per capita Gross national income (GNI) is the aggregate value of the balances of gross primary incomes for all sectors; (gross national income is identical to gross national product (GNP) as hitherto understood in national accounts generally). (Department of Statistics, Malaysia, 2012)



Current Account (CA)



The current account (balance of payments) shows details of goods and services, income, and current transfers. (Department of Statistics, Malaysia, 2012) Export (Ex) 287

Exports of goods consist of exports of the following items from residents to nonresidents, generally with a change of ownership being involved: general merchandise, goods for processing, repairs on goods, goods procured in foreign ports by domestic carriers and non-monetary gold. (Department of Statistics, Malaysia, 2012) 

Import (Im) Imports of goods consist of imports of the following items from non-residents to residents, generally with a change of ownership being involved; general merchandise, goods for processing, repairs on goods, goods procured in foreign ports by domestic carriers and non-monetary gold. (Department of Statistics, Malaysia, 2012) SAMPLING

For this selection study, the sample consists of the Exchange Rate, GDP, GNI, Current Account, Malaysian exports and imports in the period 2002 to 2011 on an annual basis. The data came from the Department of Statistics, Malaysia. REGRESSION

Regression equation expresses the linear relationship between two or more variables. The purpose of the regression is to evaluate the impact of the independent variables to the dependent variables. Conducted coefficients at the significance of 5%, reject the null hypothesis (H0) when the p-value0.05. The models are demonstrated as below:

GDP GNI CA Ex Im

= α + β ER + ε = α + β ER + ε = α + β ER + ε = α + β1 ER + ε = α + β1 ER + ε

Where, α ER GDP GNI CA Ex Im ε

= constant value = Exchange Rate = Gross Domestic Product = Gross National Income = Current Account = Export = Import = error

288

CORRELATION

Correlation measures the degree to which two variables are associated with or relate to each other. However, correlation does not provide a test of ‗cause and effect‘. A correlation coefficient can take any value between and including -1 and +1. A value of ‗-1‘ means that the two move in the opposite direction by the exact same magnitude. A correlation coefficient of ‗+1‘ means that the two variables move in the same direction by the exact same amount. These are two extreme cases. In the middle is the case where the correlation coefficient is equal to ‗0‘. In this situation, the two variables move independently from one another.

FINDINGS REGRESSION ANALYSIS

TABLE 1 : EXCHANGE RATE AND ECONOMIC GROWTH REGRESSION RESULTS GDP GNI CA EX IM Model t Sig. t Sig. t Sig. t Sig. t Sig. 1 (Constant) 17.885 .000 16.939 .000 -9.653 .000 15.959 .000 17.992 .000 ER 3.369 .003 2.977 .008 10.506 .000 4.546 .000 3.830 .001 Dependent Variable: GDP, GNI, CA, EX, IM

The regression results in table 1 show that exchange rate has significant positive coefficients with gross domestic product, gross national income, current account, export and import at 5% level of significance. This is defined by saying that all the variables reflect when exchange rate if it fluctuates, either by depreciation or appreciation.

This result is supported by monetary and financial conditions that export dependent sectors in competitive international markets tend to be adversely affected by an exchange rate appreciation. When the ringgit appreciates, firms that rely more on export revenue but source their inputs locally will face a more significant impact on their profit margins. Other than that, the impact on the broad economic sector is either neutral or positive so they were adversely affected. For a highly open economy like Malaysia, with trade in 2010 accounting for 157.8% of GNI, such an outcome is expected. In this regard, the uncertain external environment makes exchange rate volatility unavoidable.i

Therefore, we will accept the alternate hypothesis and reject the null hypothesis because there is significant influence of the exchange rate on the economic growth in Malaysia. 289

TABLE 2 : EXCHANGE RATE AND ECONOMIC GROWTH ANOVA RESULTS Model R-Squared R-Squared Adjusted F-Test Sig.

GDP .387 .353 11.347 .003a

GNI .330 .293 8.865 .008a

CA .860 .852 110.369 .000a

EX .534 .509 20.668 .000a

IM .449 .418 14.668 .001a

Dependent Variable: GDP, GNI, CA, EX, IM

Based on the table 2, the regression on GDP is expressed by the estimated R-Square of 0.387, indicating that 38.7% of changes in GDP were due to changing in the exchange rate and this is reliable. The exchange rate will influence GDP by 38.7%. As a result, GDP is significantly related to the exchange rate.

Then, the regression on GNI shows an estimated R-Square of 0.330, indicating that exchange rate will influence GNI by only 33%. As a result, GNI is significantly related to the exchange rate.

For the result on the Current Account, it indicates that 86% in the Current Account is due to changes in exchange rates and this is reliable. The exchange rate will influence the Current Account very strongly by 86%.

Other than that, the regression on exports shows an estimated R-Square of 0.534, indicating that changes in the exchange rate will influence exports by 53.4%. And, the regression on imports shows an estimated R-Square of 0.449, indicating that changes exchange rate will influence exports by 44.9%.

This results are consistent with other studies which indicate that there is a relationship between the exchange rate and inflation and this is highly complex and involves interactions through a number of transmission channels in the economy, including trade, domestic demand, expectations of households and businesses, financial markets, liquidity and monetary conditions, and the costs of production.ii

Therefore, we accept alternate hypothesis and reject the null hypothesis because there is a significant influence of the exchange rate on the economic growth in Malaysia.

290

CORRELATION ANALYSIS

TABLE 3 : CORRELATION MATRIX ON EXCHANGE RATE AND ECONOMIC GROWTH ER 1

GDP .622** 1

GNI .574** .998** 1

CA .927** .827** .794** 1

ER GDP GNI CA EX IM **. Correlation is significant at the 0.01 level (2-tailed).

EX .731** .983** .972** .889** 1

IM .670** .986** .979** .840** .994** 1

Table 3 shows the relationship between the exchange rate and economic growth such as Gross Domestic Product, Gross National Income, Current Account, and Malaysian exports and imports. From the above analysis it has been found that there are significant relationships between the exchange rate and all variables of economic growth in Malaysia.

The exchange rate is positively correlated with Gross Domestic Product, Gross National Income, Current Account, and Malaysian exports and imports at the 0.01 significance level. This correlation test simply confirms that each variable has correlation between each variable. The result suggests to accept the alternate hypothesis correlation coefficients because there is significant correlation between the variables.

The researchers stated that some prices in the economy can be sticky, and that movements in nominal exchange rates can alter relative prices and affect international trade flows in the short run. (Auboin and Ruta, 2011)

This results comply with other studies that in Malaysia, the impact of exchange rate changes on import prices and subsequently on consumer prices is estimated using monthly observations from July 2005 to mid-20112. Their resulting estimation suggests that exchange rate movements are statistically significant in influencing import prices.iii

CONCLUSION

As a conclusion, the study concludes that there are significantly relationships between the exchange rate and economic growth. Thus, the depreciation and appreciation of exchange rates will have some effect on economic growth. This result is also consistent with other research (Auboin and Ruta, 2011) and indicates that exchange rate changes can have strong effects on the economy. The exchange rate has an effect on the structure of output and 291

investment, lead to inefficient allocation of domestic resources and external trade, influence labour market and prices, and alter external accounts.

This result also shows that there is a significant correlation between all variables. In this case, all variables will effect each other when there are changes among them. This result complies with other research who conclude that economic growth is the result of a variety of influencing factors, which can only be approximated by growth theory. The simple growth models can be extended over time by relaxing the model restrictions and supplementing new variables to give a better explanation of economic growth. (Kogid, Mulok, Beatrice and Mansur, 2010)

To summarize, all the studies mentioned investigated the existence of exchange-rate exposure. Generally, they view the return on the market index as an important explained variable, which stands for the economic situation. One may question the potential correlation between the return on the market index and exchange-rate fluctuations may cause general regression with difficulties to explain the results.

For further studies, the research on the importance of the exchange rate as a factor to accelerate the economic development across ASEAN countries. Thus, from this research we can examine the difference in changes in exchange rate and the effect on economic growth of ASEAN countries.

REFERENCES Abu Tarawalie (2010). ―Real exchange rate behavior and economic growth: evidence from Sierra Leone South African‖, Journal of Economic and Management Sciences, Vol 13, No 1., pp.8-25. Aghion, Philippe, Philippe Bacchetta, Romain R. and Kenneth R. (2006), ―Exchange Rate Volatility and Productivity Growth: The Role of Financial Development,‖ NBER Working Paper, No. 12117 (March). Arunachalaramanan, Shri and Ramesh Golait (2011), ―The Implications of a Renminbi Appreciation on Indian Trade‖, RBI Working Papers Series 2/2011, Reserve Bank of India. Auboin, M. and Ruta, M. (2011). ―The Relationship Between Exchange Rates and International Trade: A Review of Economic Literature‖, World Trade Organization, Economic Research and Statistics Division, Staff Working Paper, ERSD-2011-17. Avellan, L. M. (2003). ―Parallel exchange rates and economic performance in developing countries: is the medicine worse than the disease?‖, University of Maryland, Central Bank of Ecuador and Espol. 292

Bahmani-Oskooee, Mohsen and Yongqing Wang (2007), ―United States-China Trade at the Commodity Level and the Yuan-Dollar Exchange Rate‖, Contemporary Economic Policy, Western Economic Association International 25: 341-361. Bailliu, Jeannine., Robert Lafrance and Jean-Francois Perrault (2001), ―Exchange Rate Regimes and Economic Growth in Emerging Markets,‖ in Revisiting the Case for Flexible Exchange Rates, Proceedings of a Conference of the Bank of Canada, Ottawa: Bank of Canada. Eichengreen, B. (2008). ―The Real Exchange Rate and Economic Growth‖, The International Bank for Reconstruction and Development / The World Bank, 4. Georgios C. and Arghyrou M. G. (2006). ―Real Exchanges Rate and Current Account Imbalances in the Euro-Area‖, University of Essex. Huang, H. and Malhotra, P. (2004). ―Exchange Rate Regimes and Economic Growth: Evidence from Developing Asian and Advanced European Economies‖, Journal of Economic Literature, IMF Working paper series, pp.1-32. Kannan, P. (2009). ―Exchange Rates and Domestic Investment in Malaysia‖, National Economic Advisory Council (NEAC) Paper, No. 6/2/2009. Kogid, M., Mulok, D., Beatrice, L. F. Y. and Mansur, K. (2010). ―Determinant Factors of Economic Growth in Malaysia: Multivariate Cointegration and Causality Analysis‖, European Journal of Economics, Finance and Administrative Sciences, 24, 14502275. Koutmos, G. and Anna D. Martin (2003), Asymmetric exchange rate exposure: theory and evidence, Journal of International Money and Finance 22, pp.365-383. McPherson, M. F. and Rakovski, T. (2000). ―Exchange Rates and Economic Growth in Kenya: An Econometric Analysis‖, African Economic Policy Discussion Paper, 56, 20523-4600. Rodrik, D. (2008). ―The Real Exchange Rate and Economic Growth‖, John F. Kennedy School of Government Harvard University Cambridge, MA 02138. Statistics Division, World Trade Organization, Rue de Lausanne 154, CH 1211 Geneva 21. Takatoshi Ito, Peter I., and Steven S. (1999), ―Changes in Exchange Rates in Rapidly Development Countries: Theory, Practice, and Policy Issues (NBER-EASE volume 7) i

The Impact of Exchange Rate Appreciation on Malaysian Trade, Monetary and Financial Conditions, Annual Report 2010. ii Outlook an policy in 2012, Annual Report 2011. iii Outlook an policy in 2012, Annual Report 2011.

293

AUDIT DELAY AND ACCOUNTABILITY INDEX IN LOCAL AUTHORITIES: CASES FROM KEDAH, PERAK AND KELANTAN

Marziana Mohamad, Wan Mohammad Taufik Wan Abdullah and Mohmad Sakarnor Deris,

College of Business Management and Accounting, Universiti Tenaga Nasional (UNITEN), Malaysia 09 - 455 2020 [email protected] College of Business Management Accounting, Universiti Tenaga Nasioanl (UNITEN), Malaysia 09 - 455 2020 [email protected] College of Business Management and Accounting, Universiti Tenaga Nasional (UNITEN) Malaysia 09 - 4552024 [email protected]

ABSTRACT This paper investigates the determinants of audit delay in Malaysia. The sample comprises three local authorities which are Kedah, Perak and Kelantan during the period 2008 – 2010. The research was conducted based on secondary data which are obtained from the Auditor General Report and Financial Management Performance of the departments or agencies for the respective local authorities in Kedah, Perak and Kelantan. The number of days between the date of the financial statement year end and the date of certificated by the auditor is used to measure the audit delay. The result indicated that the financial management performance of most of the departments or agencies in the sample based on the Accountability Index was at a satisfaction level while most of them did not publish the financial statements on time. However, this study cannot be generalized to other local authorities in Malaysia, since it is meant for Kedah, Perak and Kelantan only.

Keywords: Audit Delay, Accountability Index, Timelines, Local Authorities

INTRODUCTION Good accounting information is usually characterized by qualitative factors such as adequacy, comparability, relevance and reliability in order for the information provided to be useful for decision making by the decision makers which include significant stakeholders. Apart from that, the accounting information should also be seen as being transparent and timely. Transparency is a very important element of financial reporting which might affect investment decisions made by an informed investor. Besides, timeliness of the audited 294

financial reporting is considered to be a critical and important factor affecting the usefulness of information made available to external users (Almosa and Alabas, 2007; Aljifri and Khasharmeh, 2010). Timelines is an important qualitative attribute of financial statement. The issuance of Governmental Accounting Standards Board (GASB)‘s states that for financial reports to be useful, they must be issued soon enough after the reported events to affect decisions.

Timeliness in financial reporting is a significant characteristic of accounting information. Stale information is of little use to decision makers in deciding significant decisions for themselves and the organization. Studies into the timeliness of accounting information have become an important issue now more than ever before as a result of phenomenal changes in both modern technology and business practices worldwide (Errunza and Losq, 1985; OwusuAnsah and Leventis, 2006). Financial reporting should also be seen as a part of the process of accountability whereby the public is informed of significant updated information based on the economic events occurring in the last financial year as promptly as possible. In Malaysia, the process of getting the financial information from any local authority takes time. This is because the users have to wait until the financial accounts are published in the official government gazettes. As a result, there is a possibility of lack of interest in the financial accounts of local authorities as any potential issues fade with the passage of time (Tayib, Coombs and Ameen, 1999). Therefore, local authorities have to take the responsibility to ensure that their financial reports are made available in a timely manner because they are accountable to the public at large. This is very important because it allows the users to evaluate the capability of local authorities in managing their affairs and resources efficiently and effectively.

Public accountability embraces all aspects of government action and direction. In financial management, the most elementary form of public accountability is the requirement that local authorities give an account of their activities to the public and provide justification of what has been done. As is identified in the literature, there has been extensive research concerning the audit delay done in the private sector but very little is known about local authorities especially Malaysian local authorities. Thus, it is our interest to develop a current study concerning the audit delays and accountability index among local authorities in Malaysia. This study enriches the existing literature on Public Sector Accounting studies in Malaysia. The aim of this study is to examine the trend of the accountability index of the local authorities in Malaysia. Meanwhile, this study also aims to investigate the relationship between the audit delays and the accountability index attained by local authorities of the respective states selected in the sample of the study. This study contributes to the Government Audit and Public Sector Accounting literature by looking at the pattern of accountability index attained by the local authorities of the selected states in the sample for the period under study. It provides supporting evidence on whether the financial reports provided by the local authorities to the interested users reflect public accountability upheld by the government.

The remainder of the paper is organized as follows. First, it discusses previous research findings based on a literature review. Next, it describes the research design in conducting the study. It further provides the results of the analysis and discussion. The final section reports conclusions and provides suggestions for future research. 295

LITERATURE REVIEW

Timeliness is an important qualitative attribute of high quality accounting information. The term is vital and may influence whether information is useful to those who read financial statements or otherwise. Its significance has been emphasized in the Statement of Financial Accounting (SFAC 2, FASB 1976, in Delaney et al. 1997). Meanwhile, the Governmental Accounting Standards Board (GASB) identifies timeliness as one of the six qualitative characteristics that financial information is expected to possess if it is to communicate effectively, along with relevance, reliability, understandability, comparability and consistency (Concepts Statement No. 1, Objectives of Financial Reporting). Timely information may be defined as information that is available soon enough after the reported events take place in order to affect decisions or assessments of accountability. In the context of audited annual financial reports, the issue of timeliness centers on the amount of time that elapses between the end of the fiscal year being reported and the date the financial report becomes available to the public.

The provision of timely information in corporate reports assumes greater importance (Wallace, 1993) in emerging economies. This is often attributed to the fact that non-financial statement sources of information such as media releases, news conferences and financial analysts‘ forecasts are not well developed and the regulatory bodies are not as effective as in developed countries. Users of financial information should be able to reach information they need in a timely manner in order that they can make reasonable decisions. Within this context, the timing of information is at least as significant as its content for financial information users. The significance of timely financial reporting to stakeholders cannot be overemphasized. Jaggi and Tsui (1999) noted that stakeholders and investors need timely information for reducing the asymmetric dissemination of financial information and for the growth of investing community as a whole. Specifically, Ismail and Chandler (2003) said that unnecessary delay in releasing financial statements results in greater market inefficiency while Ahmad and Kamarudin (2001) also noted that it reduces the relevance of the documents and their information content. In addition, the study of Ashton, Willingham and Elliott (1987) on timeliness of corporate reporting suggested that audit delay increases uncertainty associated with investment decisions. However, the substantial body of literature regarding ‗audit timing‘ or the period between the end of the fiscal year and the date of the audit report, that has developed in the corporate sector Ashton et al. (1987) is not matched in the government sector. The available studies of governments have settled on three groups of influencing factors; competency of the government‘s financial management, competency of the auditor, and characteristics and complexity of the government (Dwyer and Wilson, 1989). More recently, Merritt Research Services (2010) published averages for issuers of municipal bonds in its database, covering the financial years 2007-2009. Average audit timing for general purpose governments (168 days to 178 days) was found to be about a month or more longer than for many types of special-purpose governments (ranging from 110 days for toll roads to 152 days for school districts and airports). Little, if any, literature existed until recently on the topic of how users of governmental financial information view timeliness. In a broader study of bond analyst 296

views on disclosure, Robbins and Simonsen (2010) asked survey respondents to label audited financial statements received within three months, six months, nine months, and so on as completely useful, somewhat useful, less useful, or no longer useful. They found that 70 percent of respondents considered audited financial statements received within 9 months to be completely useful. On the other hand, 89 percent identified as no longer useful audited financial statements received after 10 months. In another study, Pane and Jensen (2002) found that the mean audit delay is 100 days for 410 municipalities in the U.S. Additionally, McLelland and Giroux (2000) found that the mean audit delay is 124 days among the 209 U.S. cities councils. In Malaysia, the Local Government Act 1976 requires the audited accounts with the auditor‘s observations be published in the government gazette as stated in Section 60(4) (Tayib et al., 1999). The study noted that financial reports for local authorities appear in the government gazette after approximately one year after the end of the financial year to which they relate. There are also cases where such information has taken up to six years to actually appear in the government gazette. Tayib et al. (1999) also dictated that taxpayers in local authorities with high arrears are almost unanimous in their desire to know more about their council‘s financial affairs. The study also indicated that the taxpayers are more willing to pay their local taxes more quickly if such information were to be made readily available. However, this willingness is reduced due to the long time taken for the financial information to be published in the government gazette.

Theoretical Arguments and Hypotheses Development

This study proposes that audit delay is affected by two factors as shown in the model as follows: Audit delay =

Accountability Index

To promote the timeliness of financial reporting in government local authorities, municipalities and local authorities receive benefits from participation in the Government Finance Officers Association (GFOA)‘s Certificate of Achievement for Excellence in Financial Reporting Award. The GFOA awards the Certificate of Achievement for Excellence in a Financial Reporting Award. This award was previously entitled the ‗Certificate of Conformance Award‘ (Dwyer and Wilson, 1989). The award is designed to give recognition on excellent achievement in the process of preparing financial reporting. In Malaysia, to ensure the level of compliance with the stipulated legislation as laid down in the federal Constitution and Audit Act 1957 and related procedures, the Audit General Department executes an audit on the effectiveness of financial management of the Government States Department and Agencies. They are finally ranked based on the accountability index according to their achievements which are based on the overall total marks obtained. Previous studies found that audit delay is reduced for cities that had received 297

excellent achievement in the process of financial management (Dwyer and Wilson, 1989; Johnson, 1998). Based on these arguments, the following hypothesis is developed: H1: There is a significant relationship between the accountability index and audit delay.

Municipal Characteristics Prior research has reported inconsistent results regarding how a city‘s size influences audit delay. McLelland and Giroux (2000) indicated a positive relationship exists between audit delays and population. On the other hand, other studies by Dwyer and Wilson (1989) and Johnson (1996) did not find a significant relationship between size and audit delay. This study likewise examines the city size as larger cities could experience longer audit delays due to increased levels of financial activity. However, larger cities could also experience shorter delays due to increased financial control and scrutiny from stakeholders and constituents. Thus, the second hypothesis is developed as follows: H2: There is a significance relationship between city size and audit delays.

RESEARCH METHODOLOGY

Purposive sampling was employed in this study which covered the local authorities in Kedah, Kelantan and Perak. The reason why those local authorities are chosen is because they are reported as those who have performed badly in submitting the statement of accounts to the Auditor General Office as reported in the Auditor General Report 2008. The data for the fouryear period from 2008 until 2010 were collected from the State Auditor General Report. There are four operational variables which comprise one dependent variable and two independent variables as described in Table 1. TABLE 1: VARIABLES MEASUREMENT Variables Dependent Variable Audit Delay  Account preparation delay 

Date of certification

Independent Variables Accountability Index

City Size

Measurement

The length of time taken to prepare financial statements The length of time taken from the submission date to the date of the audit certificate

The mean of accountability index achieved by the states The size of population for each state 298

Data Analysis and Interpretations

Descriptive Analysis

Table 2 shows the descriptive statistics results for selected samples from annual reports for the period of 2008 until 2010 in Kedah, Perak and Kelantan. In the Audit General Report, the National Audit Department has carried out financial management performance of the departments or agencies based on the Accountability Index for auditing the financial statements that had been submitted. The Accountability Index is based on the four levels which are excellent (4 star), good (3 star), satisfactory (2 star) and unsatisfactory (1 star). From the results, the highest mean of the accountability index for the three states is good performance which is in Kelantan (3.21), followed by Kedah (3.17) and lastly, Perak (3.05).

Based on the results, in the 2008 Audit General Report it indicated that the highest percentage which received the excellent award in their accountability index was Kedah which was 14.29 percent and this was followed by Perak which was 7.69 percent. Then in 2009, Kelantan showed the highest percentage which was14 percent followed by Kedah with 11.11 percent which received the excellent award in their financial performance. However, Perak received an unsatisfactory accountability index (2.70 percent) for the Perak Council of Islamic Religion and Malays Customs. For 2010, the highest percentage received the excellent award in their financial management performance was Kedah (23.53 percent), followed by Kelantan (21 percent) and Perak (5.26 percent). Therefore, the trend of the accountability index for the three years from 2008 until 2010, the highest average mean was Perak (3.00) which was good, followed by Kedah (2.96) and last was Kelantan (2.90) which means a satisfactory level. TABLE 2: SUMMARIES OF ACCOUNTABILITY INDEX Kedah ( N=9) Perak (N=10) Kelantan (N=6) Years Accountability Index Percentage Mean Percentage Mean Percentage Mean 2008

2009

2010

Excellent Good Satisfactory

14.29% 57.14% 28.57%

Excellent Good Satisfactory Unsatisfactory

11.11% 63.89% 25% -

Excellent Good Satisfactory Average

23.53% 70.59% 5.88%

2.86

7.69% 53.85% 38.46%

2.86

2.70% 83.79% 10.81% 2.70%

3.17

5.26% 78.95% 15.79%

2.96 299

3.08

36% 64%

2.36

2.86

14% 86% -

3.14

3.05

21% 79% -

3.21

3.00

2.90

Correlation Analysis

Table 3 depicts the correlation between accounts preparation delay, date of certificate with city size and the accountability index. This analysis is to measure the second objective which is to investigate the significant relationship between all dependent variables with the independent variable. Based on the results for the state of Kedah, in terms of accounts preparation delay it only had one significant relationship with the mean accountability index which had a p-value of less than the 0.01 level (correlation value -1.000). In terms of the date of receiving the certificate also it had one significant relationship with the city size which was a p-value of 0.003 (correlation value .866).

For Perak state, the results indicated that there was only one significant relationship between accounts preparation delay with city size and the accountability index. The p value was less than 0.01 which was (correlation value -.0845) a significant relationship with city size and (correlation value 0.845) for the mean of accountability index. The p value was 0.002 which is less than the p value at the 0.01 level. However, Kelantan state reported that all the dependent variables had a significant relationship with the independent variable. In terms of accounts preparation delay, this had a significant relationship with city size (correlation value -.866) and the mean accountability index (correlation value -.866) that the p value is less than 0.05 which is p value 0.026. Then in terms of the date of certification it was reported that there was a significant relationship with city size and the accountability index (correlation value -.866) that the p value was less than 0.05. Therefore, the alternate hypotheses H1 and H2 were accepted. This result is consistent with previous studies, for example McLelland and Giroux (2000) who found a positive relationship between audit delay and population. However, Dwyer and Wilson (1989) and Johnson (1996) did not find a significant relationship between size and audit delay.

According to Dyer and McHugh (1975) the management of larger companies has greater incentives to reduce both audit delay and reporting delay since they are closely monitored by investors, trade unions and regulatory agencies. Besides, professional city managers have greater incentive to signal competent professional performance by producing a timely audited financial report (Dwyer and Wilson, 1989).

300

TABLE 3: CORRELATION ANALYSIS Dependent variable Kedah

Independent Variable City Size Accountability Index

Accounts Preparation Delay: Correlation Coefficient Sig. (2-tailed) N Date of Certificate: Correlation Coefficient Sig. (2-tailed) N City Size: Correlation Coefficient Sig. (2-tailed) N Perak Accounts Preparation Delay: Correlation Coefficient Sig. (2-tailed) N

Date of Certificate: Correlation Coefficient Sig. (2-tailed) N City Size: Correlation Coefficient Sig. (2-tailed) N Kelantan Accounts Preparation Delay: Correlation Coefficient Sig. (2-tailed) N Date of Certificate: Correlation Coefficient Sig. (2-tailed) N Date of Certificate: Correlation Coefficient Sig. (2-tailed) N

*Correlation is significant at the 0.05 level (2-tailed) **Correlation is significant at the 0.01 level (2-tailed)

301

.000 1.000 9

-1.000** . 9

.866** .003 9

-.500 .170 9

1.000 . 9

.000 1.000 9

City Size

Accountability Index

-.845** .002 10

.845** .002 10

. . 10

. . 10

1.000 . 10

-.429 .217 10

City Size

Accountability Index

-.866* .026 6

-.866* .026 6

-.866* .026 6

-.866* .026 6

1.000 . 6

1.000** . 6

CONCLUSION

The results provide important new insights into the determinants of municipal audit delays. Supposedly the issuance of the timely financial reporting is significant to municipalities, and so the government must identify and comprehend what factors they should consider to control in minimizing audit delays. The findings suggest that audit delays are significantly associated with city size and the accountability index achieved by the respective states in the sample. However, we would also like to highlight that the characteristics that influence audit delays may be different between the samples of states selected to be the sample of the study and other non-selected states. Overall, the findings provide beneficial information to the governments regarding the potential determinants of audit delays. Future research may consider which parties are liable for the audit delay, either on the hands of the preparers or auditors. REFERENCES Ahmad, R. and Kamarudin, A. (2001). Audit delay and timeliness of corporate reporting: Malaysian evidence, available from internet at www.hicbusiness,orgbiz2003proceedings/Khairul%20Kamarudin5202.pdf [Retrieved on 31 March 2012) Aljifri, K. and Khasharmeh H. (2010). The timeliness of annual reports in Bahrain and United Arab Emirates: An Empirical Comparative Study. The International Jornal of Business and Finance Research, 4(1), 51-71 Almosa, A.S. and Alabas, M. (2007). Audit Delay: Evidence from listed joint stock companies in Saudi Arabia. King Khalid University, Abha, Saudi Arabia, available from internet at www.kku.sa/conference/SSEFP/Presentations [Retrieved on 15 April 2012] Ashton, R.H., Willingham, J.J. and Elliot, R.K. (1987). An empirical analysis of audit delay. Journal of Accounting Research, 25(2), 275-292. Delaney, P.R., Epstein, J.R., Adler, J.R. and Foran, M.F. (1997). GAAP 1997: Interpretation and application of generally accepted accounting principles, USA, John Wiley and Sons Inc. . Dyer IV, J.C. and McHugh, A.J. (1975). The timeliness of the Australia annual report. Journal of Accounting Research, (Autumn), 204 220 Dwyer, P.D., Wilson, E.R., (1989). An Empirical investigation of factors affecting the timeliness of reporting by municipalities, Journal of Accounting and Public Policy 8(1), 2955 Errunza, V. R. and Losq, E. (1985). The behavior of stock prices on LDC markets. Journal of Banking and Finance, 9(4), 561-575

302

Ismail, K., Nor, I. and Chandler, R. (2003). The timeliness of quarterly financial reports of companies in Malaysia, available from internet at http://papers.ssrn.com/sol.3/papers.cfm?abstract_id=415047 [Retrieved on 19 April 2012] Jaggi, b. and Tsui, J. (1999). Determinants of audit report lag: Further evidence from Hong Kong. Accounting and Business Research, 30(1), 17-28. Johnson, L.E., (1996). Factors influencing municipal audit delay. Accounting Enquiries, 6(1), 121 – 148 Johnson, L.E., (1998). Further evidence on the determinants of local government audit delay. Journal of Public Budgeting, Acounting and Financial Management,10, 375-397.

McLelland, A.J., Giroux, G., (2000). An empirical analysis of auditor report timing by large municipalities, Journal of Accounting and Public Policy, 19(3), 263 – 281 Merritt Research Services (2010). Just how slowly do municipal bond annual audit reports waddle in after the close of the fiscal year? Available from internet at http://www.merrittresearch.com/about/research_team/anselm.htm [Retrieved on 20 April 2012] Owusu-Ansah, S. and Leventis, S. (2006). Timeliness of corporate financial reporting in Greece. European Accounting Review, 15(2), 273-287. Payne, J.L., and Jensen, K.L. (2002). An examination of municipal audit delay. Journal of Accounting and Public Policy, 21, 1-29. Robbins, M. and Simonsen, W.(2010), The quality and relevance of municipal disclosure : What bond analysts think. Municipal Finance Journal, 31. 1-20. Tayib, M., Coombs, H.M., Ameen, J.R.M. (1999). Financial Reporting by Malaysian Local Authorities: A Study of the Needs and Requirements of the Users of Local Authority Financial Accounts. The International Journal of public Sector Management, 12. Wallace, R.S.O. (1993). Development of accounting standards for developing and newly industrialized countries. Research in Accounting in Emerging Economies, 131-156.

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SMALL BUSINESS TAXPAYERS’ BEHAVIOUR, BELIEF AND PERCEPTION OF FAIRNESS: EVIDENCE FROM TAX PRACTITIONERS IN KUANTAN, PAHANG

Marziana Mohamad, Abdul Hadi Abdul Aziz, Muhammad Amir Zainuddin, Sheikh Mohd Iszuan Sheikh Mohd Zurid

College of Business Management and Accounting, Universiti Tenaga Nasional (UNITEN), Malaysia 09 - 455 2020 [email protected] College of Business Management Accounting, Universiti Tenaga Nasioanl (UNITEN), Malaysia [email protected] College of Business Management and Accounting, Universiti Tenaga Nasional (UNITEN), Malaysia [email protected] College of Business Management and Accounting, Universiti Tenaga Nasional (UNITEN), Malaysia [email protected]

ABSTRACT This paper investigates using a survey among tax practitioners, perspective of small business taxpayers‟ behavior, beliefs and perceptions of fairness towards tax compliance. First, it analyses the level of behavior, beliefs and perceptions of fairness among small business taxpayers. Second, it investigates the relationship between behavior, beliefs and fairness on its tax compliance. 200 questionnaires were distributed to tax practitioners in Kuantan, Pahang, only 113 agreed to participate (56.5 percent response rate). Descriptive statistics indicated that the level of taxpayers‟ behavior, beliefs and perceptions of fairness was at an average level of their tax compliance. Furthermore, correlation analysis also indicated that there are relationships between taxpayers‟ behavior, beliefs and fairness among small business taxpayers with tax compliance.

Keywords: Behavior , Belief, Perception of Fairness, Tax Practitioners.

INTRODUCTION Small and Medium Enterprise (SME) are subjected to income tax payable either as individuals or as corporate taxpayers depending on the business establishment. The taxation of both individuals and corporate businesses is governed by the Income Tax Act (ITA) (Malaysia) 1967. Business taxpayers are required by law to file an annual tax return correctly (Section 77 and 77A; ITA 1967), to keep sufficient records and documentations (Section 82 and 82A; ITA 1967) and to observe other tax related requirements (Section 107, 107B, 107C 304

and 108; ITA 1967). Compliance to the regulatory requirements is mandatory in nature, placing an enormous burden and cost upon the business sectors. Largely, international experiences often indicate the difficulties faced by the SMEs in managing government laws and regulations (Fernandez & Lynne (1998).

The issues faced by SME business in relation to regulatory costs are worldwide phenomena almost identical in the US, UK, Australia and New Zealand. These include a lack of understanding of the regulatory requirement, frequent changes in regulations and high fixed costs (Francis et al. (2003). The previous study done by Hanefah et al. (2001) indicated that the Malaysian business tax system appears to be becoming increasingly more complex, either due to major amendments being made to existing laws or a new assessment system. Therefore, tax complexity could be measured via tax compliance costs (Simon et al. (1998); Pope, (1992).

For the majority of taxpayers, tax practitioners were their sole source of support. The tax practitioners are people that taxpayers can trust to keep them on the right side of the law. Having the honest tax practitioners or adviser was the highest priority. Tan (1999) was reported that New Zealand suggesting the core important contribution is the tax practitioners make to taxpayers as a whole to given them confidence that their tax matters are under control and their tax paying behavior is lawful. Collins et al., (1990) and Hite and McGill (1992) indicated similar conclusions in their work in United States.

SME businesses interested in tax minimization were open to have tax practitioners who understand both low and high risk strategies. In addition, the emergency of two distinct factors represents tax minimization with conflict avoidance on one hand and tax minimizing with high risk on the other (Yuka and Valeria (2003). Marshall et al., (1998) conclude that diversity occurs among Australian tax practitioners in the ethical stances that they take. Tax practitioners appear to be successful in marketing their skills in a way that is suitable to the clients‘ needs or the other hand.

This study analyses the level of behavior, beliefs and perceptions of fairness among SME business taxpayers. Besides that, this study also investigates the relationship between behavior, beliefs and fairness on its tax compliance from the perspective of tax practitioners. LITERATURE REVIEW

Tax Behavior, Belief and Perception of Fairness Behavior is related with the observable human behavior. The Organization for Economic CoOperation and Development (OECD) (2010) organized a forum on tax administration for SMEs in understanding and influencing taxpayers‘ compliance. The behavior of the taxpayers is as a result of his or her personal norms and experiences related to a specific context which are social, economic, and environmental and society. Allingham and Sandmo (1972) indicated that people are behaving in an economically rational way. The compliant and non 305

compliant behavior is the results of a cost benefit calculation. People comply when the costs of evasion outweigh the benefits of evasion and do not comply when the balance tips with the other side. The opportunity for tax evasion or compliance has also a great impact on taxpayers‘ behavior. In terms of keeping evasion in check, strong empirical support can be found for limiting the opportunity that potential tax evaders have for avoiding paying tax. Braithwaite (2008) reported that a third party has also been shown to improve compliance, lending credibility to enforcement capacity in the process. Previous researchers found that a broader behavioral perspective has identified a large number of factors and drives that are associated with tax compliance. According to Umashanker Trivedi et al., (2005), attitudes relate to one‘s own personal views about the behavior. Based on the previous literatures, the present study is trying to test the following hypotheses: H1: There is a significant relationship between behaviors of SME business and tax compliance

Belief is referred to the personal statement based on assumed personal knowledge or facts such as tax rates are high or tax agents are essential to ensure correct lodgment. Based on the theory of reasoned action (TRA), attitudes are believed to have a direct effect on behavioral intention. Ajzen and Fishbein (1980) defined attitude as the degree to which an individual has a good or poor evaluation of a particular behavior. Attitudes are influenced by a belief on an outcome in which it uses degrees to measure the outcomes evaluation. Belief is underlined by subjective norms which refer to a normative belief. A normative belief is influenced by one‘s belief toward a referent or a referent group. In a study by Erten (2002), the behavior of the individual within the society is under the influence of defined factors, originating from certain reasons and emerging in a planned way.

The higher rates of tax compliance were found to be associated with the higher ethical attitudes (Chan et al.., 2000; Kasipillai et al. 2003). Henderson and Kaplan (2005) reported that the relationship between taxpayers‘ ethical beliefs and their tax compliance decisions is not simply direct and one dimensional. Besides that, having to pay high taxes and the belief that others are also not complying with tax obligations are also being perceived as reasons why taxpayers would not be likely to exercise tax compliance. The taxpayers who believe that most referents with whom he or she is associated are motivated to comply if they think they should not perform the behavior that will be perceived as social pressure to avoid performing that behavior. Halizah et al., (2011) reported that the general subjective norm is determined by the perceived expectation of specific referent individuals or groups to comply with all expectations. Therefore, the second hypotheses as follows: H2: There is a significant relationship between beliefs of SME business and tax compliance

Blissenden (2002) said that procedural fairness entails that administrations follow particular processes in ensuring that their decision making process is fair. Importantly, authorities should treat SME taxpayers in a fair and respectful manner when undertaking such 306

procedures, particularly when the taxpayers are committed to pay their tax.. Murphy (2004) reported that the reasons for taxpayers to abide by or disobey institutional decisions have been prominent in psychological research. The taxpayers‘ are willing to comply if they are treated in a respectful and fair manner by the authorities. Wenzel (2003) identified three different areas of fairness in relation to tax compliance. They are distributive justice, procedural justice and retributive justice. Tax procedures are neutral and are consistently applied to all and this will have a favorable impact on the perceptions of fairness by the taxpayers. Taxpayers who perceive unfair treatment from the tax authorities will decrease their level of compliance (Tan, (1998); Sheffrin & Triet, (1992); Spicer & Becker, (1980). Cristensen et al., (1994) indicated that fairness is difficult to define because of four problems which are that it is multidimensional, it can be defined at the individual level or for society at large, fairness is intertwined with complexity and lack of fairness may be perceived as justification for or a cause of noncompliance. Therefore, the third hypotheses as follows: H3: There is a significant relationship between perception of fairness of SME business and tax compliance

Tax Compliance and Tax Knowledge Previous researches indicate that tax knowledge is essential in order to increase the level of tax compliance (Richardson, (2006); Kirchler et al., (2008). Hence, it is very important to have knowledgeable and competent taxpayers. Park & Hyun (2003), suggest that tax education is one of the effective tools to induce taxpayers to comply more. In other words, taxpayers are more willing to comply if they understand the basic concept of taxation. For example, the level of tax compliance in Japan is high. The main reason for the high tax compliance in Japan is because of the efforts made by the Japanese National Tax Administration (NTA). The Self Assessment System was introduced in 1947 and plays an important role in the taxation learning process to taxpayers. To promote the principles of voluntary compliance, the Japanese tax authorities performed activities such as public relations, tax education, tax consultation, guidance and examination (Rani, (2005).In addition, tax knowledge will also reduce the potential for evasion. In a cross country study by Richardson (2006) towards 45 countries in the world, he found that education in general has a negative relationship with tax evasion, where the tendency to evade tax reduces with the level of education.

However, it is still questionable whether this general level of education will increase tax compliance. This is because in a study by Loo and Ho (2005) toward a group of salaried individuals in Melaka, Malaysia, they found that the taxpayers‘ competency level is quite low even though most of them have tertiary education. This is an alarming situation because it might impact on their readiness to exercise appropriate compliance under the new self assessment system (SAS). In a study by Junainah (2002) towards the implementation of SAS among individual taxpayers in Kota Kinabalu, Malaysia, she also finds that most of the taxpayers were unwilling to participate in SAS because of the burden that they have to face, especially in terms of completing atax return and calculating income tax payable. They were comfortable with the simplification of the formal system. In his book entitled ―Malaysian Taxation under Self Assessment‖ Kasipillai (2007) emphasizes that knowledge about tax law 307

is assumed to be of importance for preference and to determine the acceptance of the Self Assessment System (SAS).

RESEARCH METHODOLOGY

Data were collected from respondents consisting of tax practitioners in Kuantan, Pahang who are doing the tax audit and tax compliance for SME business. The list of tax practitioners‘ officers was provided by the Inland Revenue Board (IRB) in Kuantan, Pahang. This research has been carried out through questionnaires. According to Sekaran (2003), a questionnaires survey is a formulated written set of questions to which respondents‘ records their answers, usually from clearly defined alternatives. 200 questionnaires were distributed to tax practitioners, but only 113 agreed to participate (56.6 percent respond rate).

There are four operational variables which comprise one dependent variable and three independent variables as shown in Table 1: TABLE 1: VARIABLES MEASUREMENTS Variables Dependent Variable Tax Compliance  Evidence from Tax Practitioners Independent Variable Behavior Belief Tax Fairness

Measurement

The level of tax compliance

The level of tax related of behavior The level of tax related of belief The level of tax related of fairness

RESULTS AND DISCUSSION

Frequency Analysis Table 2 presents the total numbers of respondents of tax practitioners in Kuantan, Pahang. In terms of gender, most of the respondents were female which was 79 percent (n=89) followed by male which were 21 percent (n=24). Then, in terms of ethnicity Malays were 84 percent (n=95), followed by Chinese 14 percent (n=16) and Indian 2 percent (n=2).

308

2.1: Gender Male Female

TABLE 2: RESPONDENT PROFILES Frequency 24 89

2.2 Races Malay Chinese Indian Total

95 16 2 113

Percent 21 79

84 14 2 100

Descriptive Analysis Table 3 presents the level of behavior, beliefs and tax fairness among the SME taxpayers. Out of 29 questions we found that 7 questions have the highest level of behavior, beliefs and tax fairness among the SME businesses who answered ―agree‖. In term of the level of behavior, the highest mean was 3.42 which was ―My client should inform and declare their actual income received from all sources to the IRB or tax practitioners”, followed by “My client are afraid of tax audits and prosecution” which was 3.13. The third highest mean was “To enable a decrease in tax liability, my client required my firm to share knowledge with them” which was 3.07. In terms of level of beliefs, the first question shows the highest mean in answering ―agree‖ which was “My client believes that by joining training courses offered by professional bodies is a good idea”(3.13). Then the second answer was ―My client believes that my firm is helpful in assessing their organization‘s tax risk” (3.09) followed by ―My client believes that specific advice offered by any organization external auditor is important” (3.07). In terms of the level of tax fairness, only one question showed the highest mean of agreement which was ―For the SME business, I think that the income tax system is fair and reasonable‖ (3.05).

TABLE 3: SUMMARIES THE LEVEL OF BEHAVIOR, BELIEF AND TAX FAIRNESS

Factors

1 2 3 4

Behavior My client should inform and declare their actual income recieved from all sources to the IRB or tax practionners. My clients are afraid of tax audits and prosecution. To enables a decrease in tax liability, my client required my firm to share knowledge with them. My client would not feel guilty if they excluded some of their income when completing the tax return. 309

Mean

Std. Deviation

3.42

0.637

3.13

0.657

3.07

0.437

2.35

0.766

Since the suporting documents do not need to be sent to the 5 IRB, my client has opportunity to manipulate the figure in the tax return. It is ethically wrong if my client excludes small amount of 6 income when completing the tax return. Tax returns take too much effort, so my client put it off 7 unless there is an incentive. My client operational decision makers are required to 8 consider the tax effects of their decisions My client organization possesses sufficient expertise to 9 share knowledge with my firm Overall my client organizations gives an appropriate level 10 of attention to taxation matters

2.32

0.749

2.95

0.843

2.51

0.695

2.94

0.419

2.86

0.526

2.97

0.542

3.13

0.590

3.09

0.400

3.07

0.437

2.42

0.638

2.26

0.654

2.97

0.558

2.46

0.668

2.44

0.801

2.88

0.578

2.97

0.525

3.05

0.497

2.96

0.516

2.66

0.591

2.51

0.568

Belief My client believes that by joining training courses offered by professional bodies is a good course My client believes that my firm is helpful in assessing their 2 organizations tax risk My client believes that a specific advice offered by any 3 organization external auditor is important My client believe the tax authority has limited capability to 4 investigate all income reported to them. My client believes that the probabilities of being detected 5 by the tax authority for not declaring the exact income that they receive are low. By paying right amount of income tax, my clients believe 6 that other people especially the poor will get the benefit. My clients believe that the penalty is lower than their tax 7 saving due to not comply with tax laws. My clients believe preparing an income tax return is a low 8 priority in their business nature. My client feel that tax is an obligation and believing in no 9 corruption. My client believe that it is important for my firm to 10 participate in their business meetings, forums and boards. 1

1 2 3 4

Fairness For the SME business, I think that the income tax system is fair and reasonable The benefits my clients receive from the government in exchange for their income-tax payments are reasonable. Current tax laws require my client to pay more than their fair share of income taxes. Compared to the amount paid by bigger firm or company my client pay more than their fair share of income taxes. 310

5 6 7 8 9

A ‗fair‘ tax rate means it should be the same for everyone. High-income company or firm has a greater ability to pay income taxes, so it is fair that they should pay higher rate of tax than low-income tax earners. My client think that special provisions in the income tax law apply only to a few people are unfair. It is fair that high-income firm pay proportionately more tax than low-income firm. Generally my clients feel that the income tax is a fair tax.

2.56

0.777

2.92

0.703

2.60

0.750

2.96

0.441

2.89

0.469

Correlation Analysis Table 4 depicts the correlation between the level of behavior, beliefs and tax fairness with tax compliance. Based on the results from the respondents all independent variables have a significant relationship with tax compliance. First, in terms of the level of behavior, it has a significant relationship with tax compliance which had a p value less than 0.01 (correlation value -0.428). It shows that the evidence from the tax practitioners regarding the behavior of SME business is valuable. This is consistent with previous studies, for example Braithwaite (2008). Therefore, the alternate hypothesis (H1) is accepted.

Second, in terms of the level of beliefs also showed a significant relationship with tax compliance which had a p value less than 0.01 (correlation value -0.393). Third, in terms of the level of tax fairness also reported that it had a significant relationship with tax compliance which was a p value less than 0.001 (correlation value -0.424). The result showed that the higher rates of tax compliance were found to be associated with higher ethical attitudes (Chan et al., (2000); Kasipillai et al. (2003). Therefore, taxpayers‘ perception of the tax system was important because fairness and belief of the tax system would instill compliant behavior among SME taxpayers. Therefore, the alternate hypothesis (H2) and (H3) is accepted.

311

TABLE 4: SPEARMAN’S RHO CORRELATIONS Mean Behavior

Mean Belief

Mean Tax Compliance Correlation -.428** -.393** Coefficient Sig. (2-tailed) 0.00 0.00 N 113 113 Mean Behavior Correlation 1.000 .663** Coefficient Sig. (2-tailed) 0.00 N 113 113 Mean Belief Correlation .663** 1.000 Coefficient Sig. (2-tailed) 0.00 N 113 113 Mean Fairness Correlation .627** .667** Coefficient Sig. (2-tailed) 0.00 0.00 N 113 113 **Correlation is significant at the 0.01 level (2-tailed)

Mean Fairness

Mean Tax Compliance

-.424**

1.000

0.00 113

113

.627**

-428**

0.00 113

0.00 113

.667**

-.393**

0.00 113

0.00 113

1.000

-.424**

113

0.00 113

RECOMMENDATIONS AND CONCLUSION

This study analyzes the level of behavior, beliefs and tax fairness among the SME business based on the perceptions of the tax practitioners. The perceptions of the tax practitioners is needed and the results indicate that they play an important role to provide the understanding of tax related behavior, beliefs and tax fairness among the SME businesses. For the majority of SME taxpayers were using the tax practitioners in calculating their tax returns and submitting them to the IRB by the due date.

Based on Section 77 of the ITA 1967, among the responsibilities of the taxpayers are to give full information of their taxable incomes, to submit their returns on time, to maintain proper records and to pay the accurate amount of tax. From the analysis conducted, it shows that all the SME taxpayers agreed that they should inform and declare their actual income received from all sources to the IRB. The tax practitioners were helpful to them in assessing their organization tax risk and believed the programs organized by the professional bodies were good and valuable. Based on the correlation analysis, all of the independent variables which

312

were behavior, beliefs and tax fairness had a significant relationship with tax compliance. Therefore, all the hypotheses were accepted.

This study, however, cannot be generalized to all SME taxpayers, since it was only conducted to the clients of tax practitioners in Kuantan, Pahang. Besides that, the questions of the level of behavior, beliefs and tax fairness were also restricted to evidence from tax practitioners only. In addition, the level of fairness was difficult to define because four problems which are multidimensional, it can be defined at the individual level or for society at large, fairness is intertwined with complexity and lack of fairness may be perceived as justification or a cause of noncompliance (Christensen et al., (1994).

REFERENCES Allingham, M.G., and Sandmo, A. (1972). Income Tax Evasion: A Theoretical Analysis. Journal of Public Economics, 1, 323-338 Braithwaite, V. (2008). Tax Evasion. Handbook on Crime and Public Policy, Oxford: Oxford University Press. Christensen, F., Saleem, K., and Panikkos, P. (1994). Tax Regulation and Small Business in the USA, UK, Australia and New Zealand. International Small Business Journal, 21(1): 93115. De Vaus, D. (2002). Analyzing Social Science Data (1st ed). London: Sage Publication Ltd. Fernandez, P and Oats,L. (1998). The Small Business under a Goods and Services Tax Regime, In Tax Administration facing the challenges of the future, edited by Evans, C and Greenbaum, A, 159-176. NWS: Prospect. (PUB-CBS-SBL-SA-04740 B2 entered)

Furnham, A. and Arfyle, M. (1998). The Psychology of money. London. Routledge (FA) Hite, P.A., and McGill, G. (1992). An Exanimation of Taxpayers Preference for Aggressive Tax Advice, National Tax Journal, 45, 389-403 Income Tax Act (ITA) (Malaysia) 1967 Junainah, J. (2002). Sistem Tafsiran Sendiri: Satu Kajian Kes Tanggapan Pembayar Cukai Individu di Kota Kinabalu. Tesis Sarjana, UKM. Kasipillai, J. (2007). Malaysian Taxation under Self Assessment System. 2nd Edition. Kuala Lumpur: McGraw Hill Kasipillai, J., Noraza, M.U., and Zaimah, Z.A. (2003). How do Moral Values Influence Tax Compliance Behaviour? Finding from a Survey, The Charted Secretary Malaysia, June: 1015.

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Kirchler,, E., Hoelzl, E., and Wahl., (2008). Enforced versus voluntary tax compliance: the ―slippery slope‖ framework. Journal of Economic Psychology 29, 210-225 Loo, E.C., and Ho, J.K.,( 2005). Competency of Malaysian Salaried Individuals in Relation to Tax Compliance under Self Assessment. http://www.austlii.edu.au/au/journals/eJTR/2005 Retrieved 4 February, 2012. Marshall, R.L.,Armstrong, R.W., and Smith, M. (1998). The Ethical Environment of Tax Practitioners: Western Australian Evidence, Journal of Business Ethics, 17, 1265-1279 Organization for Economic Co-Operation and Development (OECD) (2010), Center for Tax Policy and Administration (CTPA): Understanding and Influencing Taxpayers Compliance. Ott, R.L. and Donnelly, D.P. (1999). Practitioners perceptions of the important of specific corporate tax knowledge for the new hires working in tax. Journal of Accounting Education, 17, 35-50. Park, C.G. Hyun, J.K. (2003). Examination the determinants of tax compliance by empirical data: A case of Korea. Journal of Policy Modeling, 25, 673-684 Rani, J. S. (2005). SAS for Individuals: Preparing for effective management of tax matters. PricewaterhouseCoopers International Limited. http://www.alltheweb.com Retrieved 4 February, 2012. Richardson, G., (2006). Determinants of Tax Evasion: A Cross Country Investigation. Journal of International Accounting, Auditing & Taxation 15 . 150-169 Sekaran, U. (2003). Research Methods for Business: A Skill Building Approach, New York: John Wiley & Sons Spicer, M.W., and Lundsedt, S.B. (1976). Audit Probabilities and Tax Evasion Decision: An Empirical Approach. Journal of Economic Psychology, 2, 241-245 Tan, L.M. (1999). Taxpayers Preference for Type of Advice from Tax Practitioner: A Preliminary Examination, Journal of Economic Psychology, 20, 431-447

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STUDENTS’ JUDGMENT ON THE ETHICALITY IN EARNINGS MANAGEMENT Nurul Nadiah Ahmad College of Business Management and Accounting Universiti Tenaga Nasional, Malaysia [email protected]

Suraya Ahmad Faculty of Accounting Universiti Teknologi Mara,Malaysia [email protected]

ABSTRACT The ethical issue on earning management has been debated for a long time in the accounting profession. This paper investigates the ethical perception of Malaysian‟s future accountants on several of the earnings management judgments. 328 responses from 400 questionnaires distributed were received. The respondents are Bachelor of Accounting students in several public and private universities in Malaysia, who are exposed to all financial accounting subjects and an ethics course during their study at university. There was a statistically significant difference in accounting earnings management and operating earnings management (p 40years old

Frequency 141 43 36 16 3

Percentage 59.0 18.0 15.1 6.7 1.3

Gender

Male Female

77 162

32.2 67.8

Academic Background

Economics Management Engineering Business Mathematics Science Other Academic Business executive Planner Engineer Manager Builder Consultant Other

52 31 53 33 11 21 38 97 18 5 18 3 1 3 94

21.8 13.0 22.2 13.8 4.6 8.8 15.9 40.6 7.5 2.1 7.5 1.3 0.4 1.3 39.3

< 3 years 3-5 years 6-10 years >10 years Full time Part time

73 36 95 35 107 132

22.4 33.4 33.2 11 44.8 55.2

Structure of programme

Full research Research and coursework Full coursework

33 108 98

13.8 45.2 41.0

Suitable time for class

Weekend Evening Office hours RM20,000

145 73 21 69 102 66 2

60.7 30.5 8.8 28.9 42.7 27.6 0.8

North South East West Sabah & Serawak Self Loan Scholarship Company EPF

45 42 81 60 11 104 70 50 14 1

18.8 17.6 33.9 25.1 4.6 43.5 29.3 20.9 5.9 0.4

Occupation

Working experience

Mode of programme

Fee

Location of programme

Main financing

Most of the respondents, chose part time programme 55.2% and 60.7% preferred having class during weekend. Meanwhile, 45.2% chose research and coursework. In order to determine the correlation between intention to choose the MSC programme and demographic factors, the data were analysis by using SPSS. 394

RELIABILITY AND VALIDITY OF THE INSTRUMENT

Coefficient alpha was used to estimate the degree of reliability with estimates that can be range anywhere between 0 to 1.0. The closer the coefficient to 1.0, the stronger the linear relationship of the items being correlated and the higher the internal consistency. Table 2 shows the reliability coefficients of intention to choose the MSC programme with coefficient of 0.767 confident level consistent with the argument that the scale is reliable if alpha value is 7.0 and above (Hair, 2006). TABLE 2 : RELIABILITY TEST Variable

No. of Item

Cronbach's Alpha

Intention to choose MSC

7

0.767

ANALYSIS OF VARIANCE This analysis was measured using independent sample t-test for measurement of differences mean score between two independent groups. Meanwhile ANOVA was conducted to determine the significant difference between more than two independent groups. The result in Table 3 indicates that there are differences in gender, mode of programme and structure of programme (significant at 95% confident level), for other demographic factors, there are no significant differences between groups. TABLE 3: RESULTS OF ANALYSIS OF VARIANCE (ANOVA)

Variable

Awareness on Energy Programme

Age

15-20 years; mean=24.0437;F=0.864

Gender

Male; mean=24.45; F=6.534**

Mode of programme

Part time; mean =24.77; F=4.496**

Structure of programme

Full research; mean=26.9; F=4.300**

Suitable time for class

Office hours; mean= 25.19; F=1.815

Location of programme

North; mean =24.667; F=0.631

Fee

RM10,001-RM15,000; mean=24.31; F=0.685

***significant at 0.01 ** Significant at 0.05 *Significant ant 0.10

395

CORRELATION ANALYSIS Correlation was conducted to determine which demographics characteristics have significant relationship with intention to choose the MSC programme . The results reported in Table 4 indicated that there is a correlation between intention to choose MSC programme with preferred mode and Structure of programme at 5 percent confident level.

TABLE 4 : CORRELATION ANALYSIS Intention

Intention

1

Preferred mode

0.154* 0.017 -0.061 0.345 0.129* 0.047

gender Structure of programme

Preferred Gender mode

Structure of programme

1 -0.081 0.215 0.009 0.884

1 0.035 0.58

1

*. Correlation is significant at the 0.05 level (2-tailed).

CONCLUSION

There is a rapidly growing demand for energy expertise in the areas of energy economics, management and policy worldwide due to the changes in energy industry. The aim of this paper wasb to investigate the relevancy of Master of Science in Sustainable Energy Management (M.Sc Sustainable Energy Management) programme and seek opinion from potential candidates for the programme selected from public and private universities and employees (employees in academic sectors, energy companies) through questionnaire survey. Correlation method was employed and the data analysis was conducted by using SPSS. The result showed that there was a correlation between intention to choose MSC programme with preferred mode and Structure of programme. This finding suggested that establishing a M.Sc Sustainable Energy Management is a strategic move for UNITEN to be an institution for postgraduate degree of choice. There is a great confidence that the programme will be successful because of a number of reasons namely trhe programme is tailored to the contemporary market demand, able to cater post-graduate education in energy and energy management in Malaysia, many industrial linkages set up to provide students more enriching industrial experience especially in relation to energy related uses and technology and finally UNITEN has top class facilities which include comfortable accommodation, well equipped library, modern lecture halls and Wi-Fi internet broadband access.

396

REFERENCES Bungartz, H.J., (2003), Computational Science and Engineering : A new Master‘s degree program at the Technische University Munchen, Future Bungartz, H-J., (2003). Computational science and engineering: a new master‟s program at the Technische Universitat Munchen. Future Generation Computer System, ,V.19 (9), 1267-1274. Cakembergh_Mas, A., Paris, J. and Trepanier, M., (2010), Strategic simulation of the management in a Kraft mill, Energy . Conservation and Management,. 51, pp. 988-997. Corbo , P., Corcione, F.E., Migliardini, F. and Veneri, O., (2006), Energy management in fuel cell power trains, Energy Conservation and Management 47, Pp.3255-3271. Gordic, D., Babic, M., Jovicic, N., Sustersic, V., Koncalovic, D. and Jelic, D., (2010), Development of Energy management system- A case study of a Serbian car manufacturer, Energy Conservation and Management, 51, Pp.2783-2790. Haux,R.,and Schmidt, (2002),, Master of Science Program in Health Information Management at Heidelberg/Heilbronn: a Health care oriented approach to medical informatics. International Journal of Medical Informatics, 65, Pp. 31-39. Jaspers, M.V.M., and Hasman, A., (2007), The new set-up of the medical informatics Master of Science Program at the University of Amsterdam. International Journal of Medical Informatics. 76S, Pp. S369-S376.. Kannan, R. and Boie,W.(2003), Energy Management Practices in an SME- A case study of a bakery in Germany, Energy Conversion and Management ,44, Pp.945-959. Sarimveis, H.K., Angelou, A.S., Retsina, T.R., Rutherford, S.R. and Bafas, G.V., (2003),Optimal Energy Management in Pulp and Paper Mills, Energy Conversion and Management, 44,Pp.1707-1718. Zia ,H. and Devadas, V. (2007), Energy Management in Lucknow City, Energy Policy, 35, Pp.4847-4868.

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CAUSALITY OF MACROECONOMIC VARIABLES IMPACTING THE STOCK MARKET INDEX: TIME SERIES APPROACH IN AMMAN STOCK EXCHANGE

Hussain Ali Bekhet Graduate Business School, College of Graduate Studies Universiti Tenaga Nasional (UNITEN), Malaysia [email protected]; [email protected] Ali Matar PhD Student, Graduate Business School College of Graduate Studies Universiti Tenaga Nasional (UNITEN), Malaysia [email protected], [email protected]

ABSTRACT

The current paper examines the relationship between the macroeconomic factors and the general stock price index in Amman Financial Market (AFM) for the 1978-2010 period. The paper used the application of the Autoregressive Distributed Lags (ARDL) approach combined with CUSUM and CUSUMQ tests to show the stability of that relationship. The yearly stock prices index of all companies listed in ASE during the study period, as well as the central bank of Jordan statistical data were used. The main objective of the study is analyzing the short or long-term equilibrium relationship between the SPI and the selective macroeconomic variables. The current paper is important for all stockholders, policy makers, all kinds of investors, corporations and other financial market participants. The result suggests an existence of long-term equilibrium relationship among SPI and the selected macroeconomic variables.

Keywords: Autoregressive Distributed Lags (ARDL); Amman Stock Exchange (ASE); Macroeconomic variables; Stock Price Index (SPI), Jordan.

398

INTRODUCTION

Several studies have examined the link between stock market and the state of the economy. Also, there is extensive discussion in the finance literature that emerging and developed financial markets may be able to promote economic growth. The results have shown a positive correlation between the economic growth and the financial development. Thus, if the economy is performing well, the stock market is likely to do the same returns (Kirman, 1992; De Gregorio & Guidotti, 1995). Although most of the studies were carried out in developed countries, only a limited number of studies were conducted in developing countries. Previous studies have devoted to corroborate the impact of macroeconomic variables on the financial market (for example, see Fama & Shwert, 1977; Chen & Ross, 1986). Many studies confirmed long-term equilibrium relationship between stock prices and relevant macroeconomic variables (Hussain, 2011; Rangel, 2011; Diamandis & Drakos, 2011; Gosnell & Nejadmalayeri, 2010; Nidhiprabho 2010; Ghosh, 2009; Rahman et al. 2009; Apergis & Miller, 2009; Abugri, 2008; Al-Sharkas, 2004; Kim et al. 2004; Maysami, 2004; Maghyereh, 2002; Omran & Pointon, 2001; and Kearney, 2000). Besides, most of these studies were take place in developed countries, we are trying to assess do emerging markets respond to the changes in macroeconomic variables? According to Abugri, (2008), emerging market stock price indices have characterized as having higher volatility than prices in the more developed markets. So, do the macroeconomic variables causes the volatility or structural breaks of emerging markets stock index? This paper aims to evaluate the macroeconomic variables impact on the stock price index in one of the emerging markets, Amman Stock Exchange (ASE). The ASE a well established, small, emerging open market, providing a showcase for other emerging markets in the world. The study adopt one of the contemporaneous time series analysis techniques, autoregressive distributed lag (ARDL) model developed by by Pesaran & Pesaran, (1997) and Pesaran et al. (2001). ARDL approach has become a popular and standard technique for examining cointegration among financial variables for evaluations. The study applies it to analyze the relationship between stock price index (SPI) and relevant macroeconomic variables namely, industrial production (IP), discount rate (DR), exchange rate (EX), inflation represented by consumer price index (CPI), and money supply (M2). Since this study adopts small sample size, employing ARDL approach in ASE will provides more suitable framework than the standard conventional co-integration models. As well known the financial markets represented by its price index, swings and sensitive to several countless causes, the study try to answer if there is any relationship between SPI and the selective variables. However, find out how long the Jordan economy needs to be in equilibrium manner, by examines if there is any significant short or long- run relationship among the economic activity represented by macroeconomic variables and the SPI. Because the macroeconomic variables are important in the economic growth, this study will highlight its impact on the Jordanian financial market to fill this gap in the literature since the most studies were taken in developed markets. The ASE becomes one of the most important 399

markets in the Middle East because of the different developments, innovations and rules done by sequential governments. Also, this study is important for different parties and for different reasons. It is of concern to policy makers, domestic, foreign investors, corporations and other financial market participants with some evidence on the investment opportunities. They are interested in the volatility of stock prices because it means profits or losses. The study aims to realize the following objectives: Give knowledge of the most important variables affecting the SPI and cause sharp fluctuations since the ASE beginning in 1978; guide the investors in making their trading decisions; ensure if it is possible the ASE respond to macroeconomic variables similarly with developed markets; and to discover which variables are more effective on SPI. The structure of this paper is as follows: The next section sheds light on Jordan economy and the ASE; section 3 exhibits the literature review; section 4 provides data sources and sample; section 5 illustrates methodology; section 6 reports the empirical results. Conclusions, limitation and managerial implications are presented in the last section.

AN OVERVIEW OF THE JORDAN ECONOMY In the past decades, Jordanian economy subjected to several political and conflicts occur in the Middle East such as gulf war1991, and Iraqi war 2003. These issues caused massive resource shortages. First, Jordan economy suffered from the 1990-91Gulf War, the Gulf countries council decided to limit economic relations by declined their workers recruitment, oil supplements, traditional export markets, and large foreign aid revenues. The Jordanian community in the Gulf then reinvested in their homeland in the form of real estate and luxury stores. However, Jordan‘s favorable trade relations with Iraq had ended and years of heavily discounted and even free oil stopped. Foreign aid from the United States and the Arabian Gulf slowed down significantly. International Monetary fund estimate that Jordan‘s GDP declined 15-20% in 1991, making Jordan a main victim after Kuwait and Iraqi themselves, of the Gulf war unemployment near 25% (Park & Agtmael, 1994). Second, the 2003 Iraq War sent 750 thousand mostly wealthy Iraqis into Jordan attracted by the kingdom free market policies and political stability. As Jordan‘s economy one of the smallest in the Middle East, with inadequate supplies of oil, water, and other natural resources, the government's heavy reliance on foreign aid. Other economic challenges for the government include high rates of unemployment, poverty, inflation, and a large budget deficit. Since 1999 Jordan has implemented significant economic reformations, such as privatizing state-owned companies, opening the trade regime, and eliminating most fuel subsidies, which in the past few years have spurred economic growth by attracting foreign investment and creating some jobs. The Government approved two subsidiary budgets in 2010, but sweeping tax cuts planned for 2010 did not happen because of Amman's need for extra revenue to cover excess spending. The budget deficit is likely to remain high, at 5-6% of GDP, and Jordan likely will continue to depend heavily on foreign aid to finance the deficit (http://www.indexmundi.com).

400

In 2008, the Real GDP growth was strong, the inflation, which had climbed sharply due to the swell in world food and fuel prices. However, economic activity expects to slow in 2009, which may reflect the much weaker global and regional outlook. Managing the prospective slowdown while guarding against vulnerabilities especially the large current account deficit is the key near term challenge (IMF Country Report No. 09/159, May 2009, p5). During 2000–2009 Jordanian economy has slowed largely due to the global and regional downturn. The annual real GDP growth averaged about 6%, supported by performing favorable external conditions and economic policies. It was consistent with the global economic slowdown, in 2009 growth fell sharply, and economic activity expects to rise modestly (IMF Country Report No. 10/297, September 2010, p4). In 2010 the Jordanian economy showed strong signs of economic recovery after surpassing the adverse impacts of the global financial and economic crisis. These increases were direct result of the measures and actions on the monetary and banking level adopted by the Central Bank of Jordan (CBJ) (CBJ / Annual Reports 2009 & 2010). FIGURE 1: REAL GDP INDEX OF THE JORDAN ECONOMY FOR THE 1965-2011PERIOD

Source: World Bank.Org, April (2012).

Figure (1) represents the growth rate of Jordanian GDP which was 7.9 percent for the 19652011 period. Also, it shows a gradually upward trend over the targeted period. Despite of the global financial crisis, and other several events during this study period, Jordanian GDP rate reached recently $28.4 billion in 2011. The ASE was established in March 1999 as a non profit, private institution with administrative and financial autonomy. It is authorized to role as an exchange for trading securities. The exchange is governed by a seven-member board of directors. A chief executive officer oversees day-to-day responsibilities and reports to the board. Jordan classified as an emerging market. However, it is consider now as frontier market according to S&P Country Classification in June 2011(see https://www.sp-indexdata.com). The ASE membership is consisting of Jordan's 68 brokerage firms, 248 companies traded on ASE until February 2012. Performing ASE in the years 2009, 2010 and 2011 was 401

exceptional. The trading value of ASE that ended the trading transactions for 2009, 2010, 2011 was JD9.7, JD6.7, and JD2.9 billion respectively. In 2010 five new companies were listed at the ASE raising the number of listed companies to 277, then decline to 247 companies at the end of 2011. Further, the market capitalization of listed shares at the ASE stands at JD21.9 billion, making up 122.7% of the GDP. The number of traded shares witnessed an increase during 2010 reaching 7 billion shares, traded through 1.9 million transactions, compared with 6 billion shares traded during 2009. The share turnover ratio also increased to reach 102.2% in 2010, compared with 91.3% in 2009 (http://www.ase.com.jo/). Figure (2) shows the trading movements of the ASE for the study period.

FIGURE 2: VALUE TRADED OF ASE, FOR THE 1978-2011 PERIOD

Source: ASE.com.jo. March (2012)

Also, Figure (2) shows differences in the pattern of trading between 1978 and 2011. Trading started at JD5,62 million in 1978, rising gradually to reach the first peak in 2005 with a value of JD16,88 billion then dropped dramatically in 2006 and 2007 to JD14,21; JD 12,35 billions respectively. Then it climbed back to reach the second peak with a value of JD 20,32 billion in 2008, only to drop again to JD 6,69 billion in 2010 and 181,1million at the end of 2011 (www.ase.com.jo/en/trading-value-ase). Figure (3) shows the ASE stock price index weighted by free float shares closed at 1995 points in 2011. A decrease of 15.9% compared with closing 2010 which stood at 2374 points with a decrease of 6.3% when compared with closing shares that stood at 2534 points at the end of 2009. The growth rate for the ASE price index weighted by free float was 6.9% during the 1978-2011 period. One of the features of Free Float Index is to give better reflection for the changes of stocks prices in the market by doesn‘t bias to the companies that have large market capitalization. This provides diversification in the index sample by giving better chances to small and medium companies to reflect the index.

402

FIGURE 3: ASE GENERAL FREE FLOAT PRICE INDEX FOR THE 1978-2010 PERIOD.

Source: ASE.com.jo. March (2012)

Foreign direct investments as market capitalization rose to 51.3% in 2011 compared with 49.6% in 2010, 48.9% in 2009, and 49.2% in 2008. Despite, the net non-Jordanian investments in the ASE witnessed sharp decline by JD14.6 million for the year 2010, compared with a decline of only JD3.8 million for 2009, it has increased by JD78.6 million during the year 2011 (http://www.ase.com.jo/).

LITERATURE REVIEW

Over the recent few years the relationship between stock price index and macroeconomic variables has been extensively researched in developed countries (see, Rahman et al., 2009; Rangel, 2011). Yet, there seems to be no consensus about the relationship in developing countries. Several studies employed the time series to examine the relationship between stock market index and its determinants variables. Some studies are based on VAR model to examine this relationship (see, Abugri, 2008; Rahman et al. 2009; Nidhiprabha, 2010), while other studies applied both VAR & VECM models (Al-Sharkas, 2004). However, GARCH model has been applied into many studies (see Hussain, 2011; Rangel, 2011; and Kim, 2002). Besides, VECM model was utilized by Maysami, (2004), the ARDL model employed by Ghosh, (2009). Kearney (2000) analyzed the causes and transmission of stock market volatility. He used monthly returns and four macroeconomic variables in five countries, namely, France, Britain, Germany, US, and Japan during the 1973-1994 period. The results suggested that world equity market volatility mostly caused by volatility in the US-Japan markets and transferred to European markets. Further, changes in volatility of inflation are associated with changes in the opposite side in stock market volatility in all markets. Omran & Pointon (2001) examined the impact of the inflation rate on performing the Egyptian stock market by using error

403

correction (ECM). The result pointed out there is a negative relationship between inflation and market liquidity and activity. Kim (2002) explored the impact of the major stock markets (UK, US and Japan) and domestic US macroeconomic news on Australia‘s financial markets. He applied a bivariate GJR-GARCH model on daily closing price index from the Sydney futures exchange. The results signalled that Some Australian and US macroeconomic news has a significant effect on the first and second moments of Australian financial markets. Maghyereh (2002) examined the long-term relationship between the Jordanian stock prices and selected macroeconomic variables. He applied a VAR model on monthly time series data during the 1987-2000 period. The result found that macroeconomic variables are reflected in stock prices in Jordan, and the stock price index is co-integrated with a set of macroeconomic variables, which provide a direct long-run equilibrium relation with the stock price index. Besides, Al-Sharkas (2004) examined the impact of selected macroeconomic variables on Amman Stock Exchange (ASE). He used the VECM and the VAR models. The data consists of 92 quarterly observations for each variable, for the 1980-2003 period. The results showed the stock prices and macroeconomic variables have a long-term equilibrium. Kim et al. (2004) found out the impact of macroeconomic variables news announcement on the risk and return of US financial market. They employed the GARCH model on daily returns data during the 1986-1998. Their results suggested that balance of trade news have the greatest impact on the foreign exchange market. In the bond market, news related to the internal economy was generally found to be important while for the US stock market, producer and consumer price information was significant. Also, financial market volatility increased in response to some classes of announcement and fallen for others. Maysami (2004) employed the VECM model on the monthly Singapore stock market index (STI) for the 1989-2001 period. He tested the co-integration and the long-term relationship between selected macroeconomics variables and the STI. The results have shown a long-term relationship between stock market index and changes in the short and long-term interest rates, price levels, industrial production, exchange rate and money supply. Abugri (2008) used VAR model to test whether change in key macroeconomic indicators (interest rates, exchange rates, industrial production and money supply) in four Latin American countries ( Argentina, Chile, Brazil, and Mexico) had significantly explain market returns. His results suggested the global factors are consistently significant in explaining returns of all countries above. To finds out a long-run equilibrium among quantity of crude oil import, income and price of the imported crude in India. Ghosh (2009) applied the ARDL model with annual data, on quantity and price of imported crude oil for the 1970–1971 and 2005–2006 periods. The result showed the long term income elasticity of imported crude oil in India is 1.97, and there exists a unidirectional long run causality running from economic growth to crude oil import. Rahman et al. (2009) applied VAR and VECM models to explore the interactions between selected macroeconomic variables (money supply, interest rate, exchange rate, reserves and industrial production index) and stock price index in Malaysia. Their results showed that all six variables contribute significantly to the co-integrating relationship and the Malaysian 404

stock market is sensitive to changes in the macroeconomic variables. Apergis & Miller (2009) examined how shocks that characterize the endogenous character of oil price; affect the stock market returns in a sample of eight countries. They used also VECM-VAR model, during the 1981 to 2007 period. Their results showed that several oil-market shocks play a significant role in explaining the adjustments in stock-market returns. A VAR model has been tested by Gosnell & Nejadmalayeri (2010) to discover if macroeconomic announcements affect the Fama-French market, size, and momentum reason and book-to-market risk reasons. The result suggested that Inflation, employment, consumption and business have a significant impact on risk reason volatilities. However, they found that industrial production and GDP influence only the momentum reason and inflation. Nidhiprabha (2010) used the same model to research Thailand‘s macroeconomic policy responses to the global financial crisis in 2009. He found that fiscal policy is relatively less effective than monetary policy. Tax decline is more powerful in stimulating output than government spending. Preserving undervalued exchange rates does not create the output expansion effect. A study by Hussain (2011) researched the volatility and return response of US and European equity indices to monetary policy with macroeconomics news announcement. He used GARCH (1, 1) model during the 2000-2008 period. His results suggested that monetary policy decisions give immediate and significant influence on stock index returns and volatilities in both the US and European markets. Besides, Rangel (2011) used the same model to examine the effect of macroeconomic releases on stock market volatility, during the 1992-2008 period. He suggested that inflation shocks show significant effects, while monetary policy and employment shocks reveal only short effects. Also, the jump intensity, responds asymmetrically to macroeconomic shocks, that gives evidence in explaining jump dynamics, and improving volatility forecasts on event days is provided. By applied the VECM model Diamandis & Drakos (2011) analyzed the short and long run relationship between stock prices and exchange rate of four Latin America countries namely (Brazil, Chile, Argentina and Mexico) during the 1980-2009 period. Their result suggested that stock and foreign exchange markets in these economies are positively related and the U.S. stock market acts as a channel for these links. Based on the study‘s objectives, orientations and the literature review the following hypotheses can be expressed: H1: There is a significant short-run relationship among selected macroeconomic variables with stock prices, based on the time series techniques, in the ASE. H2: There is a significant long-run relationship among selected macroeconomic variables and stock prices, based on the time series techniques, in the ASE.

MODEL SPECIFICATION AND VARIABLES Franses, (1998) noted that since financial time series data reflected the result of trading among buyers and sellers. For example stock markets, various sources of news and other exogenous economic events, it may have an impact on the time series pattern of asset prices. 405

To perform diagnostic data testing of white noise and all descriptive statistics, some variables have been transformed into natural logarithmic (ln) such as (M2, IP, EX, and DR). Further, to standardize the unit of variables by using SPSS (19) and E-views (7) packages. Equation (1) represents SPI as a function of all variables which will use in this study. SPIt = γ0 + γ1lnM 2 + γ2lnEX t + γ3CPIt + γ4lnIPt + γ5lnDRt + εt

(1)

Where: SPI: stock price index a measure of the performance of underlying stocks, changes in the index reflect changes in the value of the stocks over the time; γ0 : Constant term; γ1 … γ5 : are the coefficients of the model; εt : is error term. (CPI): Consumer Price Index is a measure of the inflation rate for the consumers in Jordan; it is a rise in the general prices level of goods and services in an economy over time. When the general price level rises, each unit of currency buys fewer goods and services. Consequently, inflation also reflects a decreasing in the purchasing power of money, the annualized percentage change in a general price index (normally the Consumer Price Index) over time. According to previous studies, there is a strong negative relationship between the inflation and the stock prices (Rangel, 2011). (M2): Money Supply is the broad amount of money available in an economy usually including currency in circulation and demand deposits. We assume that M2 has positive effects on stock price through its effects on inflation confusions. (IP): Industrial Production is an index measuring the real economic activity, includes manufacturing, mining, utilities and the energy sector in Jordan. Since IP gives a signal of economic growth we hypothesized there is a positive relationship between IP and Stock price, similar to studies by Maysami, (2004). (EX): Exchange Rate represent the exchange rate of Jordan Dinar and US Dollar ($/JD). It is known in economics the EX depends on trade balance and international trading, that is determined by the size of import and export in the economy. The relation between the exchange rate and stock price is positive (Abugri, 2008; Maysami, 2004). (DR) Discount Rate is an interest rate of central bank charges depository institutions that borrow reserves from it. It used to represent the monetary policy, because the time series data of interest rate in the CBJ forms several variables. For example Jensen & Johnson, (1995) was choose DR while Chen, (2007) considered an increase in DR as a restrictive monetary policy with negative relation to stock prices.

METHODOLOGY There were several studies used Engle and Granger (1987) and Johansen Juselius (1991) techniques to determine the co-integration between macroeconomic variables and stock price index (SPI). These techniques need all the variables (regressors) in the system must be of 406

equal order of integration. Recently, a contemporaneous model has developed to introduce a surrogate co-integration technique known as the Autoregressive Distributed Lag (ARDL) bound test (Pesaran & Shin, 1996; Pesaran & Pesaran, 1997; Pesaran & Smith, 1998; and Pesaran et al. 2001). This technique has a many advantages over the previous co-integration techniques. First, the ARDL model considered more proper than the Johansen– Juselius & Engle Granger multivariate approach for testing the co-integration among variables in small sample size (Ghatak & Siddiki, 2001), while the Johansen co-integration techniques needs large data samples for validity. Second, it is not necessarily to examine the non stationary property and order of integration. This means that we can apply ARDL whether underlying regressors are purely I(0) or purely I(1), while other co-integration techniques require all the regressors to be integrated of the same order (Pesaran & Shin, 1999; Pesaran et al., 2001). Third, the ARDL application allows the may have different optimal lags, while it is impossible with conventional co-integration procedures (Ozturk & Acaravci, 2011). Finally, the ARDL model has become increasingly popular in recent years (Jayaraman & Choong, 2009). Based on these advantages of ARDL this paper will employ bound test for testing cointegration among the variables in current study , the estimation takes the following formula: n1

n2

n3

n4

n5

n6

i=1

i=0

i=0

i=0

i=0

i=0

ΔSPI t = β01 +  β11 ΔSPIt-i +  β12 ΔlnM2t-i +  β13 ΔlnDRt-i +  β14 ΔlnEX t-i +  β15 ΔCPIt-i +  β16 ΔlnIPt-i + 11SPIt-1 + 12lnM2t-1 + 13lnDRt-1 + 14 lnEX t-1 + 15CPI t-1 + 16 lnIPt-1 + εt1

(2) n1

n2

n3

n4

n5

n6

i=1

i=0

i=0

i=0

i=0

i=0

ΔlnM2t = β02 +  β21 ΔlnM2t-i +  β22 ΔSPIt-i +  β23 ΔlnDRt-i +  β24 ΔlnEX t-i +  β25 ΔCPI t-i +  β26 ΔlnIPt-i + 21SPIt-1 + 22lnM2t-1 + 23lnDRt-1 + 24lnEX t-1 + 25CPI t-1 + 26lnIPt-1 + εt2

(3) n1

n2

n3

n5

n6

n7

i=1

i=0

i=0

i=0

i=0

i=0

ΔlnDRt = β03 +  β31 ΔlnDRt-i +  β32 ΔSPIt-i +  β33 ΔlnM2t-i +  β34 ΔlnEX t-i +  β35 ΔCPI t-i +  β36 ΔlnIPt-i + 31SPIt-1 + 32lnM2t-1 + 33lnDRt-1 + 34lnEX t-1 + 35CPI t-1 + 36lnIPt-1 + εt3

(4) n1

n2

n3

n5

n6

n7

i=1

(i=0)

i=0

i=0

i=0

i=0

ΔlnEX t = β04 +  β41 ΔlnEX t-i +  β42 ΔSPI(t-i) +  β43 ΔlnM2t-i +  β44 ΔlnDRt-i +  β45 ΔCPI t-i +  β46 ΔlnIPt-i + 41SPIt-1 + 42lnM2t-1 + 43lnDRt-1 + 44lnEX t-1 + 44CPIt-1 + 46lnIPt-1 +εt4

(5) n1

n2

n3

n5

n6

n7

i=1

i=0

i=0

i=0

i=0

i=0

ΔCPI t = β05 +  β51 ΔCPIt-i +  β52 ΔSPIt-i +  β53 ΔlnM2t-i +  β54 ΔlnDRt-i +  β55 ΔlnEX t-i +  β56 ΔlnIPt-i + 51SPI t-1 + 52lnM2t-1 + 53lnDRt-1 + 54lnEX t-1 + 55CPI t-1 + 56 lnIPt-1 + εt5

(6) n1

n2

n3

n5

n6

n7

i=1

i=0

i=0

i=0

i=0

i=0

ΔlnIPt = β06 +  β61 ΔlnIPt-i +  β62 ΔSPIt-i +  β63 ΔlnM2t-i +  β64 ΔlnDRt-i +  β65 ΔlnEX t-i +  β66 ΔCPIt-i + 61SPIt-1 + 62lnM2t-1 + 63lnDRt-1 + 64lnEX t-1 + 65CPI t-1 + 66lnIPt-1 + εt6

(7)

407

Where: SPI, lnM2, lnDR, lnER, lnIP (1999 as a base year), CPI (2006 as a base year) are the macroeconomic variables that have defined in section (4);  , is the first difference operator. β01 ,..., β06 : are the constant terms, β11 ,..., β66 represented the short-run coefficients; while the 11 ,..., 66 represented the long-run coefficients; n1, ..., n7 : are the lag length;

εt1 ,...,εt6 : are white noise error terms. For testing the existence of short-run relationship among the variables in the equations (2-7) we can formulate the null and alternative hypotheses as the following:

H0 : No short – run relationship

H1 : A short – run relationship

11  12  13  14  15  16  0

11  12  13  14  15  16  0

21  22  23   24   25   26  0

 21   22   23   24   25   26  0

31  32  33  34  35  36  0

31  32  33  34  35  36  0

41  42  43   44   45   46  0

 41   42   43   44   45   46  0

51  52  53  54  55  56  0

51  52  53  54  55  56  0

61  62  63  64  65  66  0

61  62  63  64  65  66  0

However, for testing the existence of long-run relationship, the null and alternative hypotheses formulates as the following: H0 : No long–run relationship

H1 : A long–run relationship

11  12  13  14  15  16  0

11  12  13  14  15  16  0

21  22  23  24  25  26  0

21  22  23  24  25  26  0

31  32  33  34  35  36  0

31  32  33  34  35  36  0

41  42  43  44  45  46  0

41  42  43  44  45  46  0

51  52  53  54  55  56  0

51  52  53  54  55  56  0

61  62  63  64  65  66  0

61  62  63  64  65  66  0

According to Pesaran et al. (2001), the null hypothesis of no co-integration among the variables can be rejected, if the estimated F-statistic higher than the upper bound of critical value. If the estimated F-statistic is smaller than the lower bound of critical value, then the null hypothesis of no co-integration cannot be rejected, which implies the variables are not co-integrated. If the calculated F-statistic falls between upper and lower bounds the decision is inconclusive regarding to the null hypothesis of no co-integration. We can use the following formula: 408

Fs Fs

Upper bound Lower bound

Reject Accept

, the variables are cointegrated. the variables aren‘t cointegrated.

Fs  Lower bound and  Upper bound Where: Fs is: F-statistic.

Inconclusive result.

RESULTS ANALYSIS In this section we analyzed the time series measures. The Augmented Dickey Fuller (ADF) of unit root test were utilized to determine the order of cointegration, followed by the bound testing .Finally, the error correction model to assess the dynamic short-run relationship among the SPI and the selective variables. Figure (4) shows the variables namely, lnM2, lnIP, and CPI exhibit a significant linear upward trend. As for the SPI, it shows a steep and sharp upward trend during the 2002-2005 period. lnM2 shows a gradual rise with some structural break. However, the variables lnIP and CPI show slight structural breaks and the variable SPI shows a minor structural break, while lnDR shows a drastic downward fall. Besides, the variable lnEX shows a sharp upward trend during the 1987-1993 period, and then it remains constant. Unit Root Tests

As we know the problems associated with non-stationary time series, the practical question is what to do to avoid the spurious regression problem that may arise from regressing a nonstationary time series? Gujarati, (2009) confirmed that if we face a non-stationary time series, we have to transform it into stationary by using the first difference. It is important to analyze the stationary need of the six variables as the stationarity characteristic is necessary in time series approaches. Here, the study employs the Augmented Dickey-Fuller (ADF) test of the data for the 1978-2010 period. Table 1 reports the test results for the six series, both in levels and in first-differences. TABLE 1: ADF TESTS st

Variables

ADF - Level

ADF- 1 Difference

Order of Integration

SPI

-1.0878

-7.4245***

I (1)

lnM2

-2.6632

-3.5140 **

I (1)

lnDR

-2.6307

-4.1355 ***

I (1)

lnEX

-2.0394

-4.3809 ***

I (1)

CPI

0.8845

-4.4547 ***

I (1)

lnIP

-3.3705**

-5.3954 ***

I (0)

Note: All variables are in natural logarithms, ***, **, * denotes significant level of 1%, 5%, 10% respectively. Source: output of E.Views Package, version 7.

409

FIGURE 4: PLOTS THE VARIABLES OF THE STUDY SPI

LNM2

10,000

11

8,000

10

6,000

9

4,000

8

2,000

7

0

6 1980

1985

1990

1995

2000

2005

2010

1980

1985

1990

LNIP

1995

2000

2005

2010

2000

2005

2010

2000

2005

2010

LNEX

5.2

-0.2 -0.4

4.8

-0.6 4.4 -0.8 4.0 -1.0 3.6

-1.2

3.2

-1.4 1980

1985

1990

1995

2000

2005

2010

1980

1985

1990

LNDR

1995

CPI

2.4

140 120

2.0 100 1.6

80 60

1.2 40 0.8

20 1980

1985

1990

1995

2000

2005

2010

1980

1985

1990

1995

Note:  is the first difference operator. Source: Output E.Views7.

The results show that we cannot reject the null hypothesis of unit roots for all variables in level forms except for lnIP which is stationary I(0). However, the null hypothesis was rejected when the ADF test was applied to the first differences of each variable. The first differences of SPI, lnM2, lnDR, lnEX, and CPI are stationary of order one, I(1). Since all variables are stationary after first differencing, it is proper to test whether the variables are co-integrated or not. 410

In the first step of the ARDL analysis, we tested for the presence of long-run relationships among the variables. While we use yearly data, the number of observation is limited. Therefore, the maximum order of lags in the ARDL was (2). According to Pesaran & Shin, (1999) the Schwartz Bayesian Criterion (SBC) is minimizing lag and the most proper in yearly data. So, we use the SBC & Akaike information criterions in lag selection with intercept and no trend. Specifically, in this paper, the small data sample is another reason to prefer SBC. The calculated F-statistics are reported in Table 2. TABLE 2: BOUND TESTING FOR COINTEGRATION Model

F-statistic

k

Fspi (SPI / lnM2,lnDR,lnEX,CPI,lnIP)

10.5987***

5

Cointegration

Critical bound Lower Upper I(0) I(1) 2.262 3.367

FlnM2 (lnM2 / SPI,lnDR,lnEX,CPI,lnIP)

3.2497

5

No Cointegration

2.649

3.805

FlnDR (lnDR / SPI,lnM2,lnEX,CPI,lnIP)

3.9584**

5

Cointegration

3.516

4.781

FlnEX (lnEX / SPI,lnM2,lnDR,CPI,lnIP)

2.3341

5

No Cointegration

FCPI (CPI / SPI,lnM2,lnDR,lnEX,lnIP)

2.5613

5

No Cointegration

FlnIP (lnIP / SPI,lnM2,lnDR,lnEX,CPI)

1.9696

5

No Cointegration

Result

Note: The critical value bounds are from Table F in Pesaran and Pesaran, Oxford (2009, p. 544). k is the number of regressors (with an intercept and no trend). * denotes that the F-statistic falls above the 90% Upper bound, ** denotes above the 95% upper bound and *** denotes above the 99% upper bound. Source: Output of Microfit Package, version 4.1.

The Equations (2)-(7) are estimated using annual data for the 1978-2010 period. Also, compared with the critical values as can be seen in Table (2), the calculated F-statistic of ( Fspi ) = 10.598 is higher than the upper bound critical value = 4.781. Besides, when discount rate variable is taken as dependent variable the computed FlnDR = 3.958 is higher the upper bound at the 5% = 3.805. Thus, we reject the null hypothesis (no co-integration). Therefore, there is a compelling long-run co-integration relationship among the variables when the regressions are normalized on both SPI and lnDR variables. On the other hand, when the process was repeated for the rest of variables, their calculated F-statistics are less than the lower bound at 10% level of significance, suggesting a strong evidence of cointegration between SPI and its determinants for in Jordan for the period under estimation. TABLE 3: LONG-RUN ESTIMATION RESULTS OF ARDL ANALYSIS

SPI model, Equation (2) SPIt  96.7803+13014.0lnM2t-1 - 6157.4lnDRt-1 +12883.2lnEX t-1  445.6172CPIt-1  18834.2lnIPt-1 t:

1.4883 [.168]

-1.9042* [0.086]

Note: ***, **, * denotes 1%, 5% and 10%. Level of significance, respectively. Source: Output of Microfit Package, version 4.1.

411

2.6816*** [0.023]

-2.2913** [0.045]

-2.0414* [.068]

Table (3) shows the results of the long run coefficients for SPI model. These results show there are long-run relationships among the variables. All estimated coefficient are statically significant except for M2 which shows a positive insignificant impact on the stock price index. Also, all coefficients have a correct sign as we expected, the discount rate marks a negative impact on SPI and significant at the 10% level. Besides, the industrial production has a negative impact at the same level of significance; the consumer price index also has a negative impact at the 5% level of significance. On the other hand, the exchange rate has a significant positive impact on SPI at 1% level of significance. The short-run dynamics equilibrium relationship between the SPI and the regressors are obtained by the relevant error correction model, the results are presented in Table 4 below. The error correction term (Ect t-1 ) marks the adjustment back to equilibrium in the dynamic model. According to Nayaran, (2005) when (Ect t-1 ) is significant with a negative sign in the short- run model confirms the existence of a long- run equilibrium relationship among the variables. The larger value of (Ect t-1 ) the faster the economy can return to its equilibrium (Pesaran & Pesaran, 2009). As can be seen from the Table (4), the error correction term noted (Ect t-1 ) coefficient is found to be negative and significant = -.96101 [.000] is highly significant at 1% level with correct sign. That implies a highly speed adjustment back to equilibrium, .96101 % of disequilibrium from previous year‘s can adjustment back to longrun equilibrium in the current year. The regressions for the underlying ARDL for all models were passed the diagnostic tests of normality, serial correlation and hetoscedasitcity, the results of SPI model reveal no evidence of any misspecification as shown in Table (4). The estimated residual series of the equations confirmed the normality by Jarque–Bera statistic; Durbin-Watson statistic results found the ARDL model to be strong against residual autocorrelation. Furthermore, The ARCH test confirms the residuals are homoscedastic in all equations at 5% level of significant. TABLE 4: THE SHORT–RUN RELATIONSHIP WHEN ΔSPI IS DEPENDENT VARIABLE

ΔSPI model ΔSPIt = - 603.6529 - .6647ΔSPI

*** t-1

- 3431.3ΔlnEX

** t

- 4261.1ΔlnEX t-1 *** - 1209.6ΔlnIPt ** + 203.9552ΔlnCPI t *** +

92.3750ΔlnCPI t-1 ** + 2204.1ΔlnDRt *** +4384.5ΔlnDRt-1 ***  8168.7 ΔlnM2t *** - .96101ECTt-1 *** Normality

χ 2 (2) = .22572 [.893]

Durbin- Watson = 1.8513

Heteroscedasticity

χ2

(1) =.099976 [.752]

ECTt-1 = -.96101 [.001]

Note: ***, **, * denotes 1%, 5% and 10%. Level of significance, respectively. Source: Output of Microfit Package, version 4.1

Finally, to check the estimated ARDL model stability between SPI and its determinants, we employ the cumulative sum of recursive residuals CUSUM and the cumulative sum of squares CUSUMQ (Brown et al., 1975; Pesaran & Pesaran, 1997; and Bahmani-Oskooee & Bohl, 2000). According to Bahamni- Oskooee, (2002) if the plot of CUSUM statistic stays within 5% range significance level (within the two straight lines) the null hypothesis that all coefficients in the error correction model are stable cannot be rejected. If either of the lines is crossed, the null hypothesis of coefficient constancy can be rejected at the 5% level of 412

significance. A similar measure is used to carry out the CUSUMSQ test. A graphical presentation of these two tests is provided in Figure 5. As can be seen from Figure 5, the plot of CUSUM statistics stay within the critical boundaries suggesting stability of the long-run coefficient of the SPI function. The case is different in plot of CUSUMQ the plot of CUSUMQ statistically does not stay within the critical boundaries by crossing the 5% critical bounds. This indicates instability of the long-run coefficients of the SPI function for the 2000-2004 period. Also, we assume the reason of instability refer to the structural breaks in SPI refer to another reasons that may affect the ASE which are need to examines in further studies. FIGURE 5: PLOTS OF CUSUM AND CUSUMQ UNDERWRITING SPI

Plot of Cumulative Sum of Recursive Residuals 15 10 5 0 -5 -10 -15 1981

1986

1991

1996

2001

2010

2006

The straight lines represent critical bounds at 5% significance level

Plot of Cumulative Sum of Squares of Recursive Residuals 1.5 1.0 0.5 0.0 -0.5 1981

1986

1991

1996

2001

2006

2010

The straight lines represent critical bounds at 5% significance level

CONCLUSION, MANAGERIAL IMPLICATIONS AND LIMITATIONS This study has employed the ARDL time series approach on annual time series data during the (1978-2010) period to endogenously examines the most significant and important macroeconomic variables impacting SPI in Jordanian economy. This paper could identify a long-run equilibrium relationship among stock price index and Money supply, exchange rate, discount rate, inflation, and industrial production. The empirical results provide strong evidence against the null hypotheses of unit roots in most of the series under investigation. Moreover, applying the ECM version of the ARDL shows the error correction coefficient, which determines the speed of adjustment, has an expected and highly significant negative sign equal -.96101. The results are consistent with the hypothesis, where the SPI is found to have both short and long-run significant relationship with the selective variables.

413

The CUSUM stability tests as well showed the coefficients of the error correction model are stable. On the other hand, the CUSUMQ is out of the critical bound which means it doesn‘t completely stable during 2000-2004. We assigns that to the disequilibrium of Jordan economy in the short- run and suggests to further studies the instability refer to other causes that may affect the Jordan economy and SPI such as, political events and crisis. So, further studies may be preceded by incorporating such variables. The estimation of the long- run coefficients of macroeconomic variables showed the macroeconomic variables are very significant and important to the SPI fluctuations. These macroeconomic variables are cointegrated. The results indicate that this cointegration relationship is consistent with the earlier findings (for example, Hammoudeh & Savi 2011; Rahman et al. 2009; Beltratti & Morana 2008; Maysami 2004; Al-Sharkas 2004; and Kim 2002). The current paper is important for all stockholders, policy makers, all kinds of investors, corporations and other financial market participants. In this study, we add to the canon of knowledge by employing ARDL approach in ASE which has become the most popular approach to examining cointegration among financial variables. In addition, studying the relationship between the macroeconomic indicators and the SPI can shed some light on the stock market‘s response to macroeconomic factors for similar emerging markets. Thus, it can be claimed that stock price variability is basically linked to economic variables, through the change in stock price lags behind economic activities. Finally, we suggests for the further studies to find more causes that may impacts SPI such as (wars, terrorist attacks, and the revolutions specially the recently Arab spring) which may have a strong effect on SPI fluctuations. The study has some limitations, namely: 1. There is a lack of previous studies examining similar purposes in emerging markets. Therefore, in this study the reference is based mostly on the studies that were carried out in developed countries, with only a limited number of studies that have been conducted in developing countries. 2. The study excluded some macroeconomic factors because of the lack of adequate data during the study period such as, GDP and domestic export. 3. Duration of longer term period provides more meaningful results. Therefore, in this study yearly data is used rather than quarterly, monthly or daily data. Besides, the data available during the time period of this study is annual data; so the choice of yearly data is supported.

REFRENCES Abugri, B.A. (2008). Empirical relationship between macroeconomic volatility and stock returns: Evidence from Latin American markets. International Review of Financial Analysis, 17, 396–410. Al-sharkas, A. (2004). The Dynamic Relationship between Macroeconomic Factors and the Jordanian Stock Market. International Journal of Applied Econometrics and Quantitative Studies, 1, 97-114.

414

Amman stock exchange, http://www.ase.com.jo/en/trading-value-ase, different publications. http://www.ase.com.jo. Retrieved 13 March (2012) Apergis, N & Miller, S.M. (2009). Do structural oil-market shocks affect stock prices? Energy Economics, 31, 569–575. Brooks, C. (2004). Introductory Econometrics for Finance.2nd edition, Cambridge University Press. Bekhet, H.A., & Matar, A. (2011). Analyzing Risk-Adjusted Performance: Markwoitz And Single-Index Approaches In Amman Stock Exchange, International Conference On Management (ICM) Proceeding, 305-321. Bekhet, H.A., & Matar, A. (2011). Risk-Adjusted Performance: A two-model Approach Application in Amman Stock Exchang. International Journal of Business and Social Science, 3(7), 34-45. Business Directroy. http://www.businessdictionary.com . Retrieved 15 December (2011). Chen, N.F; R.Roll & Ross, S. 1986, Economic Forces and the Stock Market, Journal of Business, 59, 383-403. Central Bank of Jordan, (www.cbj.gov.jo). Retrieved 13 March (2011). De Gregorio, J., & Guidotti, P.E. (1995). Financial development and economic growth. World Development, 23(3), 433-448. Diamandis, P.F., & Drakos, A.A.(2011). Financial liberalization; exchange rates and stock prices: exogenous shocks in four Latin America countries. Journal of Policy Modeling,33,381-394. Engle, R.F. & C.W.J.Granger, 1987, Cointegration and Error Correction: Representation, Estimation and Testing, Econometrica, 55, 251-76. Fama, E. And Schwert, G. (1977). Asset returns and inflation. Journal of Financial Economics 5, 115-146. Fama, E. (1990). Stock returns, expected returns, and real activity. Journal of Finance, 45, 1089-1109. Ghatak S. and Siddiki, J.(2001), The use of ARDL approach in estimating virtual exchange rates in india, Journal of Applied Statistics,11:573-583. Ghosh, S. (2009). Import demand of crude oil and economic growth: Evidence from India. Energy Policy, 37(2), 699-702. Griffiths, W.; Hill, R.; & Lim, G. (2012). Using Eviews for Principles of Econometrics. 4th edition, New York/Chichester/Weinheim/Brisbane/Singapore/Toronto: John Wiley & Sons,INC. 415

Gosnell, T. & Nejadmalayeri, A. (2010). Macroeconomic news and risk factor innovations. Managerial Finance, 36(7), 566-582. Granger, C.W.J. (1986). Developments in the study of co-integrated economic variables. Oxford Bulletin of Economics and statistics, 48, 213-228. Gujarati, D. (2009). Basic Econometrics. 4th edition, New York : McGraw-Hill. Hussain, S.M. (2011). Simultaneous monetary policy announcements and international stock markets response: an intraday analysis. Journal of Banking & Finance, 35, 752–764. International Monetary Fund. http://www.imf.org. Retrieved 14 April (2012). Jayaraman, T. & Choong, C.K. (2009). Growth and oil price: A study of causal relationships in small Pacific Island countries. Energy Policy, 37(6), 2182-2189. Johansen, S. (1991). Estimation and Hypothesis Testing of Cointegrating Vectors in Gaussian Vector Autoregressive Models, Econometrica 59, 1551-80. Kearney, C. (2000). The determination and international transmission of stock market volatility. Global Finance Journal, 11, 31-52. Kim, S. (2002). The influence of foreign stock markets and macroeconomic news announcements on Australian financial markets. Pacific-Basin Finance Journal, 10, 571– 582. Kim, S.J., McKenzie, M. D., & Faff, R. W. (2004). Macroeconomic news announcements and the role of expectations: evidence for US bond, stock and foreign exchange markets. Journal of Multinational Financial Management, 14(3), 217-232. Kirman, A.P. (1992). Whom or what does the representative individual represent? The Journal of Economic Perspectives, 6(2), 117-136. Maghyereh, A.I. 2002. Causal relations among stock prices and macroeconomic variables in the small, open economy of Jordan. Available at http://ssrn.com/ abstract=317539. Retrieved 15 November, 2011. Maysami, R; Howe, L. & Hamzah, M. (2004). Relationship between Macroeconomic Variables and Stock Market Indices: Cointegration Evidence from Stock Exchange of Singapore‘s All-S Sector Indices. Jurnal Pengurusan, 24, 47-77. Nidhiprabha, B. (2010). Effectiveness of Thailand's macroeconomic policy response to the global financial crisis. ASEAN Economic Bulletin, 27(1), 121-135. Omran, M. & Pointon, J. (2001). Does the inflation rate affect the performance of the stock market? The case of Egypt. Emerging Markets Review, 2, 263-279. Park,K. & Agtmael, A.(1994). The World Emerging Stock Markets. 1st publishing, Heinemann Asia, Singapore.

416

Philip Hans Franses, Time Series Models for Business and Economic Forecasting, Cambridge University Press, New York, 1998, p. 155. Pesaran, M., & Pesaran, B. (2009). Time Series Econometrics, 1st edition, Oxford University Press Inc., New York. Pesaran, M., & Pesaran, B. (1997). Microfit 4.0 (Windows Version). New York: Oxford University Press. Pesaran, M., Shin, Y. & Smith, R. (2001) ) Bounds Testing Approaches to the Analysis of Level Relationships, Journal of Applied Econometrics, 16, 289-326. Rahman, A., Sidek, N. & Tafri., F. (2009). Macroeconomic determinants of Malaysian stock market. African Journal of Business Management, 3(3), 95-106. Rangel, J.G. (2011). Macroeconomic news, announcements, and stock market jump intensity dynamics. Journal of Banking & Finance, 35, 1263–1276. Sari, R., Ewing, B. T., & Soytas, U. (2008). The relationship between disaggregate energy consumption and industrial production in the United States: An ARDL approach. Energy Economics, 30(5), 2302-2313. S&P,https:www.spindexdata.com/idpfiles/shariah/prc/active/pressreleases/SP_Indices_Count ry_Classification_Consultation_2011R.pdf. http://www.indexmundi.com/jordan/economy_profile.html. Retrieved 4 April (2012). http://data.worldbank.org/indicator/NY.GDP.MKTP.CD/countries/JO. Retrieved 4 April (2012).

417

ANALYZING ELASTICITIES AND THE RELATIONSHIP AMONG CONSTRUCTION PRODUCTION DETERMINANTS IN MALAYSIA

Hussain Ali Bekhet Graduate Business School, College of Graduate Studies University Tenaga Nasional (UNITEN), Malaysia [email protected], [email protected]

Nor Hamisham Binti Harun Department of Finance and Economics, College of Business Management and Accounting Universiti Tenaga Nasional (UNITEN), Malaysia [email protected]

ABSTRACT The current paper investigates the relationship between production and energy of the Malaysian construction industry. Time series data for production (Q), Gross Fixed Capital Formation (GFCF), labour (L), and energy (E) for the 1978-2011 period are used. However, the paper examines the long-run relationships among Gross Fixed Capital Formation (GFCF), labour (L), and energy (E), and construction industry production (Q) over the 19782011 period. Besides, the significant relationships among the variables above and the production theory applied are also explored. The results of the unit root tests show that the variables are stationary in the second difference at the 5 percent significance level. Furthermore, there is a co-integration among the study‟s variables. This implies the existence of a long run relationship among the Q and its factors (GFCF, L, and E). The results also reveal that labour is one of the most important factors compared to energy and capital, towards the construction industry. Keywords: production theory, construction industry, unit root tests, co-integration , Malaysia..

418

INTRODUCTION The construction industry plays an important role in the economic development of any country in the world. It establishes the infrastructure required for socioeconomic development while being a major contributor to overall economic growth (Abdullah et al., 2004). In Malaysia, the annual growth rate between construction and economic growth move together. Generally, most researchers have discussed the conceptual factors of of the construction industry. Wong & Ng. (2010) discussed the factors that influence a company‘s failure. Furthermore, Begum et al. (2009) explained about the contractor attitudes and behaviors that affect waste management in the construction industry in Malaysia. Tzortzopoulos et al. (2005) studied about the implementation process for the construction industry to enhance the effectiveness and efficiency of the design and construction activity in response to the need for improving performance. Wibowo (2009) examined the determinants that affect investing in construction. The affects considered are those of the micro and macro economy of the people directly or indirectly employed by the construction industry. There is considerable research which has analyzed the relationship between economic growth, development, and the construction industry (Giang & Pheng, 2011; Ofori & Han, 2003; Dong et al. (2011). Gerard (2005) discussed the construction industry using the production function. However, This paper focuses on the input side to analyze the properties of construction production technology, the role of technical progress and the shift in the production function. Allen (2001) estimated the construction industry using the Cobb-Douglass production function to determine the impact of the capital-labour ratio, economies of scale, labour quality, percentage union, the composition of output and the distribution of construction projects across regions. The current paper presents a theory of elasticities using the Cobb Douglass production function to measure the elasticity of capital, labour and energy in the construction industry in Malaysia. Therefore, the primary aim of this paper is to establish from observation in the construction industry in Malaysia for the 1978 – 2011 period, the elasticity of capital, labour and energy; using either labout-intensive technology, capital-intensive technology or energy use. The second objective is to analyze the relationship between production and labour, capital and energy in the construction industry. The rest of the paper is organized as follows; Section 2 discusses the construction industry, focusing on the background and the growth rate of the construction industry in Malaysia. Section 3 reviews previous literature related to the current study. Section 4 defines the data, variables and methodology used in this study. Section 5 analyzes elasticity and relationship of capital, labour and energy towards the construction production. Section 6 discusses the policy implications of the result. Finally, section 7 includes some conclusion and suggests recommendation and further studies.

OVERVIEW OF CONSTRUCTION INDUSTRY

419

The construction industry in Malaysia began since independence in 1957. Ibrahim et al. (2010) explained that the Malaysian construction industry is separated into two areas. The first area is general construction, which comprises residential construction, non-residential construction and civil engineering construction. The second area is special trade works, which comprises activities of metal work, electrical work, plumbing, sewerage and sanitary work, refrigeration and air-conditioning work, painting work, carpentry, tiling and flooring work and glass work. However, the construction industry‘s output is relatively small when compared to the other sectors in Malaysia. The Department of Statistics (2011) showed that the construction industry only contributes 6.16 percent to GDP compared to the other sectors in Malaysia. Even though, the growth rate of the construction production was 9.7 percent for the 19782011 period (Refer to Figure 1).

FIGURE 1: PRODUCTION OF CONSTRUCTION INDUSTRY FOR 1978-2011 (RM MILLION)

* Source: Department of Statistics, Malaysia (2011)

Ofori (1990) showed that the construction industry plays an important role in national employment. This situation will create more job opportunities to society. The construction industry employed 6.53 percent of the total labour force in Malaysia (Malaysia Economic Report, 2012). Unfortunately, most of workers come from Indonesian or other countries. Even though, the construction industry is frequently used as a tool by government to manage the local or national economy (Wibowo, 2009). For instance, the government uses the construction industry to increase public expenditure when there is a situation of recession and the number of unemployment is high (Ball & Wood, 1994). The results of this policy showed the growth rate of labour was 3 percent in the 1978–2011 period (See Figure 2).

420

FIGURE 2: NUMBER OF WORKERS IN CONSTRUCTION INDUSTRY FOR 1978-2011 (‘000)

* Source: Department of Statistics, Malaysia (2011).

Furthermore, we can say that the major input that contributes to construction production is labour-intensive. However, instead of being only labour-intensive, there is capital formation as a factor of production in the construction industry. The formation of fixed capital investment is a vital concern for the state of the nation as it represents investment in the future of the economy of the country (Wibowo, 2009). For instance, plant and machinery of the construction industry represent business investment.

The conceptual of the gross capital stock is useful in measuring the productivity of the economy. Giang and Pheng (2011) revealed that higher productivity in turn attracts more resources (private investment) into production, which further contributes to a higher levels of output, profitability of production, income and employment in these industries. The process of investing in the physical capital stock of an economy, including infrastructure is measured by the Gross Fixed Capital Formation (GFCF). In the Malaysia economy it is shown that the growth rate of capital formation for the 1978–2011 period was 5 percent (See Figure 3). FIGURE 3: GFCF OF CONSTRUCTION INDUSTRY FOR 1978-2011 (RM’000)

* Source: Department of Statistics, Malaysia (2011).

The production capacity of an economy is usually described in terms of the complete utilization of factors of production which are labour and capital (Giang & Pheng, 2011).

421

Instead of the existence of labour and capital as factors of production, energy will be used to analyze the essential factors of production towards the growth of the construction industry. Nowadays, energy becomes a most important factor that contributes to all the industries in the world. This topic is related to energy that is more interesting to researchers. Most researchers have analyzed energy with the macroeconomic variables. However, the growth rate of energy in the Malaysia economy was 6.5 percent for the 1978-2011 period (See Figure 4). However, this analysis investigates the relationship between the factors of production (labour, capital and energy) towards the production of the construction industry.

FIGURE 4: TOTAL ENERGY USE IN CONSTRUCTION INDUSTRY FOR 1978-2011 (KTOE ‘000).

* Source: National Energy Balance, Malaysia (2011).

LITERATURE REVIEW Many of the previous studies concentrate on the conception of the construction industry. Tzortzopolous et al. (2005) discussed different process models to enhance the effectiveness and efficiency of the design and construction activity in response to the need for improving performance. Begum et al. (2009) studied the attitudes and behaviors of individuals involved in the construction industry and their influence on its economic growth and performance. Furthermore, Ibrahim et al. (2010) explained the production process utilized by the Malaysian construction industry. His current study analyzes the global construction industry focusing on the evolution of lean production systems. Also, Wibowo (2009) investigated how the money invested in construction flows through the economy in Indonesia using the survey analysis. Furthermore, Wong and Ng (2010) studied company failure in the construction industry; what are the causes of construction to fail? What are the techniques for predicting company failure? All these questions are important because they believed that understanding the mechanism of failure is the key in attempting to avoid it. However, there are many papers which have discussed the relationship between industry and economic growth. Ofori and Han (2003) examined the relationship between construction 422

activity and economic development at the provincial level in the Peoples‘ Republic of China. They also analyzed the variations in the mix of construction outputs among the provinces as they achieved increasing levels of development. Consequently, data demonstrating developments in China‘s wider economy and its construction activity at the provincial level can be used to test the applicability of the Turin hypothesis within a country that has undergone significant developments over such a short period of time. Dong et al. (2011) found that short run economic fluctuation causes industrial structure disproportion, while a long run bidirectional causal relationship exists between industry structure disproportion and economic aggregate fluctuation in China. Further, Giang and Pheng (2011) showed that there is a significant relationship between the construction industry and economic growth in developing countries. However, Gerard (2005) analyzed the inputs which are concerned with the technical constraints of production processes that determine the cost base.

Batisani and Yarnal (2010) analyzed the elasticity of capital-land substitution in the housing construction using the Constant Elasticity of Substitution (CES) and the Variable Elasticity of Substitution (VES) production function. They evaluated the impacts that anti-sprawl, smart growth policies promoting higher land prices can have on housing prices. Analysis for Gabrone, Botswana captures the city‘s sprawling nature by showing that residential housing density is constant and low across the metropolitan area. Arnberg and Bjoner (2007) estimated factor demand models with electricity, other energy, labour and machine capital as flexible inputs using both the translog and the linear logit specification, based on micro panel data for industrial companies. They found that both electricity and other energy are complements with capital. This result showed that energy also plays an important role towards industrial companies instead of capital. Furthermore, Tse and Ganesan (1997) investigated lead-lag relationships between construction activity and the aggregate economy in Hong Kong using Granger causality methodology. The result showed that the unidirectional nature of GDP tends to lead the construction flow not vice versa. Additionally, Ozcelebi (2011) analyzed the effect of some major macroeconomic variables on construction sector activity in Turkey using a Vector Autoregression (VAR) model. The current study focuses on the factors of production (capital, labour and energy) and how they influence the production of the construction industry in Malaysia using production theory.

DATA AND METHODOLOGY Data and Variables The annual data of the production, capital, labour and energy for the 1978-2011 period, are used in this study.. This study focuses on the construction industry in Malaysia. The production of the construction industry is measured by gross output in value of RM‘000, while it uses Gross Fixed Capital Formation (GFCF) in Ringgit Malaysia (RM), to represent capital (K). These values are converted to real values, by deflating a country‘s consumer 423

price index, 2000 is used as a base year. However, labour (L) is measured by the total number of workers in the construction industry. Whereas, energy is measured by total energy consumed in the industry in kilo tonnes of oil equivalent (ktoe). Technology (T) is included as a variable, indicating that when time is increased, the new technology is introduced. Besides, data on gross output, gross fixed capital formation and total number of workers in the construction industry are obtained from the the Department of Statistics, Malaysia (DOSM). While, total energy in the industry is extracted from the National Energy Balance in Malaysia. The E-Views Microsoft package is used to achieve the objectives of this study. Methodology In the current paper, production theory is used which was presented by Stern 1993. Furthermore, there were many researchers who have presented this theory in advanced economies (For example, Ghali and El-Sakka (2004); Soytas and Sari (2007); Yuan et al. (2008). Currently, we applied the following formula.

Q  A(t ) K  L E  [1] Where Q is the production, t is technology, K is capital, L is labour and E is energy. The elasticities of capital, labour and energy are represented by estimated coefficients α, β and γ; respectively. For the purpose of this study, the Equation [1] is rewritten using a natural logarithm form, as shown in Equation [2].

[2] The parameters α, β and γ represent the elasticities of capital, labour and energy; respectively. dA  0 indicating that with a higher technology t the While A (t) has a positive derivative, dt same inputs produce more output (Thompson, 2006). The unit root test and multivariate cointegration test are used to determine the long run equilibrium among Q, K, L and E variables. Unit Root Test The Augmented Dickey-Fuller (ADF), and/or Phillips-Perron (PP) tests can be used to infer the number of unit roots (if any) in each of the variables (Enders, 1995). These tests are very useful to show the importance of stationary properties. Therefore, the purpose of these tests are to make sure that the individual variables used in this study are stationary. These tests also can determine whether they are integrated or not. If all variables are not stationary, it is not necessary to proceed since standard time series methods apply to stationary variables (Enders, 1995). Therefore, the result could be spurious regression, if the test is a non-stationary series. The null and alternative hypothesis for the existence of unit root for the study‘s variable, X i (Q, K, L and E) are: 424

H0: δ = 0 (Xi is non-stationary or contains a unit root ). H1: δ < 0 (Xi is stationary or a non-unit root ). However, if the value of ADF or PP tests statistic is less than a critical value, the null hypothesis will be rejected. In other words, if the estimated value for δ is significantly less than zero, the series is stationary. Otherwise, the time series have a unit root process. Some studies confirmed that the economic variables are likely to be stationary in the first difference, I(1), for most economic variables (Tang, 2009). Co-integration Test The co-integration procedure is used to identify the long run relationship between the dependent and independent variables. If the result of the unit root test indicates that all variables are integrated with the same order, then we can estimate the long run equilibrium relationship (Enders, 1995). Using the Ordinary Least Square (OLS) estimation, it would be convenient if we could perform the Augmented Dickey-Fuller (ADF) test on the estimated residuals to determine the order of integration (Enders, 1995). If the residual is stationary or level, there is a co-integrating relationship between dependent and independent variables and vice-versa. This test was developed by Engle-Granger (1987).

RESULTS ANALYSIS Table 1 reports the ADF and PP test statistics on the natural logarithms of the Q, K, L and E in Equation [2]. The results show that the null hypothesis of unit root for all variables, in level form and first different, with or without a time trend, are rejected at all conventional levels of significance. Therefore, all the variables are stationary at the second different I(2) at the 5 percent significance level. TABLE 1: UNIT ROOT TEST FOR STATIONARITY. At Levels

At First difference

At 2nd difference

PP

ADF

PP

ADF

PP

Intercept and trend

Intercept and trend

Intercept and trend

Intercept and trend

Intercept and trend

Intercept and trend

lnQ

**-3.635006

-1.916508

***-3.399425

***-3.399425

*-6.917453

*-6.966647

lnK

-1.711319

-1.936539

**-4.000655

**-3.867783

*-5.756944

*-14.13289

lnL

**-3.758036

-2.17247

***-3.414871

***-3.414871

*-7.001138

*-7.264413

lnE

-0.162647

-0.60394

**-3.970249

**-3.777048

*-6.084500

*-12.86518

Variables

ADF

Note : *it means that the value test less (