The influence of the institutional environment on entrepreneurial intentions in an emerging economy Gordon Shaw Chair in Entrepreneurship University of Fort Hare [email protected]

Boris Urban Professor of Entrepreneurship Wits Business School, University of the Witwatersrand PO Box 98, Wits, 2050 [email protected]

Abstract: Building on the literature on institutional profiles this paper examines regulatory, normative and cognitive institutional dimensions which may influence entrepreneurial intentions in an emerging market context. By accessing relevant theoretical foundations and contextualising the study in an emerging market context, hypotheses are tested using correlational and regression analyses. Results from a sample of 199 respondents indicates that perceptions of favourability of the different institutional profiles were positively but not significantly correlated with entrepreneurial intentions. Public policy makers and market entrants need to be aware of the less than favourable conditions for entrepreneurship in emerging markets, and of the numerous and often conflicting institutional pressures and constraints facing potential entrepreneurs.

Keywords: institutional profiles, entrepreneurial intention,

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Introduction In recent years development economists have turned towards unpacking the concept of „institutions‟ as the ultimate determinant of development (Naude, 2007, 2010a). Institutions are seen as the „rules of the game‟ and include property rights, contract enforcement, and good governance (North, 1990). The nature and quality of institutions in a country determine whether or not individuals will pursue entrepreneurial activity (Shane, 2003). Thus this institutional environment (the socio-economic and political milieu in which an entrepreneur operates) influences people‟s willingness to engage in socially productive activity (Luiz, 2008). Furthermore, the institutional environment determines the process of gaining cognitive and socio-political legitimacy, which is critical for entrepreneurial organisations to overcome the liabilities of newness (Stinchcombe, 1965), smallness (Aldrich and Auster, 1986), to increase their survival prospects (Freeman, Carroll, and Hannan, 1983; Manolova, Eunni and Gyoshev, 2008) and to gain cooperative exchanges in business networks (Besser and Miller, 2010). Acknowledging earlier work on institutions, where North (1990) and Scott (1995) classified the formal and informal institutions that impact organisations and organisational actors into regulatory, normative, and cognitive categories, this study builds in this direction by investigating how perceptions of institutional profiles may influence entrepreneurial intentions. Regulatory institutions refer to the formally codified, enacted, and enforced structure of laws in a community, society, or nation. Less formal are the normative institutions, which typically manifest in standards and commercial conventions such as those established by professional and trade associations, and business groups. Cognitive institutions inform the axiomatic beliefs about the expected standards of behaviour that are specific to a culture; which are typically learned through social interactions by living or growing up in a community or society.

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It is further noted that idiosyncrasies in the institutional profiles of emerging economies contrast with those of the developed market economies, generally characterised by a well established regulatory basis, a long tradition of management in a market-based competition, along with societal acceptance and support for entrepreneurship (Manolova, Eunni and Gyoshev, 2008). Recognising the importance of the institutional environment to entrepreneurship there is a need to analyse how contextual variables differ in emerging economies and to what degree they shape entrepreneurial goals, behaviours, and intentions. A theory is more powerful if its applicability is established in different settings. Emerging economies are unique environments that offer the ability to obtain fresh insights, expand theory and increase understanding by incorporating more contextualised considerations (Bruton, Ahlstrom and Obloj, 2008). Recognising the gap in literature on institutional profiles in an emerging economy context, the aim of this study is to investigate perceptions of formal and informal institutions in terms of the regulatory, normative, and cognitive categories which may influence entrepreneurial intentions. Researching the relationship between institutions and intentions is important for entrepreneurship, as the institutional environment defines, creates, and limits entrepreneurial aspirations, intentions, and opportunities, and thus affects the speed and scope of entrepreneurial entry rates (Shane, 2003). Indeed it has been suggested that the entire entrepreneurial process unfolds because individual entrepreneurs act and are motivated to pursue opportunities (Gaglio and Katz 2001; Gartner 1990; Shane and Venkataraman 2000). Intentions predict innovation adoption behaviour and in cognitive motivation people motivate themselves and guide their actions in anticipation through the exercise of forethought or intention (Bandura 1997; Santos, Curral and Caetano, 2010). This study extends earlier research which suggests that the setting up of new firms by intending individuals is moderated and mediated by personal circumstances, by individual cognitions of new business opportunities (Busenitz and Lau 1996; Mitchell, Busenitz and

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Lant et al. 2002), and by broader environmental factors at both individual and national institutional levels (Davidsson and Wiklund 1997; Dutta and Thornhill 2007). To the degree therefore that a countries‟ context and institutions may influence the behaviours, occupation patterns, and outcome effects of entrepreneurs, the research question then becomes: to what extent does the institutional environment, in terms of the regulatory, normative and cognitive profiles, affects entrepreneurial intentions in an emerging market context. Undertaking this research is important, noted by Manolova, Eunni and Gyoshev (2008), as a large part of research on institutions and entrepreneurship have been either case-based, or predominantly examined the regulatory (formal) environment. Empirical research investigating the complex effect of the institutional environment for unlocking entrepreneurial phenomena in emerging economies is important. New ventures offer the promise of empowering marginalised segments of the population in these economies. New ventures are pivotal to the growth and development of the South African economy, and inextricably linked to economic empowerment, job creation, and employment within disadvantaged communities (Gauteng Provincial Government, 2008).Thus, whereas there may be a genuine appreciation of the role of entrepreneurship in the economic development process in literature, the attention has been largely confined to advanced economies (Naude, 2010). This study will allow researchers to compare and examine different institutional profiles in similar environmental contexts. The rest of the article is structured as follows. First, relevant theoretical foundations are accessed to provide a basis for the hypotheses which are formulated on existing theory. Next, the research approach is delineated in terms of sampling, measures and analytical techniques used. Results and implications follow, the study‟s limitations are addressed and avenues for future research suggested.

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The institutional environment and entrepreneurship Institutions, defined broadly as the „rules of the game‟ are seen to include property rights, contract enforcement, and good governance (North, 1990). Institutions can be described as relatively widely diffused practices, technologies, or rules of social interaction that have become entrenched in the sense that it is costly to choose alternative practices, technologies, or rules (Welter and Smallbone, 2011). The institutional framework of a society comprises the fundamental political, social, and legal ground rules that establish the basis for production and distribution, and organisations must conform to it if they are to receive support and legitimacy (North, 1990). Thus institutions are seen as conducive to good policies, which in turn will facilitate accumulation of capital and labour (for a discussion in the African context see, Naudé 2004). Economists would argue that there is a strong case to be made that entrepreneurship is itself a consequence of the adoption and development of institutions that encourage entrepreneurial behaviour (Luiz, 2008; Stiglitz, 2006). This in turn will stimulate economic development and growth and where in order to stimulate entrepreneurship we should focus on getting the institutions right (Luiz, 2008). With poor institutions, transaction costs in the economy will be high (for instance informal networks might need to substitute for contract enforcement) and there may be less productive entrepreneurs and more evasive entrepreneurs (avoiding predatory governments) and even more unproductive and destructive entrepreneurs (they might find it more lucrative to become politicians or to bribe politicians to share in rents, than add new value). With less productive entrepreneurs there may be less demand for labour and more self-employed „necessity‟ entrepreneurs – creating a vicious cycle (Naude, 2007). Baumol (1990) illustrates, by using historical evidence that entrepreneurs respond to the incentive structures underpinning an economy. Institutional factors provide incentives for rent-seeking entrepreneurial activities (such as crime and corruption) versus socially

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productive entrepreneurial activities (such as the establishment of new enterprises) (Shane 2003). When property rights and the rule of law are secure and the institutional environment is such that it does not suppress legitimate entrepreneurial activity, then entrepreneurs will respond appropriately through socially productive investment (Baumol, 1990). Indeed productive and unproductive entrepreneurial activities may be seen to be substitutes and the choices depend upon the governing incentive structure – both formal and informal (Luiz, 2008). According to Stiglitz (2006) it is precisely because Africa has so many of its countries as rent economies (being dependent on natural resource exports) that conflicts are so frequent. Many developing countries are sitting atop enormous wealth, both physical and human, which they are not tapping into because of unsuitable environments. Fadahunsi and Rosa (2002) investigate this hypothesis using Nigerian traders as a case study, and they found that the lack of rule of law and property rights led entrepreneurs to engage in corruption to make possible their entrepreneurial endeavours. The importance of bribery to successful entrepreneurial action also led to the widely held view of Nigerian society of accepting illegal behaviour as justifiable aspects of business activity (Shane 2003). Given this understanding of entrepreneurship, the policy implication is that efforts to increase the supply of entrepreneurship itself may be less important than efforts to change the allocation of entrepreneurial effort into productive entrepreneurship (Baumol 1990). The formation of entrepreneurial start ups is often cited as the most effective way to relocate labour and capital in a transition economy (Luthans, Stajkovic and Ibrayeva, 2000), with recent research among European countries in transition emphasising the point that entrepreneurship exists in every country and this spirit can be fostered with an appropriate institutional framework. Consistent with the notion that the institutional environment does indeed affect entrepreneurial intentions, the next section investigates this link further as

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intentions reflect a person‟s willingness to pursue a certain course of behaviour, taking cognisance of constraints imposed by the external environment (institutional) or the individual‟s background/abilities.

Entrepreneurial Intentions An established body of research suggests that intention to start a venture is central to entrepreneurship (Bird, 1988; Boyd and Vozikis, 1994; Gist and Mitchell, 1992; Krueger, 1993; Krueger, Reilly and Carsrud, 2000; Urban, 2006, 2010). Review of the literature finds strong arguments for intentions, with existing applications of intentional models showing consistent support (Krueger and Brazeal, 1994). Krueger (1993) defines entrepreneurial intentions as a commitment to starting a new business. This is accepted as a more encompassing concept than merely to own a business, since the creation of a venture is central to the definition of entrepreneurship. Two intention-based models that are widely recognised, and offer a well-developed theory base, are Ajzen's (1991) theory of planned behaviour (TPB) and Shapero's (1982) model of entrepreneurial event (SEE). These models which have considerable overlap, suggest that to encourage new venture creation, it is important first to increase perceptions of feasibility and desirability (Krueger et al., 2000; Kruger and Dickson, 1994). Starting a business or initiating a new venture is often described as purposive and with intentional choice. Attitudes influence behaviour by impacting on intentions. Path analysis confirms that the correlation between attitudes and behaviour is explained by attitude – intentions, and intentions – behaviour links (Kim and Hunter, 1993). Individuals with entrepreneurial intent may be distinguished from those who merely have an entrepreneurial disposition or personality by virtue of their having, first, given some degree of conscious consideration to the possibility of themselves starting a new business at some stage in the

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future, and then, second, having not rejected such a possibility. Those with an entrepreneurial disposition but who do not possess entrepreneurial intent may either not yet have gotten around consciously to considering setting up a new business, or, alternatively, may have considered the possibility, but, for various reasons not started (Thompson 2009).

Contextualizing the study: Institutions and intentions in South Africa Since 1994 the South African government has acknowledged the important role in fostering an enabling environment for the creation and growth of new ventures. A number of support institutions and measures have been put in place, with a recent strategic move to integrate a wider group of institutions into the realm of small-enterprise development (Gauteng Provincial Government, 2008). Central to strategic actions and institutional arrangements, and to the shift from uncoordinated to integrated service delivery, is the broadening of support programmes and the streamlining of support institutions. These relate to the legal and regulatory environment, access to markets, access to finance and affordable business premises, the acquisition of skills and managerial expertise, access to appropriate technology, the tax burden, and access to quality business infrastructure in poor areas or poverty nodes. To further elucidate the nature of the institutional environment and its impact on potential entrepreneurs, the regulatory, normative, and cognitive dimensions are described in the context of South Africa‟s current socio-economic milieu.

Regulatory dimension of the institutional environment There are substantial national consequences for entrepreneurial activity, and as a global phenomenon entrepreneurial activity absorbs a substantial amount of human and financial resources (Autio, 2007). The existence of a systematic relationship between the per capita GDP of a country, its economic growth and its level of entrepreneurial activity, albeit

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complex, is intensifying as a result of longitudinal studies such as the Global Entrepreneurship Monitor report (GEM) (Bosma and Levie, 2009). More specifically, evidence is accumulating which suggests that improving the regulatory environment may have positive benefits on the growth and survival of new ventures in South Africa (Orford et al., 2004). In 2009, the average new firm prevalence rate for all efficiency-driven countries was more than double South Africa‟s rate. The prevalence rates for established business activity were even more disturbing, with the average for all efficiency driven countries being almost six times higher than South Africa‟s rate. The economic implications of these findings paint a bleak picture of the South African SMME sector‟s current potential to contribute meaningfully to job creation and economic growth. This is similar to the experiences of the former Soviet countries, demonstrating that during the initial stages of transition to a market economy, entrepreneurship, as a source of economic growth, is not only unsupported but largely neglected and even suppressed (Manolova, Eunni and Gyoshev, 2008). South Africa‟s low levels of entrepreneurial activity are the result of personal as well as environmental factors. Improving the skills base and fostering positive entrepreneurial attitudes through the education system is critical. However, without a more enabling environment that encourages individuals to see entrepreneurship as a financially viable employment option, it is debatable whether South Africa will experience a significant increase in entrepreneurial activity. A major prerequisite for a thriving enterprise sector is the existence of an enabling environment, institutions which render political and economic stability, relative security, market based incentives, and access to resources needed to grow (Herrington, Kew and Kew 2010). Recognising the context of the regulatory environment and given the definition of regulatory institutions which refers to the formally codified, enacted, and enforced structure

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of laws in a community, society, or nation (Busenitz et al., 2000), the first hypothesis predicts that: H1:

Positive perceptions of favourability of the regularity institutional environment

are associated with higher levels of entrepreneurial intentions.

Normative dimension of the institutional environment Not only does the macroeconomic environment together with the more immediate business environment affect the levels of entrepreneurial activity in a country, but more specifically enduring national characteristics have been predicted to have an impact on entrepreneurship (Bygrave and Minniti, 2000; Urban, 2008). Calls have been made for countries to re-orientate their values and behaviours towards entrepreneurship. If entrepreneurship is not valued in the culture of a particular country, then not only will it be associated with criminality and corruption but also other forms of economic encouragement will prove ineffective (Baumol, 1990). Davidsson and Wiklund (1997), offer two views in terms of the normative environment effecting entrepreneurship: Firstly, the supportive environment perspective or societal legitimisation perspective where prevailing values and beliefs, among others, may make a person more or less inclined towards new venture formation. Secondly, because some regions have a larger pool of entrepreneurs, entrepreneurship leads to more entrepreneurship and the degree of entrepreneurial activities is an outcome of a dynamic process in which social habits (entrepreneurial memory) are as important as legal and economic factors. This view is in accordance with McClelland‟s (1961) and Bygrave and Minniti‟s (2000) arguments, which emphasise the embeddedness of entrepreneurship in social and structural relationships and suggest that entrepreneurship is a self-reinforcing process. Thus entrepreneurs act as catalysts of economic activity, where the normative institutions as well as the entrepreneurial history

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of a community are important. Less formal are these normative institutions, which typically manifest in standards and commercial conventions such as those established by professional and trade associations, and business groups. In the series of GEM reports, cultural and social norms are emphasised as the major strength of entrepreneurial intentions and seem to be the differentiating factor for high levels of entrepreneurial activity in different countries (Minniti and Bygrave 2003). In South Africa, not only is there a sense of entitlement and an expectation that big business, government and others should create jobs; rather than that one creating one‟s own employment; but aspiring entrepreneurs have low levels of entrepreneurial experience, inadequate education, lack of access to finance and business-orientated networks (Herrington, Kew and Kew, 2010). In line with the definition of the normative dimension of the institutional environment, which determines the degree to which a country‟s residents admire entrepreneurial activity and value creative and innovative thinking (Busenitz et al., 2000), the second hypothesis predicts that: H2:

Positive perceptions of favourability of the normative institutional

environment are associated with higher levels of entrepreneurial intentions.

Cognitive dimension of the institutional environment Beginning with McGrath and MacMillan‟s (2000) conceptualisation of the entrepreneurial mind-set, scholars have embraced the notion that dynamic sense making and decision processes are central to success in an entrepreneurial environment (Ireland, Hitt and Sirmon 2003). The entrepreneurial cognition literature has developed substantially in the area of examination of cognitions relating to entrepreneurial decision making (Baron 2004; Dutta and Thornhill 2007; Mitchell, Busenitz and Lant et al. 2002; Mitchell, Busenitz and Bird et al. 2007). The central premise of the cognitive perspective is that entrepreneurial behaviour

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emerges as a result of the entrepreneurs underlying cognitions. Essentially the entrepreneurial cognitions perspective allows researchers to understand how entrepreneurs think and why they do some of the things they do (Krueger 2000). While cognitive approaches to entrepreneurship have devoted considerable energy to defining „entrepreneurial cognitions‟ based on knowledge (Shane 2000), or heuristics (Busenitz 1999), cognitive adaptability, as a process-orientated approach, is new to entrepreneurship. Haynie and Shepherd (2009) conceptualise cognitive adaptability as the ability to effectively and appropriately change decision policies (i.e., to learn) given feedback (inputs) from the environmental context in which cognitive processing is embedded. Cognitive institutions are the axiomatic beliefs about the expected standards of behaviour that are specific to a culture, which are typically learned through social interactions by living or growing up in a community or society. Research suggests that while such a cognitive task is difficult to achieve (Rozin, 1976), it is positively related to decision performance in contexts that can be characterised as complex, dynamic, and inherently uncertain (Earley and Ang, 2003; Kirzner, 1979). The entrepreneurial context, particularly the country‟s institutional environment, exemplifies such a decision environment. In South Africa most entrepreneurs are restricted by their scarcity of skills, business knowledge and resources in their ability to grow and create employment (Urban, Barreira and Van Vuuren, 2005). Recognising that the cognitive dimension reflects the knowledge and skills possessed by the people in a country pertaining to establishing and operating a new business (Busenitz et al., 2000), we hypothesize that:

H3:

Positive perceptions of favourability of the cognitive institutional environment

are associated with higher levels of entrepreneurial intentions.

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Methodology Participants We considered it appropriate to closely approximate the characteristics of our sample with those of earlier studies investigating institutional profiles and entrepreneurial intentions (Douglas and Shepherd, 2002; Manolova, Eunni and Gyoshev, 2008; Urban, 2006, 2008). It has been suggested that research using students to study intention allows for the improvement of predictive abilities, providing a fertile ground from which seeds of entrepreneurship can sprout. Research finds that student samples are very similar to actual entrepreneurs provided that the sample has high entrepreneurial potential (Hemmasi and Hoelscher 2005). As Dipboye and Flanagan (1979) argue, laboratory research that relies on mostly college students provides a solid basis for the generalisation to the population of working people and adults, whereas research that relies on contextually grounded samples (managers, entrepreneurs, team leaders) is exceedingly homogeneous (male, professional, educated, etc.), and therefore potentially constrained in its generalisability. Our initial sample included 377 students from random class selections at different university faculties of business located in cities of two provinces (Gauteng and Eastern Cape) in South Africa. Scherer et al (1989) indicate that student populations add control and homogeneity to a study because individuals studying business already have an interest in pursuing business related careers and students have the necessary education required to run a business. In terms of the selected locations, Johannesburg is situated in the Gauteng province, the economic hub of South Africa, and the most entrepreneurially dynamic province in terms of both early-stage activity as well as opportunity motivated entrepreneurship. In contrast East London situated in the Eastern Cape Province is one of the lowest ranked entrepreneurial provinces in the country, with much of the variation due to differences in levels of

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opportunity versus necessity-motivated entrepreneurship, and migration from stagnant markets (Herrington, Kew and Kew, 2010). Such a contrast in sampling different provinces with variation in entrepreneurial levels and aspirations should provide wider generalisability for this study. Sample parameters, which served as control variables, are: (a) gender (female = 53%; male = 47%), (b) age (mean age = 24.8 years), (c) education level (undergraduate student = 64%; postgraduate student = 35%), (d) race/ethnic group (black = 65%; coloured = 4%; indian = 7%, white = 23%), (e) work experience if any (no experience = 39%; 1-2 years = 21%; 3-5 years = 23%; 6-9 years = 6%; more than 10 years = 9%), (f) family, friends or relatives who are entrepreneurs (yes = 56%; no = 43%). Data was gathered over a four month (one term) period from respondents attending a series of day and evening classes during their studies. The survey was administered as a paper-and-pencil test, and as a matter of practicality was distributed during a classroom setting allowing the researcher to maintain control over the environment, and to ensure a high response rate (65%), rendering a final sample of 199. Measures Institutional dimensions – independent variables: As Manolova, Eunni and Gyoshev (2008) note the Busenitz et al. (2000) scale is an appropriate instrument to use in the context of emerging economies. Results from their study employing confirmatory factor analysis suggest high reliability, internal consistency, and construct validity. For the present study all items were measured with five-point Likert scales ranging from strongly agree (5) to strongly disagree (1). The regulatory dimension was measured with 5 items, the normative dimension with 4 items and the cognitive dimension with 4 items. Notwithstanding the previous scale validation scale reliability was retested. Cronbach‟s alphas for each of the aggregate scales were .61 for the regulatory dimension, .76 for normative dimension, and .74 for cognitive

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dimension. These were deemed acceptable for exploratory research, since all are within range of the benchmark of.70 indicating a high degree of internal consistency across items (Nunnally, 1978). Entrepreneurial Intentions – dependant variable: Several measures of entrepreneurial intentions were scrutinised for suitability of use in this study (Douglas and Shepherd, 2002; Krueger et al., 2000; Thompson 2009). Based on the notion that the degree and intensity of individuals‟ entrepreneurial intent might reasonably be expected to vary from person to person, and to vary for the same person at different points in time depending on circumstances, individual entrepreneurial intent is best assessed using a continuous, as opposed to a categorical, measurement approach (Diamantopoulos and Siguaw 2006; Thompson 2009). A measure which captures these aspects of intent is Thompson‟s (2009) individual entrepreneurial intent scale (IEIS) which was developed to incorporate high content validity, plus broad applicability across populations by nationality, age, and occupation. Moreover, the items have been selected to help maximise general applicability to the majority of individuals with entrepreneurial intent regardless of the stage to which they might have advanced in terms of setting up a firm. A rigorous development and validation procedure has ensured that the IEIS is internally reliable, uni-dimensional, and stable, both within the same sample over time and across populations, this latter giving considerable support for the scale‟s wider generalisability (Thompson, 2009). For these reasons the IEIS measure was adopted using an interval scale (1-5) starting on the left with the statement “not very true,” and ending on the right with the statement “very true.” As recommended the items for the IEIS appear as a single block, where certain items were included which served as distracter items, or acted as red herrings and were not included in scale analyses. Some items were reverse coded in scale analyses. Scale reliability was tested for this sample and rendered an overall Cronbach Alpha of 0.71 for the total ten IEIS items.

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Data analysis Diagnostics were carried out for normality checks using the Shapiro-Wilk test. Results indicate that data is approximately normally distributed because the means, modes and medians for each question are almost equal. The Q-Q plots also support the normality of the data and the stem-and-leaf plots show a bell shape and all the significant values for the items are less than 0.05 indicating that the data is normally distributed and parametric tests could be conducted on this data set. Multiple regression analyses were performed to determine the predicted relationship between the specified variables. The use of multiple regressions allows for the partitioning of variance with correlated predictors, thereby reducing the likelihood of making a Type 1 error (Cohen and Holliday, 1998). Control variables were included in the regression analyses by means of the inclusion of appropriate dummy variable. Backwards stepwise regression was used to eliminate variables with insignificant regression coefficients.

Results Mean scores, standard deviations and correlation coefficients are displayed in Table 1. Descriptive statistics for the regulatory and normative dimensions have total mean scores of 3.33 and 3.74 respectively. These relatively high average mean scores are above the scale mid-point (2.5), suggesting that individual‟s perceptions of the regulatory and normative institutional profiles are favourable. In terms of the cognitive dimension the mean score is 2.86 suggesting less favourable perceptions of this institutional dimension. To evaluate the hypothesized relationships between the variables, correlational and regression analyses were performed and are displayed as scatter plot diagrams in Figures 1-3. For the correlation matrix, refer to Table 2, the Pearson Correlation Coefficients are reported with levels of significance denoted. According to Cohen and Holliday (1998), a

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multiple correlation coefficient of 0.7 or above is considered a high relationship, whereas Anastasia and Urbani (1997) maintain it should be high enough to be statistically significant at the 0.05 and 0.01 levels. The interpretation of these correlations and the corresponding levels of significance allowed for acceptance or rejection of the hypotheses, as follows: Perceptions of favourability of the regularity institutional dimension were positively but not significantly correlated with higher levels of entrepreneurial intentions (r = 0.12, p = .255), leading to the rejection of Hypothesis 1. Perceptions of favourability of the normative institutional profile were positively but not significantly correlated with higher levels of entrepreneurial intentions (r = 0.20, p = .062), leading to the rejection of Hypothesis 2. Perceptions of favourability of the cognitive institutional profile were negatively and not significantly correlated with higher levels of entrepreneurial intentions (r = -0.14, p = .174), leading to the rejection of Hypothesis 3. Apart from education levels (r = 0.35, p = .001), all the other control variables were not significantly correlated with the intent variable. To further try and evaluate the relationship between the institutional dimensions and intentions, multiple regression analysis was conducted. Refer to Table 3 for the full results. The use of multiple regressions allows for the partitioning of variance with correlated predictors, thereby reducing the likelihood of making a Type 1 error (Cohen and Holliday 1998). Although no rule exists regarding what fraction of variance needs to be explained to make relationships strong many researches consider a squared multiple correlation of 0.3 or greater to be at least moderately strong (Sudman and Blair, 1998). It is worth noting that although the coefficient of determination (R-squared) does not exceed 30%, the relationships determined through the regression analysis, while they may be weak, are nevertheless statistically significant, the R-square is 0.128, and an adjusted R-square of 0.108 is

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interpreted that the predictors (institutional dimensions aggregate score) explain 12.8 % of variance in the dependant variable (intentions). This means that there may be other variables that influence this relationship. In the ANOVA section an F Value (1.44) = 6.45 is statistically significant (p<.0146). The constant coefficient provides a t value of 6.82, significant at the .001 level (p < .001). The beta weight (.357) is significant at the .005 level (p < .005). An examination of the collinearity diagnostics reveal relatively low variance proportions for the institutional dimensions and control variables. These diagnostics when read in conjunction with collinearity statistics, not shown due to space limitations, indicate variable inflation factor (VIF) values between .265 and .0627. These figures are well below critical values and deemed as acceptable, indicating no incidence of multicollinearity. When the values are 10.0 or more the regression coefficients can fluctuate widely from sample to sample, making it risky to interpret the coefficients as indicators of the predictors (Cooper and Emory, 1995). T-tests were calculated on various groupings on the control variables across the institutional dimensions and intentions. In Table 4 only the significant variables are shown. Several significant differences are observed on all variables, apart from the regulatory dimension, for differences between undergraduate and post-graduate levels of education. Similarly several significant differences are also found on variables for respondents who had parents, friends or relatives who are or had been entrepreneurs. These findings resonate with previous research which confirms that would-be entrepreneurs are influenced by family to start a venture (Santos, Curral and Caetano, 2010).

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Discussions and Conclusion The purpose of this study was to build on research incorporating the institutional dimensions of the regulatory, normative and cognitive environment. In this regard the present study adds to the growing knowledge base on the institutional environments in emerging market contexts. Specifically it was hypothesized that each of the institutional dimensions will be significantly associated with entrepreneurial intentions. The empirical evidence ensuing from this study does not support these propositions, where relatively favourable perceptions in terms of means scores were not significantly associated with entrepreneurial intent. Based on the regression results the different institutional dimensions explain a modest amount of variance in entrepreneurial intentions. This means the strength of the relationships between various dimensions of institutional dimensions is mostly positive although generally weak. The negative relationship detected in terms of the cognitive dimension means that this factor may have a reverse effect on intentions. Plausible reasons for this may be that in South Africa the country‟s institutional environment exemplifies an environment, where potential entrepreneurs are reluctant to start a venture due to lack of skills, business knowledge, resources, and self-belief (Urban, 2006). Several differences in demographic variables suggest that different levels of education seem to play a role in the perceptions of the regulatory and cognitive institutional dimensions in terms of entrepreneurial intentions. This is significant in that research finds that those with more formal education tend to start high-potential ventures with substantial growth prospects (Urban, van Vuuren and Barreira, 2008). Implications Measuring institutional profiles and their effect on entrepreneurial behaviour is important in an emerging market context. Hernando de Soto (2000) has exposed the damaging effects of heavy business regulation and weak property rights in developing countries. In particular, he

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has illustrated the dead capital that many potential entrepreneurs sit on because they are unable to leverage it due to poor securities, title, contracts etc. In effect, these potential economic agents are rendered redundant because of the ineffective institutional environment (Luiz, 2008). The series of „Global Competitiveness‟ reports (World Economic Forum, 2009), indicate that South Africa ranks 45 out of 133 in terms of an overall index. However South Africa‟s apparent favourable institutional environment, when compared with other African countries, does not translate into high entrepreneurial activity as is clear from the declining levels of total entrepreneurship activity (TEA) (Herrington, Kew and Kew, 2010). The most problematic factors for „doing business‟ in South Africa are cited as crime and theft and an inadequately educated workforce. Moreover, the cost of regulatory compliance is extremely high, especially for small businesses. Much has been said about this by government officials, but little real and effective action has been taken. Taken together, these characteristics of the formal, or regulatory dimension would profess predominantly necessity-based and mostly low-growth, short-term oriented entrepreneurship in South Africa, as with other emerging economies (Manolova, Eunni and Gyoshev, 2008). Thus, in such circumstances the quality of the entrepreneurial pool in a country worsens from both the inflow of low-ability entrepreneurs as well as the outflow of high-ability entrepreneurs. This will lead to further restrictions from the side of credit markets, in the form of higher interest and/or collateral requirements – which may further push out talented entrepreneurs. The consequence is that poor countries may be caught in a self-reinforcing „entrepreneurial development trap (Naude, 2009). Notwithstanding these potential pitfalls, when considering the wide range of entrepreneurship rates across countries, even when controlled for variations in institutional quality, would suggest that specific policies, interventions and regulations – relating to start-

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up costs or innovative activities – may have an influence on the supply of entrepreneurs (Naude, 2010b). Public policy makers should enhance the institutional framework in order to support entrepreneurial intentions by developing a country-specific mix of entrepreneurfriendly legislation, and promoting positive entrepreneurial role models to influence social attitudes and aspirations towards entrepreneurship. This study also has implications for small business owners and managers, who need to be aware of the less than favourable conditions for entrepreneurship in emerging markets, and of the numerous and often conflicting institutional pressures and constraints facing potential market entrants. Limitations and further research Limitations of the study include that data may have been contaminated by common method variance, since all variables were surveyed from the same set of respondents. Another limitation of this article is that a cross-sectional study loses the dynamic aspects of entrepreneurial institutions as they may well change over time with focused reform measures. As with previous studies, using aggregate measures of the institutional environment for entrepreneurship may mask subtle and persistent differences, and less readily observable influences such as legal and cultural traditions, or social norms and values (Manolova, Eunni and Gyoshev, 2008). As a directive for future research, it is noted that more and more scholars and policy makers today are underscoring the critical importance of the institutional environment to entrepreneurship (Shane, 2003; Naude, 2010b), where several gaps are currently missing in the literature, which provides fertile ground for future research. For instance, future research could focus on the cognitive dimension of the institutional environment in order to generate high-growth ventures, with a focus on human capital and cognitive adaptability that is compatible with emerging market demographics.

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Table 1: Descriptives for institutional and intention variables

Intent Variables

Cognitive variables

Normative Dimension

Regulatory variables

Variables

ItemTotal Correl.

Alpha if - deleted

Mean

Std.dev

3.35

1.00

0.480

0.503

3.34

0.99

0.441

0.524

3.51

0.93

0.362

0.567

3.73

0.81

0.325

0.585

2.71 3.33

0.97 0.61

0.257

0.622 0.614

3.65

1.06

0.648

0.755

3.80 3.94

0.91 0.87

0.694 0.560

0.736 0.795

3.57 3.74

1.06 0.78

0.633

0.764 0.763

2.81

1.12

0.625

0.744

2.76

1.04

0.651

0.733

2.81

1.03

0.677

0.722

3.08 2.86 4.12 4.26 3.96

1.19 0.86 0.89 0.77 0.90

0.517 0.434 0.366 0.468

0.802 0.740 0.696 0.706 0.691

Search for business start-up opportunities Read financial planning books Are saving money to start a business Read books on how to set up a firm Plan your finances carefully

3.29 3.71 3.64 3.25 3.94

1.23 1.14 1.11 1.31 0.93

0.359 0.353 0.330 0.343 0.558

0.707 0.707 0.711 0.712 0.677

Have plans to launch your own business Spend time learning about starting a firm Mean of intent variables

3.41 3.95 3.75

1.28 0.96 0.57

0.257 0.482

0.726 0.687 0.713

Government organisations assist individuals starting their own businesses Government sets aside government contracts for new and small businesses Local and national government have special support for individuals starting a new business Government sponsors organisations that help new businesses develop Even after failing, government assists entrepreneurs starting again Mean of regulatory variables Turning new ideas into businesses is admired in this country In SA, innovative and creative thinking is viewed as a route to success Entrepreneurs are admired in this country People in SA greatly admire those who start own businesses Mean of normative dimension Individuals know how to protect a new business legally Those who start new businesses know how to deal with risk Those who start new businesses know how to manage risk Most people know where to find info about markets for their products Mean of cognitive variables Intend to set up a business in the future Plan your future carefully Read business newspapers

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Table 2: Correlation matrix for institutional dimensions and intentions Mean of Mean of Mean of Mean of Regulatory Normative Cognitive Intent Details of correlations variables dimension variables Variables 1.0000 .3559 .2565 .1241 Mean of Regulatory N=86 N=86 N=86 N=86 variables p= --p=.001 p=.017 p=.255 .3559 1.0000 .0047 .2023 Mean of Normative N=86 N=86 N=86 N=86 dimension p=.001 p= --p=.965 p=.062 .2565 .0047 1.0000 -.1480 Mean of Cognitive variables N=86 N=86 N=86 N=86 p=.017 p=.965 p= --p=.174 .1241 .2023 -.1480 1.0000 Mean of Intent Variables N=86 N=86 N=86 N=86 p=.255 p=.062 p=.174 p= ---

Table 3: Regression summary for dependent variable Std.Err. Std.Err. b* - of b* b of b t(44) p-value Intercept 2.785007 0.407915 6.827419 0 Mean of Normative dimension 0.3578 0.140775 0.269643 0.10609 2.541641 0.014632 Mean of Intent Variables. R = .35780042 R²= .12802114 Adjusted R²= .10820344 F (1, 44) =6.4599 p

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Table 4: Differences on institutional dimensions per demographics Mean – Mean – Variable Group 1 Group 2 t-value df p Gender: Group 1: Male, Group 2: Female People in SA greatly admire those who start own businesses 3.83 3.35 2.129 84 0.036 Education: Group 1: Diploma/Degree/Post-grad complete, Group 2: Matric complete Gov organisations assist individuals starting their own businesses 3.07 3.58 -2.300 79 0.024 Gov sets aside gov contracts for new and small businesses 2.98 3.68 -3.347 79 0.001 Mean of Regulatory variables 3.15 3.48 -2.455 79 0.016 Those who start new businesses know how to deal with risk 2.56 3.03 -2.069 79 0.041 Those who start new businesses know how to manage risk 2.58 3.11 -2.290 78 0.024 Mean of Cognitive variables 2.70 3.09 -2.084 79 0.040 Intend to set up a business in the future 4.35 3.87 2.709 79 0.008 Search for business start-up opportunities 3.51 2.87 2.453 77 0.016 Parents are entrepreneurs: Group 1: No, Group 2: Yes Gov sets aside gov contracts for new and small businesses 3.57 3.00 2.668 82 0.009 Spend time learning about starting a firm 3.78 4.25 -2.078 77 0.041 Friends are entrepreneurs: Group 1: Yes, Group 2: No Those who start new businesses know how to deal with risk 2.46 2.94 -2.169 82 0.032 Those who start new businesses know how to manage risk 2.35 3.13 -3.751 81 0.000 Most people know where to find info about markets for their products 2.86 3.21 -1.331 81 0.184 Mean of Cognitive variables 2.55 3.06 -2.796 82 0.006 Search for business start-up opportunities 3.83 2.91 3.513 79 0.000 Plan your finances carefully 4.23 3.76 2.343 79 0.021 Have plans to launch your own business 3.74 3.16 2.042 77 0.044 Mean of Intent Variables 3.92 3.63 2.393 82 0.018 Relatives are entrepreneurs: Group 1: Yes, Group 2: No Individuals know how to 2.54 3.16 -2.624 83 0.010 32

protect a new business legally Plan your finances carefully Have plans to launch your own business Mean of Intent Variables

4.15

3.67

2.413

81

0.018

3.66 3.87

3.06 3.59

2.126 2.371

79 84

0.036 0.019

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Scatterplot of Mean of Intent Variables against Mean of Regulatory variables Mean of Intent Variables = 3.3621+0.1157*x 5.0 4.5

Mean of Intent Variables

4.0 3.5 3.0 2.5 2.0 1.5 1.0 1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

Mean of Variables: Regulatory rvariables Mean of Regulatory variables:Mean of Intent = 0.1241, p = 0.2548; r 2 = 0.0154

Figure 1: Scatterplot of mean of intent variables s against mean of regulatory dimension

34

Scatterplot of Mean of Intent Variables against Mean of Normative dimension Mean of Intent Variables = 3.1985+0.1466*x 5.0 4.5

Mean of Intent Variables

4.0 3.5 3.0 2.5 2.0 1.5 1.0 1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

of Normative Mean of Normative dimension:MeanMean of Intent Variables: dimension r = 0.2023, p = 0.0617; r 2 = 0.0409

Figure 2: Scatterplot of mean of intent variables against mean of normative dimension

35

5.0

Scatterplot of Mean of Intent Variables against Mean of Cognitive variables Mean of Intent Variables = 4.0251-0.0972*x 5.0 4.5

Mean of Intent Variables

4.0 3.5 3.0 2.5 2.0 1.5 1.0 1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

Cognitiver variables Mean of Cognitive variables:Mean of Mean Intent of Variables: = -0.1480, p = 0.1738; r 2 = 0.0219

Figure 3: Scatterplot of mean of intent variables against mean of cognitive dimension

36

5.0