Success Factors of Indonesian SMEs

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E-mail: nurulindarti@ugm.ac.id. Marja Langenberg. Langenberg Advies bv, Den Haag,The Netherlands. CICAT, Delft University of Technology, The Netherlands.
FACTORS AFFECTING BUSINESS SUCCESS AMONG SMES: EMPIRICAL EVIDENCES FROM INDONESIA1

Nurul Indarti Small and Medium Enterprises Development Center (SMEDC), Gadjah Mada University, Yogyakarta, Indonesia E-mail: [email protected]

Marja Langenberg Langenberg Advies bv, Den Haag,The Netherlands CICAT, Delft University of Technology, The Netherlands E-mail: [email protected]

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Factors affecting business success among SMEs: Empirical evidences from Indonesia Abstract In Indonesia, despite the fact that some SMEs have been declining or stagnant, some others have been successful and growing. What factors affect business success among SMEs? The recent study aims to answer this main question. Based on survey to 100 SMEs, the study discloses that marketing, technology and capital access affect the business success in a positive way significantly, while legality does it in a negative direction. Altogether, independent variables explain 38.6% of the total variances. These findings suggest that to be successful SMEs, the owners of the SMEs should pay more attention to improve marketing strategy, to advance technology, and to get capital access. Other interested parties with development of SMEs such as government agencies, universities, and business service development (BDS) should also be prepared for giving assistances in those fields. Why does legality have a negative effect on business success? The speculative explanation may be complicated bureaucracy and legal aspect that takes too many resources of the SMEs to deal with. Simplification of bureaucracy and deregulation of legal aspects are also recommended to foster the development of the SMEs in Indonesian context. Keywords: SME, business success, success factor, Indonesia. Introduction Small- and medium-sized enterprises (SMEs) have long been believed to be important in supporting economics development within a country (e.g. Akhtar; CDASED, 1999; Mazzarol, Volery, Doss, & Thein, 1999). One of the important roles of SMEs in this context includes poverty alleviation through job creation. For instance, in the Netherlands, SMEs account 98.8% of all private sector companies, contribute 31.6% to Gross Domestic Product (GDP), and employ 55% of total workforce (EIM Business & Policy Research, 1999). In Italy, SMEs contribute to USD35 million in exports and absorb 2.2 million of national labors (Patrianila, 2003). Thai SMEs are increasingly seen as creator of new jobs (Swierczek & Ha, 2003) and Vietnamese SMEs employ 64% of industrial workforce. According to Indonesian statistics, in 2003, the number of Indonesian SMEs was 42.4 millions and they contribute to 56.7% of GDP, account 19,4% of total export, and employ 79 millions of work force (BPS & KUKM, 2003). Therefore, in ensuring the economic growth of a country, more attention should be paid into SMEs development. Increasing business competition, in particular against large and modern competitors, put SMEs in a vulnerable position. In Indonesia, most SMEs operate along traditional lines in production and marketing. It has been argued that the main problem for SMEs in developing countries is not their small size but their isolation, which hinders access to markets, as well as to information, finance and institutional support (Mead & Liedholm, 1998; Swierczek & Ha, 2003). Lack of capital, lack of skills, and problems in business development are of problems faced by Indonesian SMEs (Kementerian KUKM & BPS, 2004). This is also the case for Vietnamese SMEs. Internal limitation, including capital shortage, old equipment and outdated technology have hindered the development of SMEs (Swierczek & Ha, 2003). In Indonesia, despite the fact that some SMEs have been declined or stagnant, some others have been growing and successful. What factors affect business success among SMEs? The recent study aims to answer this main question. The rest of the paper is organized into six sections. The theoretical framework is presented in section two, followed by description of study methodology in section three. The 1.

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results of survey are expounded in section four and the followed by the discussion in subsequent section. The general conclusions and policy recommendations bring the paper to an end. Theoretical Framework Storey (1994) identified key components to be important in analyzing the growth of SMEs: the characteristics of the entrepreneurs; the characteristics of the SMEs; and the type of strategy associated with growth. Instead of the last component, we explore contextual elements of SME development. The theoretical framework is developed in line with these adjusted three components as depicted in Figure 1. Justification for each variable included in the model is explained in subsequent section. 2.

Characteristics of entrepreneur - Age - Gender - Work experience - Education Characteristics of SME - Origin of enterprise - Length time in operation - Size of enterprise - Capital source

Business success

Contextual variables - Marketing - Technology - Information access - Entrepreneurial readiness - Social network - Legality - Capital access - Government support - Business plan

Figure 1. Research model 2.1

Characteristics of the entrepreneur Several previous studies found that demographic characteristics, such age and gender, and individual background, such as education and former work experience, had an impact on entrepreneurial intention and endeavour (e.g. Kolvereid, 1996; Mazzarol et al., 1999). Age. Reynolds et al. (2000) found that individuals aged 25-44 years were the most entrepreneurially active. Finding from another study in India by Sinha (1996) disclosed that successful entrepreneur were relatively younger in age. In their study on Internet café entrepreneurs in Indonesia, Kristiansen, Furuholt, & Wahid (2003) found a significant correlation between age of the entrepreneur and business success. The older (>25 years old) entrepreneurs were more successful than the younger ones. Gender. Mazzarol et al. (1999) found that female were generally less likely to be founders of new business than male. Similarly, Kolvereid (1996) found that males had significantly higher entrepreneurial intentions than females.

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Work experience. Kolvereid (1996) found that individuals with prior entrepreneurial experience had significantly higher entrepreneurial intentions than those without such experience. Conversely, Mazzarol, et al. (1999) found that respondents with previous government employment experience were less likely to be successful founders of smallbusinesses. But, they did not investigate the relationship between previous employment experience in private companies and entrepreneurial intentions. Education. A research by Charney and Libecap (2000) found that entrepreneurship education produces self-sufficient enterprising individuals. Furthermore, they found that entrepreneurship education increases the formation of new ventures, the likelihood of selfemployment, the likelihood of developing new products, and the likelihood of self-employed graduates owning a high-technology business. Also, the study revealed that entrepreneurship education of employee increases the sales growth rates of emerging firms and graduates’ assets. Similarly, Sinha (1996) who analysed the educational background of the entrepreneur revealed that 72% of the successful entrepreneurs who had a minimum of technical qualification, whereas most (67%) of the unsuccessful entrepreneurs did not have any technical background. She summed up that entrepreneurs with business and technical educational background are in a better position to appreciate and analyse hard reality and deal with it intuitively, which seems to play a critical role in entrepreneurial effectiveness. 2.2

Characteristics of the SMEs Origin of enterprise. According to Smallbone, Leig, and North (1995), in small firms, where ownership and management were typically combined in one or more individuals, future goals for the business might be determined as much by personal lifestyle and family factors as by commercial considerations. Further, they concluded that one characteristic which did distinguish the best performing firms from other firms in the study was their commitment to growth. Also, they found another characteristic that did distinguish high growth firms from others was their propensity to acquire other businesses. Length time in operation. Length time in operation may be associated learning curve. Old players most probably have learned much from their experiences than have done by new comers. Kristiansen, Furuholt, & Wahid (2003) found that length time in operation was significantly linked to business success. Size of enterprise. Size of enterprise reflects how large an enterprise in employment terms. McMahon (2001) found that enterprise size significantly linked to better business performance. Larger enterprises were found to have a higher level of success. Capital source. In a study in Australia, McMahon (2001) discovered that greater dependence upon external finance associated with better business growth. In a more recent study, in Indonesia, Kristiansen, Furuholt, & Wahid (2003) found that financial flexibility was significantly correlated to business success. The SMEs that took advantage of family and third-party investment experienced higher level of success. 2.3

Contextual variables Marketing. In Indonesia, most SMEs operate along traditional lines in marketing. Stiffer competition in the market should be responded proactively by SMEs by doing market development. Access to market was of problems faced by SMEs (Mead & Liedholm, 1998; Swierczek & Ha, 2003). Market development is, therefore, crucial for preserving high growth in the business. Smallbone, Leig, and North (1995) in their study in UK found that the vast majority of the high growth SMEs had identified and responded to new market opportunities. New market opportunities included findings new products or services to offer existing customers and obtaining new customers for existing product or services. In a slightly different term, market stability (i.e. high proportion of regular customers) was found to be 4

significant in determining business success (Kristiansen et al., 2003). Furthermore, market orientation defined as organization culture creates the necessary behaviour for the creation of superior value to customers was found to be significantly correlated with company performance (Verhees & Meulenberg, 2004). More specifically, they pointed out market orientation is helpful in selection of an attractive product assortment when the SMEs operate in markets with relatively homogenous product. Technology. Rapid changes in technology should be responded by the SMEs to find alternative ways to sustain their competitive advantage by deploying new process and new growth methods. Technology may play an important role in this respect. In this context, technology has a close relationship with improvement of production process. Previous study has revealed that lack of equipment and outdated technology are among hindrances of SME development (Swierczek & Ha, 2003). In their study in US, Gundry, Kickul, Welsch, and Posig (2003) disclosed that technological change innovations had significant relationship with market growth. A study in Ireland unearthed that technological posture, automation, and process innovation were significantly linked to satisfaction on return on investment (ROI) (Gibbons & O'Connor, 2003). Information access. Availability of business information is similarly important for the intention to initiate a new enterprise. Singh and Krishna (1994), in their studies of entrepreneurship in India, pointed out that eagerness in information seeking is one of the major entrepreneurial characteristics. Information seeking refers to the frequency of contact that an individual makes with various sources of information. The result of this activity is most often dependent on information accessibility, either through individual efforts and human capital or as a part of a social capital and networking. Access to new information is indispensable for the initiation, survival and growth of firms (Duh, 2003; Kristiansen, 2002; Mead & Liedholm, 1998; Swierczek & Ha, 2003). Business information of special relevance for the perception of ability to succeed and thereby for entrepreneurial intention is related to markets and sources of inputs, technological solutions, design, and government rules and regulations. The availability of new information is found to be dependent on personal characteristics such as the level of education, infrastructure qualities such as media coverage and telecommunication systems, and on social capital such as networks (Kristiansen, 2003b). Entrepreneurial readiness. Entrepreneurial readiness in this study refers to selfefficacy. The term self-efficacy, derived from Bandura’s (1977) social learning theory, refers to a person’s belief in his or her capability to perform a given task. According to Ryan (1970), self-perception plays an important role in the development of intention. Intentions and their underlying attitudes are perception-based, which should mean that they are learned and can be continuously influenced, and not fixed by personality traits formed in early childhood. Accordingly, they will vary across historical and cultural contexts. Cromie (2000) stated that self-efficacy affects a person’s beliefs regarding whether or not certain goals may be attained. The attitude provides the foundation for human motivation (Pajares, 2002) and personal accomplishment: unless people believe that their actions can produce the outcomes they desire, they have little incentive to act or to persevere in the face of adversities (Pajares, 2002). Bandura (1977, p. 2) pointed to the fact that ‘people’s level of motivation, affective status and actions are based more on what they believe than on what is objectively true’. An individual’s perception of self-efficacy has a strong influence on how he or she will act and how the available knowledge and skills will be utilized. Consequently, people behave according to beliefs about their capabilities rather than on real facts based on their competence and capabilities. In their study among Norwegian and Indonesian students, Kriatinsen and Indarti (2004) found a significant correlation between self-efficacy and entrepreneurial intention. In their study of Internet café entrepreneurs in Indonesia, 5

Kristiansen, Furuholt, and Wahid (2003) also found that entrepreneurial readiness was linked significantly to business success. Social network. Social networks have an impact on the likelihood of successful entrepreneurial endeavour. The study of entrepreneurship has increasingly reflected the general agreement that entrepreneurs and new companies must engage in networks to survive (Huggins, 2000). Networks represent a means for entrepreneurs to reduce risks and transaction costs and also to improve access to business ideas, knowledge and capital (Aldrich & Zimmer, 1986). A social network consists of a series of formal and informal ties between the central actor and other actors in a circle of acquaintances and represents channels through which entrepreneurs get access to the necessary resources for business start-up, growth and success (Kristiansen, 2003). In his study in Tanzania among small-scale garment and carpentry industries, Kristiansen (2003a) found that social network has significant relationship with business adaptability. Legality. Not many studies have been conducted to examine direct relationship between legal aspect readiness and business success. Legal aspect in developing countries in Indonesia is probably of hindrances of success among SMEs. In many cases, dealing with legal aspects has forced the SMEs to allocate significant amount of financial resources due to bribery practices. Legal aspect is often also used in selection operating decision in order to ensure future business success (Mazzarol & Choo, 2003). Unsuitable legislation is also found of obstacles faced by Slovenian SMEs (Duh, 2003). Capital access. Access to capital is obviously one of the typical obstacles to the start-up of new businesses, not least in developing economies with weak credit and venture capital institutions. Several empirical studies have concluded that the lack of access to capital and credit schemes and the constraints of financial systems are regarded by potential entrepreneurs as main hindrances to business innovation and success in developing economies (Marsden, 1992; Meier & Pilgrim, 1994; Steel, 1994). Potential sources of capital may be personal savings, extended family networks, community saving and credit systems, or financial institutions and banks. Robinson (1993) found that informal sources of credit, though with high interest rates, constitute very substantial contributions to business start-ups in developing countries, where the capital to labour ratio is normally low and small amounts of capital may be sufficient for a business start-up. In developed economies with efficient financial infrastructure, access to capital may represent similar restrictions to individuals’ perception of entrepreneurial options because of the high entry barrier ensuing from high capital to labour ratios in most industries. As aforementioned, lack of capital is of problems faced by Indonesian SMEs (Kementerian KUKM & BPS, 2004). A more recent study among Vietnamese SMEs revealed that of internal limitations that hinder SMEs to succeed is capital shortage (Swierczek & Ha, 2003). Hence, capital flexibility as abovementioned is of factors determining business success (Kristiansen, Furuholt & Wahid, 2003). Government support. Many governments in the world (e.g. Chaston, 1992; Mulhern, 1996; Patrianila, 2003) have been paying a more attention to SME development in order to strengthen national economy. Indonesian government, through Ministry for Cooperative and Small- and Medium-sized Enterprises have launched many programs (e.g. giving financial assistance) dedicated to SME development (Kementerian KUKM, 2003). The programs were proven to be significant in Indonesian SMEs development (Kementerian KUKM & BPS, 2004). In short, government support is of necessary condition to foster SMEs development. Government regulations are identified by Reynolds, Day, and Lancaster (2001) to be one of the top problems faced UK SMEs. In addition to lack of financial support as abovementioned, lack of institutional support was of hindrances of SME development (Mead & Liedholm, 1998; Swierczek & Ha, 2003). 6

Business plan. Insufficient awareness of the need for a business plan was identified as one problem at the start-up phase among SMEs (Chaston, 1992). In this context, business plan can also be regarded as development orientation. McMahon (2001) revealed that greater development orientation significantly linked to better business growth. In line with this, Smallbone, Leig, & North (1995) pointed out that one characteristics that distinguished the best performing enterprises from other was their commitment to change. Therefore, we believed that well-planned business activities as manifested in a business plan will yield a better business performance. Research Methods 3.1 Research instrument This study can be regarded as explanatory study since the focus is on identification of success factors of Indonesian SMEs. The questionnaire was the main instrument of the study, though some in-depth interviews were also conducted to grasp the dynamic of entrepreneurial process among SMEs2. Inputs from one-day seminar attended by 25 entrepreneurs were used as a basis for developing the questionnaire. The questionnaire consisted of three parts. The first part comprised demographic information of the respondents and a set of items to measure business success. Five-point Likert scale anchored by strongly disagree and strongly agree were applied to measure the perceived success that comprised four items: “I am satisfied with the growth of net-income of the business”, “I am satisfied with the time needed to reach break event point (payback period)”, “I consider my business successful”, and “I consider my business growing”. In the second part, the respondents were asked to score the importance of nine factors considered to partake in determining business success using 5-point Likert scale anchored by very unimportant to very important. The factors were marketing, technology, information access, capital access, social network, legality, business plan, entrepreneurial readiness, and government support. The respondents were asked to rank statement on contextual condition related to each success factor faced by the respondents in the third part. This part consisted of 31 items which were intended to measure factors of business success. 3.

3.2

Sample and data collection The number of respondents was 100 owners of the SMEs. According to Indonesian Statistics, an enterprise with less than 100 employees is considered as SME. Purposive sampling procedure was used to select the respondents from SME database comprised 250 SMEs in Yogyakarta, Indonesia, compiled by Small and Medium Enterprises Development Center (SMEDC), Gadjah Mada University. Yogyakarta is a good sample of Indonesia as the people come from all corners of Indonesia to get either better education or living. Yogyakarta is typically one of Indonesian big cities where we can only find a few large enterprises therein. Most economic activities are run by SMEs. In filling in the questionnaire, personal interviews were deployed. In case such an interview was impossible practically, “drop and collect” procedure then was chosen. This procedure was selected to get a high response rate. In case of some values were missing, we re-asked the respondents by telephone to supply the missing ones. Not surprisingly, the response rate was 100% and all returned questionnaires were usable for analyses. In addition to quantitative data collected using the questionnaire, 20 semi structured interviews were conducted3. At average, each interview lasted for two hours. At average, the number of full-time workers of each SME was 17 ranged from 1 to 70, while the number of part-time workers was 19 varied from 1 to 150. However, a large percentage (>70%) of the SMEs employed less than 20 full-time workers which could be 7

categorized as small enterprises according to Indonesian Statistics. Table 1 comprises the background of the entrepreneur and the enterprises. As can be seen in Table 1, most entrepreneurs (71%) were male. As regards their education, the vast majority of the respondents (75%) had senior high or university educations. A large percentage (63%) of the entrepreneurs had no former work experience prior to running the business which was mostly (85%) established by themselves. Obviously, personal savings (56%) and family investment (23) were the dominant source of capital. Most SMEs (54%) were running in crafts and arts industry. Table 1. Background information Variable Gender - Female - Male Education of the entrepreneur - Elementary - Junior high - Senior high - University Previous experience - Yes - Never Origin of SMEs - Established - Inherited - Other Source of capital - Personal savings - Joint venture with colleagues/friends - Family investment - Third party investment - Bank - Other Industry sector - Crafts and arts - Agribusiness - Food processing - Service - Trading - Other

% 29 71 12 12 38 37 37 63 85 12 3 56 3 23 2 3 12 54 6 12 15 3 10

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Data analysis methods In addition to descriptive statistics, we employed correlation and regression analyses. Before applying regression analysis, the validity and reliability of the research instrument were examined using factor analyses and values of Cronbach’s alpha. More specifically, in correlation analyses, t-test and ANOVA were used as appropriate. Correlation analyses were used to examine relationship between characteristic of the entrepreneurs and SMEs and business success, while regression analysis was employed to look at relationship between contextual variables and business success. Post hoc test using LSD (least significant differences) method was also applied when ANOVA revealed significant differences among groups compared. 8

Results 4.1 Validity and reliability of the instrument Factor analysis applied to items used to measure business success revealed one variable. Value of Cronbach’s’ alpha of the items was 0.81. Hence, we could conclude that the items were valid and reliable measurement for business success. Using exploratory factor analysis, 31 items in the questionnaire were trapped into 10 variables. Each variable consisted at least two items except one; X1 (see Appendix). Hence, we ignored it in further analysis since it has been represented by the items in marketing variable. The result of exploratory factor analysis after deleting M1 is presented in Table 2. Table 3 depicts values of Cronbach’s alpha of the instrument. With exception on social network, the values of Cronbach’s alpha were greater than 0.6 – or even 0.5 for exploratory study – which was considered as acceptable ones (Nunally, 1978). Taken together, we concluded that the research instrument used in the study was valid and reliable. 4.

Table 2. Factor loadings Item X14 X16 X15 X12 X11 X8 X13 X6 X5 X7 X2 X18 X28 X17 X3 X23 X24 X4 X26 X25 X27 X21 X22 X30 X29 X31 X10 X9 X19 X20 % variance explained

INFO 0.82 0.67 0.66 0.65 0.63 0.50 0.50 0.20 0.10 0.37 0.02 0.26 0.09 0.44 0.01 0.05 0.19 -0.06 0.03 0.18 -0.02 0.05 0.01 0.34 0.02 0.17 0.22 0.08 0.05 -0.01

TECH 0.20 0.06 0.39 -0.01 0.11 0.43 0.03 0.85 0.80 0.60 0.13 0.18 0.34 -0.07 -0.18 0.15 0.18 -0.09 0.06 0.13 0.12 0.02 0.17 0.10 0.07 0.04 0.23 0.12 0.29 -0.16

MARK 0.15 -0.12 0.18 0.52 0.08 0.00 0.25 0.13 0.12 -0.03 0.76 0.74 0.53 0.51 0.50 0.10 -0.05 0.17 -0.04 -0.09 0.28 0.16 -0.12 -0.04 0.07 -0.04 0.07 -0.18 0.09 -0.22

BPLA -0.11 0.19 0.06 0.27 -0.06 0.30 -0.25 0.05 0.03 0.17 0.00 0.03 0.23 0.11 0.37 0.80 0.77 0.75 0.21 0.11 0.10 0.03 0.14 -0.10 0.06 0.16 0.10 0.08 0.03 0.18

EREA 0.14 0.01 -0.10 0.02 0.30 0.14 0.28 0.13 0.22 0.05 0.04 -0.03 0.43 0.03 -0.02 0.18 0.17 0.09 0.80 0.78 0.77 -0.08 0.11 0.07 -0.01 0.06 -0.03 0.22 -0.02 0.12

LEGA 0.06 0.27 0.03 0.01 -0.13 0.09 -0.17 0.11 0.11 0.08 -0.01 -0.07 0.00 0.05 0.17 0.09 -0.02 0.05 -0.01 -0.07 0.23 0.87 0.80 0.67 0.15 0.26 -0.01 0.05 -0.08 0.19

GOVS -0.04 0.07 0.11 0.10 0.32 -0.01 0.29 0.15 0.02 0.00 -0.04 0.07 0.01 -0.02 0.08 -0.02 0.06 0.13 0.12 0.02 -0.10 0.15 0.11 0.48 0.89 0.86 0.04 -0.01 0.08 -0.01

CAPI 0.14 0.08 -0.10 0.03 0.34 0.25 0.42 0.06 0.23 0.19 -0.04 -0.15 -0.18 0.24 0.35 0.00 0.13 0.02 0.08 0.05 0.11 0.07 -0.04 0.01 0.06 0.00 0.79 0.70 0.23 0.07

SOCN -0.03 0.17 -0.08 -0.08 0.07 -0.27 0.14 0.16 0.11 -0.37 -0.27 0.34 -0.08 0.28 -0.19 -0.07 0.10 0.20 0.12 0.00 -0.06 0.11 0.01 -0.13 0.15 -0.08 0.05 0.21 0.72 0.69

23.62

9.08

8.46

7.67

6.55

5.21

4.88

3.98

3.65

Notes: - INFO: Information access, TECH: Technology, MARK: Marketing, BPLA: Business plan, EREA: Entrepreneurial readiness, LEGA: Legality, GOVS: Government support, CAPI: Capital access, SOCN: Social network. - Extraction method: Principal Component Analysis; Rotation method: Varimax with Kaiser Normalization.

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Table 3. Reliability test No 1 2 3 4 5 6 7 8 9

Variable Information access Technology Marketing Business plan Entrepreneurial readiness Legality Government support Capital access Social network

No of items 6 3 5 3 3 3 2 3 2

Cronbach’s alpha 0.83 0.82 0.70 0.78 0.77 0.81 0.85 0.66 0.46

4.2

Data analysis Table 4 summarizes mean ratings that indicated perceived importance of variables related to business. Capital access (mean=4.56), marketing (4.55), and information access (4.53) were considered to be most important factors in running the business, while social network (4.02) was perceived to be less important in business operation. Table 4. Mean ratings No 1 2 3 4 5 6 7 8 9

Variable Capital access Marketing Information access Entrepreneurial readiness Government support Legality Business plan Technology Social network

Mean 4.56 4.55 4.53 4.43 4.33 4.07 4.07 4.07 4.02

Standard deviation 0.78 0.82 0.69 0.81 0.90 0.96 1.01 1.05 1.04

Regression analysis then was employed to examine the relationship between nine independent variables (see Table 2) and business success. Values of independent variables were calculated by multiplying the perceived importance of each variable (as depicted in Table 4) and the value of the independent variables obtained by averaging the values of items comprise the variable. The results of regression analysis are summarized in Table 5. Table 5. Regression results Variable Information access Technology Marketing Business plan Entrepreneurial readiness Legality Government support Capital access Social network Model summary Adjusted R2 = 32.5% F = 6.29***

Beta 0.107 0.182* 0.370*** -0.127 0.069 -0.277** 0.036 0.302*** -0.020

Notes: *p