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Journal of High Technology Management Research 23 (2012) 1–14

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Journal of High Technology Management Research

Factors affecting the adoption of Internet banking in Tunisia: An integration theory of acceptance model and theory of planned behavior Wadie Nasri a, Lanouar Charfeddine b,⁎ a

Assistant Professor, Management department in the Higher Institute of Management of Gabes, University of Gabes, Tunisia Assistant Professor, Quantitatives methods department, Higher Institute of Management of Gabes, University of Gabes, Tunisia, BP 75, ISG Gabès, Street Jilani Al Habib, 6000, Gabes, Tunisia

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a r t i c l e

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Available online 29 March 2012 Keywords: Technology acceptance model (TAM) Theory of planned behavior (TPB) Intention behavior Tunisian Banks Structural equation modeling (SEM)

a b s t r a c t This paper examines empirically the factors that affect the adoption of Internet banking by Tunisian bank customers. As base model, we use the technology acceptance model (TAM) and theory of planned behavior (TPB). The model employs security and privacy, self efficacy, government support, and technology support, in addition to perceived usefulness, perceived ease of use, attitude, social norm, perceived behavior control and intention to use Internet banking. Structural equation modeling is employed to examine the inter-correlations among the proposed constructs. A survey involving a total of 284 respondents is conducted and confirmatory factor analysis was used to determine the measurement efficacies. Theoretically, this study confirms the applicability of the TAM model and TPB in predicting Internet banking adoption by Tunisian bank customers. The results allow banks' decision makers to develop strategies that can encourage the adoption of Internet banking. Banks should improve the security and privacy to protect consumers' personal and financial information, which will increase the trust of users. Government should also play a role to support bank industry by having a clear and solid law on this will ensure that customers are more confident for using Internet banking, ensuring a better Internet infrastructure and helps them to encourage users to use Internet banking. Lastly, Tunisian Banks should focus on those clients who already have a home PC, access Internet and more educated and younger since they are the most likely to adopt Internet banking. © 2012 Elsevier Inc. All rights reserved.

1. Introduction The evolution of technological innovation has had a major effect in banking industry. This evolution of banking has been driven by changes in distribution channels as evidenced by automated teller machine (ATM), Phone-banking, Telebanking, PCbanking and most recently Internet banking (Chang, 2003). The adoption of technology has led to the following benefits: greater productivity, profitability, and efficiency; faster service and customer satisfaction; convenience and flexibility; 24 × 7 operations; and space and cost savings. Banks have recognized the importance to differentiate themselves from other financial institutions through new distribution channels. This has resulted in banks developing, and utilizing new alternative distribution channels to reach their customers (Daniel, 1999; Thornton & White, 2001).

⁎ Corresponding author. Tel.: + 216 22 998 570. E-mail addresses: [email protected] (W. Nasri), [email protected] (L. Charfeddine). 1047-8310/$ – see front matter © 2012 Elsevier Inc. All rights reserved. doi:10.1016/j.hitech.2012.03.001

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Recently, Internet banking has been rapidly gaining popularity as a potential medium for electronic commerce (Crede, 1995; Ooi, 1999). The rapid growth of the Internet has presented a new host of opportunities as well as threats to business. With the development of new technology, Internet banking is expected to become a major banking method for customers. Internet banking should reduce costs by providing customers with another means of accessing their accounts without physically visiting a bank (Martin & Ambrosio, 2003). In addition, competition pressure from non-banks entering the financial markets by offering financial products and services have forced many banks to adopt Internet banking methods in order to stay competitive (Mols, 1998; Sathye, 1999). In recent years, a variety of theoretical perspectives have been applied to provide an understanding of the determinants of Internet banking adoption and use, including the intention models from social psychology. From this stream of social psychology research, the technology acceptance model (TAM) (Davis, 1989), an adaptation of theory of reasoned action (TRA) (Fishbein & Ajzen, 1975) and the theory of planned behavior (Ajzen, 1991) (TPB), are especially well researched intention models that have proven successful to predict technology acceptance behavior (Chau and Hu, 2001; Gefen, 2000; Gefen & Straub, 2000; Igbaria, Iivari, & Maragahh, 1995; Szajna, 1994). The purposes of this study are as follows: 1. To identify and describe the factors influencing the adoption of Internet banking in Tunisia. 2. To clarify which factors are more influential in affecting the intention to use Internet banking in Tunisia. 3. To evaluate whether the integration of TAM and TPB provides a solid theoretical basis for examining the adoption of Internet banking in Tunisia. The remainder of the paper is set out in seven sections. The first section contains a literature review on online banking and information systems acceptance. The second section presents the research methodology used in this work. The third section comprises the data analysis and hypotheses testing results. In this section the data is analyzed using a structural equation modeling. The Fourth section presents results. The fifthly sections consists to discuss the main findings and draw implications for theory and practice in sixthly section. Seventhly and finally, we suggest conclusion and future research directions and offer some final remarks.

2. Literature review 2.1. Internet banking in Tunisian Internet banking is another term used for online banking. Both share the similar meaning. Internet banking or online banking is defined as the use of Internet as a remote delivery channel of banking system services via the World Wide Web. Internet banking allows customer to have direct access to their financial information and undertake financial transactions without the hassle of going to the bank (Abdul Hamid, Amin, & Lada, 2007). This system enables customers 24 hour 7 day access to their account, and allows customers to conduct more complicated transactions, such as pay bills, applying for housing loan applications, online shopping, account consultation, and stock portfolio management. Tunisia country is one of the most developed telecommunication infrastructures in North Africa. Since the first use of Internet in Tunisia in 1996 until now, the number of Internet users is growing regularly. In fact, the number of Internet users is jumped from 111 users in 1996 to 3.6 million users in June 2010. This number reached to 3.9 millions in January 2010 (ATI). According to the «Global Information Technology Report 2008–2009», Tunisia was classified as the 38th country in the world (among 134) using information technology, it also remains the leader in Africa and succeeds to be the 7th one in the Mediterranean. For several years, commercial banks in Tunisia have tried to introduce Internet banking systems, such as the UBCI, STB, ATTIJARIBANK, BH, BTK, BIAT, BT, UIB, AB and BNA. The first bank offering Internet banking services was the Amen Bank in 2000. Actually, banking services offered via Internet are extended to other services more various and developed. So they are not only limited to services of consultation but also to other services more complicated like orders and payments of bills, deposit accounts, debit and prepaid cards, credit and commercial products, account management, statement payments, fund transfers, online shopping, etc. Although, the development of the Internet banking supply, the number of Internet banking users is still very weak in comparison with the other e-banking services, such as the telephone banking, mobile phone banking (SMS), and ATMS. Banking industry, suggest that Internet banking may become an increasing important distribution channel for all banks in Tunisia. Therefore, there is a need to understand the factors that influence intention to use Internet banking. However, there are limited empirical studies that identify the factors influencing Tunisian customers' decision to adopt Internet banking (Ayadi & Kafella, 2004; Dhekra, 2009 and Wadie, 2011). Therefore, this study seeks to provide academics and practitioners an understanding of the factors and their importance in influencing the adoption of Internet banking by Tunisian customers'.

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2.2. The technology acceptance model, theory of reasoned action and theory of planned behavior Several studies had been conducted to investigate the influencing factors of Internet adoption using different theory and models. The technology acceptance model (TAM) was originally proposed by Davis (1989), the theory of reasoned action (TRA) was originally proposed by Fishbein and Ajzen (1975), and the extension of TRA into a theory of planned behavior (TPB) was originally proposed by Ajzen (1991).

2.2.1. The technology acceptance model (TAM) The TAM introduced by Davis (1986) is one of the most cited theoretical frameworks to predict the acceptance and use of new information technology (software and information systems) within organizations. In this model the system use is directly determined by behavioral intention to use, which is in turn influenced by users' attitudes toward using the system and the perceived usefulness of the system. Attitudes and perceived usefulness are also affected by perceived ease of use. Perceived usefulness is defined as the extent to which a person believes that using a particular system will enhance his or her job performance while perceived ease of use is defined as the extent to which a person believes that using a particular system will be free of effort (Davis, Bagozzi, & Warshaw, 1989). Perceived usefulness directly influences intention to use, while perceived ease of use has an indirect effect through perceived usefulness and attitude on the behavioral intention. One key benefit of using TAM to understand system usage behavior is that it provides a framework to investigate the effects of external variables on system usage (Hong, Thong, Wong, & Tam, 2001). Several important external variables that have received more and more attention in the context of TAM research are individual differences, such as computer self-efficacy (Agarwal & Prasad, 1999; Hong et al., 2001; Venkatesh, Morris, & Ackerman, 2000).

2.2.2. The theory of reasoned action (TRA) The theory of reasoned action (TRA), developed by Fishbein and Ajzen (1975), is probably one of the most influential theories used to explain human behavior (Venkatesh, Ramesh, & Massey, 2003). According to TRA, the behavioral intention can be explained by two determinant factors: a personal factor termed attitude toward behavior, and a person's perception of social pressures termed subjective norm (Fishbein & Ajzen, 1975). The attitude is populated to be the first antecedent of behavioral intention. It is “an individual's positive or negative feelings (evaluative effect) about performing the target behavior” (Fishbein & Ajzen, 1975). An individual will intend to perform a certain behavior when he or she evaluates it positively. Attitudes are determined by the individual's beliefs about the consequences of performing the behavior (behavioral beliefs), weighted by his or her evaluation of those consequences (outcome evaluations). Subjective norm refers to perception that important others who really matter to the individual think that he either should or should not perform the behavior in question (Fishbein & Ajzen, 1975). Important others might be a person's, spouse, close friends, etc.

2.2.3. The theory of planned behavior (TPB) The theory of planned behavior (TPB) was proposed by Ajzen (1985) as an extension of the theory of reasoned action (Fishbein & Ajzen, 1975) for conditions where individuals do not have complete control over their behavior (Ajzen, 1991). The TPB suggests that in addition to attitudinal and normative influence, a third antecedent to the theory called perceived behavioral control, perceived behavioral (PBC), also influences behavioral intentions and actual behavior (see Fig. 2). This construct reflects to the degree to which an individual feels that performance or non performance of the behavior in question is under his or her volitional control. Perceived behavioral control indicates that a person's motivation is influenced by how difficult the behaviors are perceived to be, as well as the perception of how successfully the individual can, or cannot, perform the activity. Perceived behavioral control can influence behavior directly or indirectly through behavioral intentions.

3. Research model and hypothesis 3.1. Research model Based on the literature review and integrating TAM and TPB, a model indicating the adoption of online banking was developed (Fig. 1). The model consists of nine constructs that we posit to have an effect on adoption of online banking. These constructs include: perceived of use, perceived ease of use, security and privacy, self efficacy, government support, and technology support as independent variables. Attitude, subjective norm, and perceived behavioral control were used as intervening variables, and intention to use as the dependent variable. We will test the strength of the hypothesized relationships embedded in the theoretical model and the robustness of the model in predicting customers' intention to adopt Internet banking in Tunisia. The theoretical model is graphically presented in Fig. 1.

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Percevied usefulness

Perceived ease of use

Attitude

Security and privacy Subjective norm

Intention to use IB

Self efficacy

Government support

Perceived behavioral control

Technology support Fig. 1. The proposed research model.

3.2. The development of hypotheses 3.2.1. Hypotheses about TAM and TPB Based on the theoretical model developed in Section 2, we formulated the following research hypotheses. TAM and TPB are used as the base models to explain adoption of Internet banking we need to test the following TAM and TPB hypotheses. Hypotheses 1, 2, 3, 4, and 5 are proposed based on TAM and hypotheses 7 and 8 based on TPB as discussed in Section 2. H1. Perceived usefulness has a positive effect on intention to use Internet banking. H2. Attitude has a positive effect on intention to use Internet banking. H3. Perceived usefulness has a positive effect on consumer attitudes toward the use of Internet banking. H4. Perceived ease of use has a positive effect on consumer attitudes toward the use of online banking. H5. Perceived ease of use has a positive effect on consumer perceived usefulness of the use of online banking. H7. Social norm has a positive effect on consumer intention to use of Internet banking. H8. Perceived behavior control has a positive effect on consumer intention to use Internet banking.

3.2.2. Hypotheses of security and privacy The importance of security and privacy to the acceptance of online banking has been noted in many banking studies (Black, Lockett, Winklhofer, & McKechnie, 2002; Giglio, 2002; Hamlet & Strube, 2000; Howcroft, Hamilton, & Hewer, 2002; Polatoglu & Ekin, 2001; Roboff & Charles, 1998; Sathye, 1999; Tan & Teo, 2000). Privacy is defined as the ability to control and manage information about oneself (Belanger, Hiller, & Smith, 2002). Consumer information includes their declared data such as name, gender, address, and the other is consumer online behavioral data. All of this information could help online bankers to create a more detailed picture of each customer, and marketing strategies of successful firms increasingly depend on the effective use of vast amounts of detailed customer data (Culnan & Armstrong, 1999). Security is being defined as a threat which creates “circumstance, condition, or event with the potential to cause economic hardship to data or network resources in the form of destruction, disclosure, modification of data, denial of service and/or fraud, waste, and abuse” (Kalakota & Winston, 1997).

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In the literature, privacy and security have been mixed together in a large body of research. There is very little research investigating the different impact of privacy and security partly due to the high correlation between them (Belanger et al., 2002). Security and privacy are one of the most challenging problems faced by customers who wish to trade in the ecommerce world (Dixit, 2010). They are increasingly more concerned about security and privacy issues (Howcroft et al., 2002). According to Howcroft et al. (2002), security and privacy are a significant impediment to the adoption of online banking. Further, it has been stated in other studies that the greatest challenge to the electronic banking sector will be winning the trust of customers over the issues of privacy and security (Bestavros, 2000; Furnell & Karweni, 1999). It is therefore hypothesized that: H6. Security and privacy have a positive effect on consumer attitudes toward the intention use Internet banking. 3.2.3. Hypotheses of computer self-efficacy In general, prior research has suggested a positive relationship between experience with computing technology and computer usage (Agarwal & Prasad, 1999; Harrison & Rainer, 1992; Levin & Gordon, 1989). Computer self-efficacy is defined as the judgment of one's ability to use a computer (Compeau & Higgins, 1995). The self-efficacy theory (Bandura, 1977) suggests that there are four source areas of information used by individuals when forming self-efficacy judgments. They are performance accomplishments, vicarious experience, verbal persuasion, and physiological state. According to Gist, Schwoerer, and Rosen (1989) self-efficacy is an important motivational variable, influencing effort persistence and motivation. On the one hand, individuals who feel less capable of handling a situation may resist it because of their feelings of inadequacy or discomfort. On the other hand, individuals with high self-efficacy will perceive the use of M-commerce to be user friendly and easy to use due to the effect of self-efficacy on the degree of effort, the persistence and the level of learning (Bandura, 1977), and will be less resistant to changes. Hence, self-efficacy will affect perceived behavior control of consumers adopting Internet banking. Therefore, it is reasonable to infer that computer self-efficacy positively influence perceived behavior control and intention to adopt Internet banking, and we hypothesized that: H9. Computer self-efficacy has a positive effect on consumer perceived behavior control of the use of Internet banking 3.2.4. Hypotheses of government support Tan and Teo (2000) cited by Goh (1995) stated that government can influence the adoption of new technologies depending on the level of support that they provide. Government support (GS) can play an intervention and leadership role in the diffusion of innovation (Tan & Teo, 2000). It is possible to measure the perception of individuals as to the level of support. The greater the level of government support perceived by an individual the more likely he or she would be to adopt Internet banking. The hypothesis thus formulated is: H10. Government support has a positive effect on perceived behavior control. 3.2.5. Hypotheses of technological support Technology support (TS) becomes easily and readily available as e-commerce applications such as Internet banking services become more feasible (Shih & Fang, 2004). In terms of Internet usage this would refer to technological resources and infrastructure that are available. Thus the perception as to the quality of Internet infrastructure could affect the perceived behavior control of individuals toward adopting Internet banking (Jaruwachirathanakul & Fink, 2005). The hypothesis formulated is thus: H11. Technology support has a positive effect on perceived behavior control. 4. Methodology The constructs in the model are operationalized from existing measures developed and employed in previous research. The survey items for perceived usefulness, attitude, and intention used in this study were adapted from Cheng, Lama, and Yeung (2006), containing four items for perceived usefulness and attitude and three items for intention to use Internet banking. The constructs of security and privacy were adopted from Pikkarainen, Pikkarainen, Karjaluoto, and Pahnila (2004), and included six items. Perceived behavior control and subjective norm were adapted from the measurements defined by Wu and Chen (2005), containing three items for each construct. The computer self efficacy survey items were adapted from the classical Compeau and Higgins (1995) study containing ten items. Government support and technology support were adopted from the measurements defined by Goh (1995) and Ko (1990) and Leong (1997), containing three items for each one. Demographic questions were adapted from (Yang, 2005). The demographic characteristics were measured in terms of gender, age, education, occupation, and experience using online banking. All the items are measured by using a five-point Likert

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scales with end points of “strongly disagree” and “strongly agree” that were used to examine participant's responses to these statements. 4.1. Sample profile Data collection took place in April 2011. The questionnaire was administered by meeting the respondents on a one-to-one and voluntarily asked to complete the questionnaire based on their perception of the Internet banking usage. The respondents engaged in this study, must have a bank account. The questionnaires were distributed to 284 respondents and were entered into SPSS version 18.0. 4.2. Findings Participants in the study were composed of 54.22% male and 45.78% female. Majority of the respondents were between 18 and 30 years old, which was 42.25% of the total respondents. Majority of the respondents were college or university graduates (87.32%). 89.34% of the respondents posses personal computers whereas only 9.7% on them don't. Moreover, 90.1% have Internet access (Table 1). 4.3. Data analysis and results The data analysis was realized with a two-step procedure of structural equation modeling (SEM) with confirmatory factor analysis (CFA) using LISREL 8.80. First, we examined the measurement model to assess convergent and discriminant validity. Second, we examined the structural model to investigate the strength and direction of the relationships among the theoretical constructs. 4.3.1. Analysis of the measurement model The initial results of the global measurement model do not have a good fit. Thus, we have introduce some modifications: one item from the security and privacy scale (SP6), one item from technology support (TSUP2) and five items from the self control efficacy scale (SCE1, SCE2, SCE4, SCE7 and SCE10) are eliminated in order to improve the fit of the measurement model. As a result of these refinements and purification, the initial measurement instrument of 42 items was reduced down to 35 items for the final, refined measurement model. To evaluate reliability and validity of the final measurement model, three criteria suggested by Fornell and Larcker (1981) were used: (1) All indicator factor loading (k) should be significant and exceed 0.5, (2) Construct reliabilities (Cronbach Alpha) should exceed 0.7, (3) Average variance extracted (AVE) by each construct should exceed the variance due to measurement error for the construct (e.g. AVE should exceed 0.5).

Table 1 Sample demographics. Means

Value

Frequency

Percentage (%)

Gender

Male Female 18 to 30 31 to 40 41 to 50 Primary Secondary College/university Yes No Executives Middle-staff employees Blue-collar workers Independents Students Yes No

154 130 120 94 66 8 28 248 254 30 154 36 10 14 70 266 18

54.22 45.78 42.25 33.09 24.26 2.82 9.86 87.32 89.34 10.66 54.22 12.67 3.52 4.93 24.64 90.1 9.9

Age

Education level

Possession computer Occupation

Internet access

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Table 2 Confirmatory factor analysis results for measurement model. Constructs

Items

Factor laoding

t-value

Average variance extracted

Cronbach alpha

Perceived usefulness

PU1 PU2 PU3 PU4 PEOU1 PEOU2 PEOU3 SP1 SP2 SP3 SP4 SP5 ATT1 ATT2 ATT3 ATT4 SN1 SN2 SN3 INT1 INT2 INT3 SCE1 SCE2 SCE3 SCE4 SCE5 GSUP1 GSUP2 GSUP3 TSUP1 TSUP2 PBC1 PBC2 PBC3

0.58 0.62 0.71 0.89 0.95 0.81 0.58 0.97 0.91 1.10 0.82 0.83 0.71 0.85 0.79 0.82 0.91 0.86 0.89 0.90 0.83 0.81 0.78 1.03 0.86 0.75 0.69 0.86 0.70 0.65 0.65 0.58 0.67 0.75 0.77

7.30 8.79 6.69 7.07 3.28 7.62 6.06 6.81 10.37 10.35 8.40 8.47 7.47 10.66 8.24 9.46 15.78 14.39 15.73 11.05 9.83 8.76 6.70 9.03 8.11 9.03 6.71 8.79 6.15 6.61 5.00 3.14 7.18 4.69 5.24

0.50425

0.797

0.63167

0.747

0.86806

0.838

0.63077

0.838

0.78660

0.916

0.71833

0.856

0.68950

0.840

0.55070

0.764

0.37945

0.714

0.53477

0.661

Perceived ease of use

Security and privacy

Attitude

Subjective norm

Intention to use IB

Self efficacy

Government support

Technology support Perceived behavioral control

The reliability readings for all variables are well above 0.6 which indicate internal consistency for all measurement. The result of CFA shows that all factor loadings are above 0.5 for all items, thus indicating convergent validity for all latent variables. The result of AVE is well above 0.5 and is significant at p = 0.001. This means that discriminant validity is supported for all constructs (Fornell & Larcker, 1981). The only value of the AVE which is less than 0.5 corresponds to the TSUP construct (0.379). This value may be due to the fact that we have only two items for this construct. In order to keep the general form of the basic model, we decide to keep the TSUP construct despite the low obtained value of AVE. The results, therefore, confirmed that our instrument had satisfactory construct validity. Table 2 summarizes the CFA results.

4.3.2. Analysis of the structural model Some common fit indices reported in structural equation modeling are designed to identify model goodness-of-fit. (see Table 2). In this study seven common measures of model fit were chosen. These include chi-square/degrees-of-freedom (χ 2/df), goodness-of-fit index (GFI), adjusted goodness-of-fit-index (AGFI), comparative fit index (CFI), normed fit index (NFI), incremental fit index (IFI), comparative fit index (CFI), and standardized root mean square error (RMSEA). Thus, this study followed these recommendations when comparing the two model fits (Table 3). The results of structural equation modeling obtained for the proposed conceptual model revealed a ratio of chi-square to the degree of freedom (χ2/df) of 1.979 (p b 0.001), goodness-of-fit index (GFI) of 0.91, adjusted goodness-of-fit index (AGFI) of 0.86, comparative fit index (CFI) of 0.92, normed fit index (NFI) of 0.86, and root mean square error of approximation (RMSEA) of 0.078. Generally, fit statistics greater than or equal to 0.9 for GFI, NFI, RFI, and CFI indicate a good model fit (Bagozzi, Yi, & Philips, 1991; Hair, Anderson, Tatham, & Black, 1998). Furthermore, RMSEA values ranging from 0.05 to 0.08 are acceptable (Hair et al., 1998); therefore, the RMSEA suggested that our model fit was acceptable. Other fit indices, except AGFI, indicated that our proposed model obtained an adequate model fit. Note that low AGFI and NFI statistics may have resulted from the small sample size used.

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Table 3 Chi-square results and goodness of fit indices for revised model. Fit indices

Norm

Absolute indices Scaled χ2 (χ2/df) Goodness of fit index (GFI) Adjusted of goodness of fit index (AGFI) Root mean square error of approximation (RMSEA)

Obtained value

>1 and b 5 >0.9 >0.9 b0.08

1.979 0.91 0.86 0.078

Incremental indices Comparative fit index (CFI) Normed fit index (NFI) Incremental fit index (IFI)

>0.9 >0.9 >0.9

0.92 0.86 0.92

Parcimonie indices AIC CAIC Expected cross-validation index (ECVI)

The lower by comparaison The lower by comparaison The lower by comparaison

530.86 799.86 3.76

(Hu & Bentler, 1999; Schumacher & Lomax, 2004)

4.4. Hypotheses testing Standardized parameter estimate from the revised model is presented in Fig. 2. Thus, H1 is supported when perceived of use is significantly and positively influencing intention to use Internet banking (β = 0.62, p b 0.1). Attitude is significantly and positively influencing intention to use Internet banking (β = 0.90, p b 0.001), thus, H2 is supported. Perceived usefulness is significantly and positively affecting attitude toward Internet banking (β = 1.29, p b 0.001) hence, supporting H3. Perceived ease of use is significantly and positively related to attitude to use Internet banking (β = 0.47, p b 0.05) thus, H4 is supported. Perceived ease of use is significantly and positively related to perceived of use to use Internet banking (β = 0.18, p b 0.05) thus, H5 is supported. Security and privacy are significantly and positively affecting attitude to use Internet banking (β = 0.59, p b 0.001) hence, supporting H6. Subjective norms are significantly and positively influencing intention to use Internet banking (β = 0.50, p b 0.001), hence, H7 is supported.

Percevied usefulness

H1 H3

H5

Perceived ease of use

H4

Attitude

H6

H2

Security and privacy Subjective norm Self efficacy

H7

Intention to use IB

H8 H9

Government support

H10

Perceived behavioral control

H11

Technology support Fig. 2. The proposed research model with hypothesis.

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Perceived behavioral control is significantly and positively influencing intention to use Internet banking (β = 0.77, p b 0.001) hence, H8 is supported. Self efficacy is significantly and positively influencing perceived behavioral control to use Internet banking (β = 0.41, p b 0.001) hence, H9 is supported. Government support is significantly and positively influencing perceived behavioral control to use Internet banking (β = 0.39, p b 0.001) hence, H10 is supported. Technology support is significantly and positively influencing perceived behavioral control to use Internet banking (β = 0.72, p b 0.001) hence, H11 is supported (Fig. 3).

5. Discussion This study adopted the TAM and TPB to examine the adoption of Internet banking in Tunisia. The results of this study show that perceived usefulness is found to be a significant determinant to predict the intention to use the Internet banking. This is similar to the TAM model, which has been applied in other adoption studies. Moreover, the result was consistent with Chiu, Lin, and Tang (2005a, 2005b) and Cheong and Park (2005). Chiu et al. (2005a, 2005b), Cheong and Park (2005) found that perceived usefulness positively influenced online purchase intentions. On the other hand, Cheong and Park (2005) found that perceived usefulness has a positive impact on intention to use M-Internet. The results also show that attitude has a significant effect on intention to use the Internet banking. This result is consistent with the original TAM model applied in other technology adoption studies and Theory of Planned Behavior. The findings in the study show that perceived ease of use has a significant effect on perceived usefulness and attitude toward Internet banking. The results is confirmed with the original TAM model, which suggests that perceived usefulness directly influences intention to use Internet banking, while perceived ease of use has an indirect effect through perceived usefulness and attitude on the behavioral intention to use Internet banking. The results also show that social norm has a significant effect on intention to use Internet banking. The result is confirmed with the study by Taylor and Todd (1995), Amin, Baba, and Muhammad (2007), and Venkatesh and Morris (2000) found social norm to be an important factor for IS acceptance and adoption in the early stages of introducing an innovation, when users have only limited direct experience from which to develop attitudes. Another finding from this study is that the perceived behavioral control influences the intention to adopt Internet banking. This is in line with the previous findings of Tan and Teo (2000) and Shih and Fang (2004), which found significant relationship between perceived behavioral control and Internet banking setting. Furthermore, the results also show that security and privacy have positive influence on the Internet banking. This is consistent with the findings of Sathye (1999), Mukti (2000), Chung and Paynter (2001), Sohail and Shanmugham (2004), Gerrard and Cunningham (2003, 2006), Sayar and Wolfe (2007), Sohail and Shaikh (2007), among others, which have reported that these factors have positive influences on the acceptance, constant use intension and satisfaction of innovations such as Internet banking, electronic commerce etc.

Percevied usefulness

0.62* H1

H3 H5

0.18 **

Perceived ease of use

1.29*** H4

Attitude

0.47*** H2

0.59*** H6

Security and privacy

0.90***

Subjective norm

H7 0.50***

Self efficacy H9

0.41*** H10

Government support

0.39***

H8

0.77***

Perceived behavioral control

0.72***

Technology support

H11

Fig. 3. Results of structural modeling analysis.

Intention to use IB

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Our results show that self efficacy has a positive effect on consumer perceived behavior control of the use of Internet banking. This is consistent with the findings of previous studies (Tan & Teo, 2000). Nor and Pearson (2008) found that the relationship between self efficacy and PBC is positive and significant. For government support this study shows a positive influence government support on perceived behavioral control. This is in line with the previous study of Tan and Teo (2000) that showed that the Government support has a significant and positive influence on perceived behavior control in banking setting. Finally, this study showed that technology support has a positive effect on perceived behavior control. This is consistent with the findings of Jaruwachirathanakul and Fink (2005), which have reported that the absence of the technology support and its development is likely to impede the Internet banking service.

6. Implications The results of this study present both theoretical and practical contributions. The model developed in this study represents an important improvement for TAM and TCB by adding four constructs, security and privacy, self efficacy, government support and technology support that have not been addressed by previous studies. The results show that intention to adopt Internet banking in Tunisia can be predicted by attitudinal factors (perceived usefulness, perceived ease of use and security and privacy), subjective norms and by perceived behavioral control factors (self efficacy, government support and technology support). The present study has many implications for future Internet banking research. First, the empirical results show that the security and privacy have a significant effect on attitude toward Internet banking, where self efficacy, government support and technology support have a positive and significant relationship with perceived behavior control. Second, the empirical results show that the integration of TAM and TPB has good explanatory power, to provide a comprehensive model to understand the antecedents of Internet banking adoption in Tunisia. In terms of managerial implications, this finding is particularly important for managers as they decide how to allocate resources to retain and expand their current customer base. Firstly, the banks should promote the advantages of online banking when compared to traditional ways of banking. In addition, it implies that banks need to make this technology easy to use. Secondly, security and privacy of Internet banking are one of the factors that play a role in determining adoption of Internet banking in Tunisia. Therefore banks in Tunisia should ensure that security and privacy of the Internet banking systems are properly developed and users should also be made aware that their systems are secured and consumers' personal and financial information is protected. Thirdly, to enhance self-efficacy in using Internet banking services, demonstrations via video presentations could be made at bank branches to showcase the user-friendliness of such services. Such initiatives will help customers to be more familiar with the bank and its Internet banking service, an important criterion in helping potential adopters' Internet; banking services (Tan & Teo, 2000). Fourthly, to encourage the use Internet banking services Tunisian government can help to ensure that there are clear regulations and laws on Internet banking transactions. Having a clear and solid law on this will ensure customers to be more confident in security and privacy to use Internet banking. The Tunisian government can also help the banking institution by ensuring a better Internet infrastructure (i.e. wireless network) and help to encourage users to use Internet banking (Chong, Ooi, Lin, & Tang, 2009). In addition, the government, as the statutory body should provide guidelines for Internet banking services and monitoring over banks operation to ensure their operation are legitimate (Abdul Hamid et al., 2007). Fifthly, the actual adoption of Internet banking in Tunisia is influenced by some individual characteristics (Has a home PC, has Internet access, college (university) degree and age between 18 and 30 years), these variables play an important role in determining the intention to use Internet banking. From the managerial point of view, Tunisian banks should first focus on those clients who already have a home PC, Internet access, more educated and younger since they are the most likely to adopt Internet banking.

7. Conclusion and future study This study aims to develop an extended TAM with a TPB model to the intention to use Internet banking in Tunisia. It gives a better understanding on the factors contributing to the Internet banking success, especially for a developing country such as Tunisia. The results show that the proposed model has a good explanatory power and confirms its robustness in predicting customers' intentions to use Internet banking. There are several limitations in this research study. First, the factors selected in this study may not cover all factors that could influence the adoption of the Internet banking in Tunisia. Therefore future studies can consider other factors, which might have an influence in the adoption of Internet banking services. Second, the demographic profiles of this study are of a group of relatively young age users. Future researchers can thus conduct a comparison between users from different age group for future studies. Third, the sample was comprised only of Internet banking users. Whether these results can be generalized to non-users or to dormant users of Internet banking will require additional future research.

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Appendix A. Survey instrument Please rate the following questions regarding the bank's Website service on the following scale: Strongly Disagree

Disagree

(1)

(2)

Sans opinion (3)

Agree

Strongly Agree

(4)

(5) (1)

(2)

(3)

(4)

(5)

(1)

(2)

(3)

(4)

(5)

(1)

(2)

(3)

(4)

(5)

(1) (1)

(2) (2)

(3) (3)

(4) (4)

(5) (5)

(1) (1)

(2) (2)

(3) (3)

(4) (4)

(5) (5)

(1)

(2)

(3)

(4)

(5)

Security and privacy SP1 I trust in the technology an online bank is using SP2 I trust in the ability of an online bank to protect my privacy

(1) (1)

(2) (2)

(3) (3)

(4) (4)

(5) (5)

SP3 SP4 SP5 SP6

I trust in an online bank as a bank Using an online bank is financially secure I am not worried about the security of an online bank Metters of security have no influence on using an online bank

(1) (1) (1) (1)

(2) (2) (2) (2)

(3) (3) (3) (3)

(4) (4) (4) (4)

(5) (5) (5) (5)

I think that using online banking is a good idea.

(1)

(2)

(3)

(4)

(5)

I think that using online banking for financial transactions would be a wise idea. I think that using online banking is pleasant. In my opinion, it is desirable to use online banking.

(1)

(2)

(3)

(4)

(5)

(1) (1)

(2) (2)

(3) (3)

(4) (4)

(5) (5)

(1)

(2)

(3)

(4)

(5)

(1)

(2)

(3)

(4)

(5)

(1)

(2)

(3)

(4)

(5)

(1)

(2)

(3)

(4)

(5)

(1)

(2)

(3)

(4)

(5)

(1)

(2)

(3)

(4)

(5)

(1)

(2)

(3)

(4)

(5)

(1)

(2)

(3)

(4)

(5)

(1)

(2)

(3)

(4)

(5)

(1)

(2)

(3)

(4)

(5)



Item

Perceived usefulness PU1 I think that using the online banking would enable me to accomplish my tasks more quickly. PU2 I think that using the online banking would make it easier for me to carry out my tasks. PU3 I think the online banking is useful. PU4 Overall, I think that using the online banking is advantageous. Perceived ease of use PEOU1 I think that learning to use online banking would be easy. PEOU2 I think that interaction with online banking does not require a lot of mental effort. PEOU3 I think that it is easy to use online banking to accomplish my banking tasks.

Attitude ATT1 ATT2 ATT3 ATT4

Subjective norm NS1 People who are important to me would think that I should use online banking. NS2 People who influence me would think that I should use online banking. NS3 People whose opinions are valued to me would prefer that I should use online banking. Self computer efficacy SCE1 I could complete my bank transaction using the internet banking, if there was no one around to tell me what to do. SCE2 I could complete my bank transaction using the internet banking, if I had never used a package like it before. SCE3 I could complete my bank transaction using the internet banking, if I had only the manuals or online help for reference. SCE4 I could complete my bank transaction using the internet banking, if I had seen someone else using it before trying it myself. SCE 5 I could complete my bank transaction using the internet banking, if I could call someone for help if I got stuck SEC6 I could complete my bank transaction using the internet banking, if someone had helped me get started SCE7 I could complete my bank transaction using the internet banking, if I had a lot of time to complete the job. SCE8 I could complete my bank transaction using the internet banking, if I had built-in help facility for assistance.

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Appendix A (continued)

N° Item Self computer efficacy SCE9 I could complete my bank transaction using the internet banking, if someone showed me low to do it first SCE10 I could complete my bank transaction using the internet banking, if I had used similar system before to do the same job. Government Support GSUP1 The government endorses Internet commerce in Tunisia. GSUP2 The Tunisian government is active in setting up the facilities to enable Internet commerce. GS UP3 The Tunisian government promotes the use of the Internet for commerce. Technology support TSUP1 Advances in Internet security technology provide for safer Internet banking. TSUP2 Faster Internet access speed is important for Internet banking TSUP3 Internet technology, like the Singapore ONE network, makes Internet banking more feasible. Perceived behavior control PBC1 I think that I would be able to use the online banking well for financial transactions. PBC2 I think that using online banking would be entirely within my control. PBC3 I think that I have the resources, knowledge, and ability to use online banking. Intention to use INT1 I would use the online banking for my banking needs. INT2 Using the online banking for handling my banking transactions is something I would do. INT4 I would see myself using the online banking for handling my banking transactions.

(1)

(2)

(3)

(4)

(5)

(1)

(2)

(3)

(4)

(5)

(1)

(2)

(3)

(4)

(5)

(1) (1)

(2) (2)

(3) (3)

(4) (4)

(5) (5)

(1)

(2)

(3)

(4)

(5)

(1)

(2)

(3)

(4)

(5)

(1) (1)

(2) (2)

(3) (3)

(4) (4)

(5) (5)

(1)

(2)

(3)

(4)

(5)

(1)

(2)

(3)

(4)

(5)

(1)

(2)

(3)

(4)

(5)

(1) (1)

(2) (2)

(3) (3)

(4) (4)

(5) (5)

(1)

(2)

(3)

(4)

(5)

Demographics characteristics D1 Are you a male or a female?  Male  Female D2 What is your age range?  18 to 30  31 to 40  41 to 50 D3 Do you own or have access to a computer?  Yes  No D4 Do you have Internet access at home?  Yes  No D5 What is your highest educational level attained?  Primary  Secondary  College/University D6 Which bank/s do you use for majority of your Internet banking services?  ………………………

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Appendix A (continued)

Acronyms Banks AB : Amen Bank ATB : Arab Tunisian Bank ATTIJARIBANK : Attijaribank BFT : Banque Franco Tunisienne BH : Banque de l’Habitat BIAT : Banque Internationale Arabe de Tunisie BNA : Banque Nationale Agricole BT : Banque de Tunisie BTE : Banque de Tunisie et des Emarates BTK : Banque Tuniso Koweitienne BTS : Banques Tunisiennes de Solidarité BZ : Banque Zitouna STB : Société Tunisienne des Banques TQB : Tunisian Qatari Bank UBCI : Union bancaire pour le Commerce et l’Industrie UIB : Union International des Banques

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