CC BY
26Eunni R.V., Doctor of Business Administration, Associate Professor, Management Department Youngstown State University, Youngstown, uSa, [email protected]
Manolova T. S, Doctor of Business Administration, Associate Professor, Management Bentley University, Waltham, USA, [email protected]
INSTITUTIONAL CONTEXT FOR ENTREPRENEURSHIP IN EMERGING ECONOMIES: A NINE-COUNTRY COMPARISON OF UNIVERSITY STUDENTS' PERCEPTIONS
In this study, we compare and contrast the perceptions of the institutional environment for entrepreneurship among university students in nine emerging economies across three global regions: Central and Eastern Europe (Bulgaria, Hungary, Latvia, and Russia), Asia (China, India, and the Republic of Korea), and Latin America (Brazil and Mexico). The student perceptions are measured employing a survey instrument developed by Busenitz et al. (2000) for industrialized countries, and validated in the context of emerging markets by Manolova et al. (2008). Our results indicate that the institutional environments are perceived as overall unfavorable to new firm formation in all the three global regions as well as the nine constituent countries. However, the institutional milieus vary along different dimensions. The reasons for such variances could be traced to differences in the respective legal systems, cognitive structures, and normative traditions across regions and countries. Consequently, the institutional environments present different opportunities and challenges to university students who consider an entrepreneurial career. We discuss the theoretical, managerial, and public policy implications of our findings.
Keywords: entrepreneurship, institutional environment, emerging economies, university students.
Introduction
Emerging economies are countries «with a rapid pace of economic development and government policies favouring economic liberalization and the adoption of a free market system» (Arnold, Quelch 1998; c.f. Hoskisson et al. 2000: 249). Hoskisson et al. (2000) identified 51 rapid-growth developing countries in Asia, Latin America, Africa, and the Middle East. To these, they added 13 transition economies in Central and Eastern Europe (CEE), which, since the late 1980's, have transi-
tioned from centrally-planned to market-based economic systems, committing themselves (in varying degrees) to strengthening their market mechanisms through liberalization, economic stabilization, and the encouragement of private enterprise.
By 2010, emerging economies accounted for 52% of the global population (Noeth, Sen-gupta 2012) and 38% of the world GDP (at market exchange rates), twice their share in 1990 (The Economist online 2011 ). Almost a quarter of the Fortune Global 500 firms are now based in the emerging markets, compared to only 4%
in 1995 (The Economist online 2011). Emerging economies are forecasted to notch up 56% of the increase in global GDP during the period 2011-2016, but would be responsible for only 13% of the increase in global debt, replacing the industrialized countries as the bedrock of the international financial system (Prasad 2011).
Emerging economies are frequently credited with the existence of a vibrant entrepreneurial class. The establishment and growth of private entrepreneurial enterprises has greatly accelerated the transition of these countries from overwhelmingly state-centered economies to competitive markets (Zahra et al. 2000; Manev, Manolova 2010) and has propelled the pace of their economic development. According to the 2012 Global Entrepreneurship Monitor report (Xavier et al. 2012), between 4% (in Russia) and 23% (in Chile) of the population aged 18-64 in these countries is currently involved in early stage entrepreneurial activity. Entrepreneurial ventures contribute to both economic growth and market transformation. They offset job losses in the state-owned and large business sector, turn technological and market innovations into economic output, provide a continual source of organizational change and renewal, and continuously reaffirm the role of market-based economic exchange. In short, as elsewhere around the world, entrepreneurial activities in emerging economies can be harnessed to become an engine of growth, innovation, and job creation.
New firm formation and development depends upon the existence and proper functioning of a system of formal and informal institutions that support entrepreneurship (North 1995; Busenitz et al. 2000; Bruton et al. 2010; Kosi, Bojnec 2013). Indeed, building and sustaining an appropriate institutional infrastructure for the promotion of high-aspiration, growth-oriented entrepreneurship is vital for the continued economic and social development of emerging economies (World Bank 2013a). In this study, therefore, we explore how university students in nine emerging economies, spread across three global regions, perceive their respective national institutional environments in terms of
their favorability or otherwise for the promotion of entrepreneurship.
The rationale for our interest in university student perceptions is grounded in studies that found that those who start new firms typically do so between 25-34 years of age (Levesque, Minniti 2011; Xavier et al. 2012), that is, shortly after completion of their college education. It is also known that university graduates with their youthful energy and creativity, combined with high level of education and technological savvy, are better equipped to start growth-oriented new ventures that exploit cutting-edge university research (Lüthje, Franke 2003; Mowery, Shane 2012), create high-quality jobs, and enhance national competitiveness. It is, therefore, imperative for both entrepreneurship educators as well as public policy makers to understand better what factors motivate university students to pursue such entrepreneurial initiatives.
Entrepreneurial intentions among university students are the result of variegated influences at the individual, family, and societal level (Lüthje, Franke 2003; Linan et al. 2011). Empirical research on university student populations has been greatly enriched by Azjen's (1987) theory of planned behavior, which models intentions as a function of three factors: (1) the personal attitudes towards the planned behavior; (2) the social norms about the planned behavior; and (3) the perceived behavioral control over the intended behavior. Empirical studies have extended Azjen's (1987) model by exploring a variety of antecedent conditions, including individual-level determinants such as psychological predispositions (Mueller, Thomas 2001; Gürol, Atsan 2006), education, experience, financial capital, and social connections (Wu, Wu 2008; Peterman, Kennedy 2003), family support and role models (Wang, Wong 2004), regional cultural contexts (Linan et al. 2011), as well as the level of macroeconomic, technological, and institutional development of a country (Veciana et al. 2005; Mueller, Thomas 2001).
Empirical studies of Chinese students have documented, for example, that engineering majors have the highest propensity, while students
with non-entrepreneurship related majors have the lowest propensity to start a new venture (Wu, Wu 2008). Similarly, entrepreneurship education in Australia has been shown to significantly increase both the desirability and the feasibility of an entrepreneurship career (Peterman, Kennedy
2003). Although students with entrepreneurial intentions exhibit generally higher risk-taking, need for achievement, locus of control, or innovative-ness as compared to students without entrepreneurial intentions (Gürol, Atsan 2006), there is a certain tension between the interest in entrepre-neurship and the perceived risk (Wang, Wong
2004), so that overall many university students consider entrepreneurship as highly desirable, but not very feasible (Veciana et al. 2005).
A related stream of research, based on the Global Entrepreneurship Monitor (GEM) data, has established that demographics influence the level of aggregate entrepreneurship in a country, because young people lack the financial resources or the experience to start a new business (Lévesque, Minniti 2011 ). In the context of the transitional economies of CEE, however, empirical findings indicate that the younger generation, which has no institutional memory of the suppression of private initiative under socialism, is more willing to embrace an entrepreneurial career, compared to older individuals (Estrin, Mick-iewicz 2011 ). To summarize, empirical research at the individual level has focused on the microinfluences on university students' entrepreneurial attitudes and intentions, whereas empirical research at the macro-level has not explored in sufficient detail the effect of different aspects of the country-level institutional environment on university students' entrepreneurial attitudes. This is the research gap our study is addressing.
We focus specifically on the role of the institutional environment for the promotion of en-trepreneurship among university students in emerging economies. We ask: Are there differences in university students' perceptions of the institutional environments for entrepreneurship in emerging economies across and within three global regions — Asia, Central and Eastern Europe, and Latin America?
Our contribution is three-fold. First, we compare and contrast the favorability of the regulatory, cognitive, and normative dimensions of the institutional environment, across three global regions: Asia, Central and Eastern Europe (CEE), and Latin America, and nine emerging economies: The Republic of Korea (South Korea), China, and India (in Asia); Bulgaria, Hungary, Latvia, and Russia (in CEE), and Mexico and Brazil (in Latin America). This approach allows us to highlight both the commonalities and the differences in the institutional infrastructure for entrepreneurship between and within these three global regions. Second, we focus on the perceived favorability of the institutional environment, thus complementing prior research which has utilized objective measures available from government or international agencies (see, for example, Bowen, De Clercq 2008; Djankov et al. 2002; Valdez, Richardson 2013). The assumption underlying our approach is that a potential nascent entrepreneur is not likely to engage in the arduous and risky process of starting a new venture unless s/he perceives the environment as business-friendly. Finally, we decided to specifically focus on the perceptions of university students because, as argued above, they have the potential and the motivation to establish high-growth innovative new ventures, vital for accelerated economic development. Our findings augment empirical support to the relatively sparse body of literature on entrepreneur-ship development in weak institutional contexts (Aidis et al. 2008; Djankov et al. 2005; McMillan, Woodruff 2002), particularly with regard to the role of the informal institutions (Estrin, Prevezer 2011) and emphasize the public policy implications of promoting entrepreneurship among the youth in emerging economies.
Our paper is structured as follows. At the outset, we present a brief theoretical overview and frame the research question that guided our study. This is followed by a description of the methods and a discussion of the results from statistical tests. In the final section, we discuss the findings of the study and delineate its theoretical and public policy implications.
Theoretical development
Institutions are widely accepted systems of practice, technologies and rules of social interaction which are normatively established in a society, so behaviors contrary to such practices, technologies and rules could be socially disapproved and even sanctioned to ensure compliance (Lawrence et al. 2002). In short, institutions are the fundamental political, social and legal ground rules that govern the conduct of all economic activity. Students of institutional theory argue that all strategic and economic activity is embedded in a social and normative context, and that such a context motivates organizations to conform to social rules and expectations in order to be accorded legitimacy and support (North 1990; Meyer, Rowan 1977). In other words, institutional theory deals with the regulatory, social, and cultural influences, both formal and informal, that promote the survival and legitimacy of an organization, rather than focusing solely on its efficiency-seeking behavior (Roy 1997; Tolbert et al. 2011). Scott (1995) is credited with a widely accepted typology of formal and informal institutional forces that classifies them into regulatory, normative, and cognitive categories.
Regulatory institutions are formally enacted laws and regulations of a society or nation which are typically codified and formally enforced to ensure compliance. Normative institutions are less formal but equally effective rules established by professional and trade bodies to standardize and control the conduct of their members. Cognitive institutions are widely held beliefs and values that define what behavior in social interactions is culturally appropriate, and these are internalized through living and growing in a community. Despite some academic quibbles (Hirsch, Lounsbury 1997), this framework has been extensively used in organizational and entrepreneurship research (Bruton et al. 2010).
Following Scott's (1995) classification, Busen-itz et al. (2000) designed a survey instrument that measures the three dimensions of a country's institutional environment for the promotion of entrepreneurship, adopting however some-
what narrower definitions of the constructs than were originally intended. Thus, the cognitive dimension is defined as «the knowledge and skills possessed by the people in a country pertaining to establishing and operating a new business» while the normative dimension measures «the degree to which a country's residents admire entrepreneurial activity and value creative and innovative thinking» (Busenitz et al. 2000: 995). Since we employed Busenitz et al.'s (2000) instrument in our empirics, we follow their definitions in our conceptual development.
The institutional environment affects the speed and scope of new firm formation and subsequent development by determining what is normatively permissible, and thereby defining and delimiting opportunity spaces (Aldrich 1990; Gnyawali, Fogel 1994). Further, by prescribing what is socially acceptable, the institutional environment also influences the process of achieving cognitive and political legitimacy, thereby increasing the chances of survival for a start-up (Freeman et al. 1983). If the institutional environment is perceived as hostile to entrepreneurial activities, aspiring entrepreneurs will be less motivated to engage in new venture formation and enter competition (Lim et al. 2010). Post-entry, if the institutional environment is perceived as uncertain or hostile, entrepreneurs will be hesitant to invest time, money, and effort into long-term projects, thus stumping the growth of their ventures. To capture this effect, Dickson and Weaver (2011) introduced the concept of «institutional readiness», conceptualized as the capacity of the institutional environment to support small-and-medium-sized enterprises' strategic initiatives (strategic alliance formation, in their case).
Earlier studies on this subject (Eunni, Manolova 2012; Estrin, Prevezer 2011) have found that the institutional environment in many emerging economies, including the leading ones, collectively known as the BRIC (Brazil, Russia, India, China) countries, is generally perceived to be unfavorable for entrepreneurial endeavors. The regulatory regimes in many of these countries are typically restrictive and
certainly not conducive to new firm formation. The costs of founding a new firm, in terms of the number of procedures, waiting time, and official fees that a start-up must bear before it can operate legally, are quite high, breeding corruption and propelling the emergence of a vast «informal» economy (Djankov et al. 2002; Godfrey 2011; World Bank 2013a). Informal institutions based on personal connections and kinship ties overcome the «voids» in the formal institutional infrastructure (Khanna, Palepu 1997); substituting, complementing, accommodating, and even competing with formal institutions (Estrin, Prevezer 2011).
As for the cognitive pillar of the institutional environment, knowledge about how to launch or manage a business may be lacking and the assistance with market research and other business development activities is still not widely available in emerging economies (Hoskisson et al. 2000; Kasjakova 2004). In regard to the normative environment, social norms, cultural mores, and attitudes to entrepreneurial businesses are quite ambiguous. In transition economies, for example, the legacy of socialist ideology left a persistent stigma on entrepreneurship because of the traditional association of private business activity with profiteering and exploitation (Aidis et al. 2008; Alas, Tuulik 2007). People in some Latin American countries view en-trepreneurship as having practical appeal but less status or visibility (Xavier et al. 2012). While small businesses may be widespread in countries such as Mexico and Korea, the desire to keep a business within family control prevent managers from taking their companies public (Spencer, Gomez 2004), thus limiting their potential for growth and public influence.
Despite these broad similarities in the texture of the institutional fabric, important differences do exist across all the three dimensions of the institutional environment among emerging economies. The nine countries in our study exemplify these differences. On the regulatory dimension, five of the nine countries in our sample share the legacy of socialism, which was characterized by harsh suppression of private business culture,
disregard for private property rights, and administrative oversight of private enterprises by party-controlled agencies (Aidis et al. 2008; Jump-ponen et al. 2008). As for the cognitive dimension, the erstwhile socialist economies traditionally placed a high emphasis on the inclusiveness and quality of their education systems, particularly in the «hard subjects» such as mathematics or engineering (Aidis et al. 2008), whereas India, Brazil, and Mexico are trying to overcome their colonial legacy of relatively lower levels of human development measured by indicators such as literacy or school enrollment. With respect to the normative dimension, besides historical legacies shaping the national psyche, cultural norms are embedded in distinct religious traditions, most notably Catholicism (Brazil, Mexico, and Hungary), Orthodox Christianity (Russia and Bulgaria), Lutheranism (Latvia), Hinduism (India), Buddhism (South Korea) and Confucianism (China). Each of these facets of the institutional environment evidently leaves its imprint on the national capacity for entrepreneurship.
This institutional heterogeneity underlies two aspects of our research question about the fa-vorability of the institutional environment for en-trepreneurship in emerging economies across three geographic regions. First, despite national idiosyncrasies, are there commonalities within a geographic region, such that some geographic regions could be perceived as more favorable than the others for the promotion of entrepreneurship? Second, are all dimensions of the institutional environment salient to university students, the population of interest to our study, or are some dimensions more important to them than others?
With respect to regional differences, research in both international business and entrepreneurship has exhibited a renewed interest in exploring the role and importance of spatial boundaries and geographic context in economic activity, including new venture formation (Rugman 2000; Steyaert, Katz 2004; Spi-gel 2012). Empirical research has documented that most firms tend to concentrate their sales within their home region (Rugman, Verbeke
2004), and that investors tend to hold their equity wealth in domestic assets (French, Poterba 1991). Moreover, regional integration trends led to the emergence of trading blocs such as the European Union, NAFTA, and the ASEAN, leading in various degrees to the harmonization of the institutional framework for regional economic activity. Geographic proximity, shared history, and mass migrations have also shaped common institutional memories, values, beliefs, and cultural mores (Gupta et al. 2002). When economic, demographic, and socio-cultural factors within a region interact in a munificent and self-reinforcing manner, they are likely to create an institutional environment conducive to economic activity and entrepreneurial initiatives across the region as a whole. Thus, we expect to find differences between global regions in the perceived favorability of the institutional framework for the promotion of entrepreneurship.
For university students, the population of interest to our study, some of the differences in their respective countries and regions' institutional profiles may be more salient than others. Globalization has been shown to lead to the development of a «bicultural identity» among young people around the world, combining their local identity with an identity linked to global culture, one that is based on individualism, free market economics, and democracy, and includes freedom of choice, openness to change, and tolerance of differences (Arnett 2002; Friedman 2000). These «global culture» values are likely to be associated with a positive evaluation of entrepreneurial initiatives (Mueller, Thomas 2001). Recall that the normative pillar of the institutional environment captures «the degree to which a country's residents admire entrepreneurial activity and value creative and innovative thinking» (Busenitz et al. 2000: 995). Thus, it is reasonable to expect that the university students across the nine emerging economies might be more similar than different in their evaluation of the national normative milieu for entrepreneurship.
On the regulatory dimension, however, by virtue of their youthful age, university students are particularly vulnerable to legal restrictions,
because of the lack of professional experience or a safety cushion of personal wealth. Finally, with respect to the cognitive dimension of the institutional environment, university students, being more highly educated than the general population, are more likely to seek out opportunities and benefit from support programs for entrepreneurship development. Our a priori expectation, therefore, is that the differences along the regulatory and cognitive dimension will be more pronounced compared to the differences along the normative dimension.
Methods
The survey instrument
We used a survey instrument developed by Busenitz et al. (2000), which was subsequently employed in a study of the influence of the institutional environment on new venture creation in 21 countries around the world (Spencer, Gomez 2004) and validated in the context of emerging markets by Manolova et al. (2008) and Gupta et al. (2012a, 2012b). This survey instrument, which is reproduced in the Appendix to the manuscript, was based on Scott's (1995) classification, i.e. the regulatory, cognitive, and normative dimensions of the institutional environment.
Data collection
We administered the survey in the nine emerging economies included in this study during March to December 2006: Bulgaria, Hungary, Latvia and Russia (CEE), China, India and South Korea (Asia), and Brazil and Mexico (Latin America). These nine countries were selected because of the observable differences in their institutional environments. Their profiles, based on the World Development Indicators (World Bank 2013b) and Doing Business data (World Bank 2013a), are presented in Table 1.
The survey was administered in English in Latvia and India, and in the respective local languages in the other seven countries, after establishing the translation validity of the instru-
Table 1
Country profiles (as of 2006)
Country GDP p.c. (current $) R&D spending (%GDP) Ease of starting a business
Number of procedures Time (days) % p.c. income
Asia
china 2069 1,39 13 48 13,6
India 820 0,77 11 71 62,0
south Korea 19676 3,01 10 17 15,7
Europe
Bulgaria 4313 0,46 11 32 9,6
Hungary 11174 1,00 6 38 22,4
Latvia 8713 0,70 5 16 4,2
Russia 6947 1,07 10 31 8,2
Latin America
Brazil 5793 1,00 17 152 10,1
Mexico 8831 0,39 9 58 15,6
ment through a back-translation procedure (Brislin 1980).
Sample
Our initial sample consisted of 982 students drawn from major business schools in the nine countries. In order to maximize the response rate, following Busenitz et al. (2000), the survey was administered in a classroom setting. With the help of a screening question on nationality, a total of 64 students, whose nationality was different from the country surveyed, were excluded from the sample, reducing the usable sample size to 918 (155 from Brazil, 80 from Mexico, 136 from Bulgaria, 64 from Hungary, 54 from Latvia, 143 from Russia, 62 from China, 130 from India, and 94 from South Korea). Although the sample included both undergraduate and graduate students, the mean age was predominantly between 18 and 25 years, similar to that in Busenitz et al.'s (2000) study.
We had to include only graduate students in our India sample for the simple reason that institutions of higher education there do not offer any undergraduate degrees in business. Even the few graduate business programs offered in the elite «Indian Institutes of Management», with
some 8 campuses spread across the country, were one-year diploma/certificate programs. In the case of China, although the business schools do offer undergraduate programs, we were advised by faculty colleagues of native Chinese origin that rarely do Chinese students decide to start a new business after completing an undergraduate program. Graduating students typically take up employment in companies or opt for graduate programs in business. In light of these country specific realities, we had inferred that graduate students in India and China are comparable to undergraduate students in the other countries for the purpose of our study. The demographic characteristics of the nine country samples are summarized in Table 2 and the descriptive statistics are presented in Table 3.
Results
Results from confirmatory factor analysis (Figure 1 and Table 4) evidence the comparability of our model, in terms of factor loadings, scale reliabilities, and goodness of fit indicators, with that of Busentitz et al. (2000) (the comparison is captured in Table 5). Factor analysis performed on each regional sample separate-
Table 2
Demographic characteristics of the global sample
Description of the line item Brazil Mexico Bulgaria Hungary Latvia Russia China India South Korea
Month and year of survey April 2006 July 2006 April 2006 March 2006 May 2006 Sept 2006 May 2006 Dec 2006 May 2006
Sample size 157 82 139 64 100 151 62 131 96
Gender
Female Male 39% 61% 61% 39% 52% 48% 55% 45% 44% 56% 71% 29% 50% 50% 37% 63% 56% 44%
Age (19-35 yrs) Mean age (yrs) 93% 21,6 96% 21 93% 21 98% 22 100% 20 98% 18,2 73% 33,9 100% 22,7 91% 24,5
Education
Undergraduate Graduate 100% 0% 100% 0% 59% 41% 0% 100% 100% 0% 100% 0% 0% 100% 0% 100% 79% 21%
# of foreign students excluded from analysis 2 2 3 0 46 8 0 1 2
Table 3
Means, standard deviations, and correlations: Global sample
Mean SD 1 2 3 4 5 6 7 8 9 10 11 12
Regulatory 1 3,48 1,59
Regulatory 2 3,30 1,43 0,50
Regulatory 3 3,48 1,49 0,54 0,50
Regulatory 4 3,82 1,43 0,38 0,36 0,45
Regulatory 5 2,84 1,39 0,39 0,37 0,46 0,47
Cognitive 1 3,50 1,60 0,27 0,16 0,22 0,24 0,32
Cognitive 2 3,66 1,58 0,20 0,13 0,13 0,15 0,19 0,53
Cognitive 3 3,58 1,49 0,20 0,15 0,14 0,15 0,18 0,51 0,72
Cognitive 4 4,09 1,54 0,22 0,09 0,12 0,17 0,15 0,39 0,51 0,54
Normative 1 4,35 1,61 0,18 0,19 0,19 0,17 0,17 0,23 0,20 0,21 0,24
Normative 2 4,54 1,66 0,22 0,21 0,19 0,13 0,20 0,21 0,15 0,15 0,16 0,55
Normative 3 4,55 1,59 0,13 0,18 0,21 0,19 0,17 0,16 0,19 0,17 0,14 0,33 0,49
Normative 4 4,44 1,54 0,12 0,17 0,16 0,15 0,15 0,19 0,18 0,19 0,14 0,33 0,46 0,66
Note: * n = 901; all correlations significant at p < 0,05 (2-tailed)
ly showed that the loading patterns were similar, indicating model equivalence across the regional samples as well.
Results of the analysis of variance (ANOVA) across the three regional samples showed significant differences across the three regions in their overall institutional profiles, as well as along the three underlying dimensions: regulatory, cognitive, and normative (Table 6). The in-
stitutional environment in Asia was found to be the most favorable (strictly speaking, least unfavorable) for the promotion of entrepreneurship, followed by CEE and Latin America (F = 45,17, p < 0,01). Asia also lead the remaining two regions in all three individual dimensions of the institutional environment (regulatory dimension F = 42,58, p < 0,01; cognitive dimension F = 52,36, p < 0,01; and normative dimension
Table 4
Model fit summary: Global sample
Model NPAR CMIN DF P CMIN /DF NFI Delta1 RFI rho1
Default 42 338,2 62 0,00 5,5 0,91 0,87
saturated 104 0 0 1,00
Independence 13 3751,7 91 0,00 41,2 0,00 0,00
IFI Delta2 TLI rho2 CFI PRATIO PNFI PCFI NCP
default 0,93 0,89 0,93 0,68 0,62 0,63 276,20
saturated 1,00 1,00 0,00 0,00 0,00 0,00
Independence 0,00 0,00 0,00 10,00 0,00 0,00 3660,66
FMIN RMSEA PCLOSE AIC BCC
default 0,41 0,07 0,00 422,20 423,64
saturated 0,00 208,00 211,56
Independence 4,52 0,22 0,00 3777,66 3778,10
ECVI MECVI HOELTER .05 HOELTER .01
default 0,51 0,51 201 224
saturated 0,25 0,25
Independence 4,54 4,54 26 28
Table 5
Model statistics: Comparison with Busenitz et al.'s (2000) study
Indicator Busenitz et al. (2000) Our study
Number of factors extracted 3 3
Scale reliabilities
Regulatory dimension 0,76 0,80
cognitive dimension 0,68 0,82
Normative dimension 0,81 0,78
overall 0,78 0,82
Goodness of Fit Indicators
cfi 0,94 0,93
NFI 0,91 0,91
IFI 0,94 0,93
rmsea 0,05 0,07
F = 32,17, p < 0,01). While CEE emerged second in regulatory and cognitive dimensions, Latin America was placed second along the normative dimension.
We followed this up by investigating the differences in student perceptions within each of the three global regions. The model fit summary and the confirmatory factor analysis for
entrepreneurship in Mexico was perceived as more favorable compared to Brazil: overall (F = 27,59, p < 0,01), as well as along the regulatory (F = 40,80, p < 0,01) and cognitive dimensions (F = 35,68, p < 0,01). However, there were no significant differences in the perceived favorability of the normative pillar of the institutional environment between the two countries.
The corresponding results for Central and Eastern Europe are presented in Table 9, Figure 3, and Table 10, respectively. Very similar to the results in Latin America, we observed significant differences across the four CEE countries in terms of the overall institutional environment (F = 3,83, P < 0,01), the regulatory (F = 10,06, p < 0,01) and the cognitive dimensions (F = 7,68, p < 0,01), with no significant differences in the normative pillar. Interestingly, Latvia emerged as the country with the most conducive institutional environment for the promotion of entrepreneurship overall, while Hungary was ranked the highest along the regulatory dimension, and Russia was placed at the top along the cognitive dimension.
The results for Asia are presented in Table 11, Figure 4, and Table 12 respectively. Here again, we observed significant differences across the three economies in the perceptions of the overall institutional environment for entrepreneurship (F = 12,95, p < 0,01), as well as two of the three individual pillars: cognitive (F = 13,80, p < 0,01) and normative (F = 18,19, p < 0,01). There were no significant differences
Table 6
Means, standard deviations and results of ANOVA: Global sample
Country Institutional Profile Regulatory Cognitive Normative
Mean (Rank) s.d. Mean (Rank) s.d. Mean (Rank) s.d. Mean (Rank) s.d.
Asia 3,34 (1) 0,73 3,39 (1) 0,97 3,04 (1) 0,92 3,60 (1) 0,89
CEE 2,90 (2) 0,70 2,81 (2) 0,84 2,85 (2) 0,91 3,04 (3) 0,92
Latin America 2,84 (3) 0,58 2,80 (3) 0,79 2,27 (3) 0,82 3,47 (2) 0,86
F test 45,17** 42,58** 52,36** 32,17**
Note: ** p < 0,01
Figure 1. Confirmatory factor analysis: Global sample
Latin America are presented in Table 7 and Figure 2, whereas the results from the analysis of variance tests are reported in Table 8. The analysis of variance shows that the institutional environment for the development of
Table 7
Model fit summary: Latin America
Model NPAR CMIN DF P CMIN /DF NFI Delta1 RFI rho1
Default 42 110,89 62 0,00 1,79 0,87 0,81
saturated 104 0,00 0 1,00
Independence 13 876,82 91 0,00 9,64 0,000 0,000
Model IFI Delta2 TLI rho2 CFI PRATIO PNFI PCFI NCP
default 0,94 0,91 0,94 0,68 0,60 0,64 48,89
saturated 1,00 1,00 0,00 0,00 0,00 0,00
Independence 0,00 0,00 0,00 1,00 0,00 0,00 785,82
Model FMIN RMSEA PCLOSE AIC BCC
default 0,68 0,07 0,06 194,89 202,83
saturated 0,00 208,00 227,68
Independence 5,41 0,23 0,00 902,82 905,28
Model ECVI MECVI HOELTER.05 HOELTER.01
default 1,20 1,25 119 133
saturated 1,28 1,41 22 24
Independence 5,57 5,59
Table 8
Means, standard deviations and results of ANOVA: Latin America
Country Institutional Profile Regulatory Cognitive Normative
Mean (Rank) s.d. Mean (Rank) s.d. Mean (Rank) s.d. Mean (Rank) s.d.
Brazil 2,71 (2) 0,53 2,58 (2) 0,74 2,05 (2) 0,69 3,49 (1) 0,80
Mexico 3,11 (1) 0,60 3,22 (1) 0,70 2,68 (1) 0,89 3,43 (2) 0,97
F test 27,59** 40,80** 35,68** 0,31
Note: ** p < 0,01
in the perceived favorability of the regulatory environment. While China was ranked as the Asian country with the most favorable institutional environment for entrepreneurship overall as well as the country with the most conducive cognitive environment, India emerged at the top along the regulatory and normative dimensions. The institutional environment for entrepreneurship in South Korea was consistently ranked as the least favorable for entrepreneur-ship among the three Asian economies.
Discussion
Our study sought to explore the differences in the perceptions of the institutional environments for entrepreneurship among university students in nine emerging economies in Central and Eastern Europe, Asia, and Latin America. Results from statistical testing yielded three main findings which are discussed below.
First, university students in all the nine countries agree that the overall institutional environ-
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ment in their respective countries is generally unfriendly to new venture creation. This is evident from the fact that on a 7-point Likert-type scale, the mean scores for the institutional environment overall, as well as for the three individual dimensions were below 4, the neutral anchor. In contrast, Busenitz et al.'s (2000) study found that in four of the six developed economies they studied, the overall institutional environments were conducive to entrepreneurship.
This finding of our study is consistent with the 2012 report of the Global Entrepreneurship Monitor (GEM) (Xavier et al. 2012). The GEM report found that only 45% of the respondents in Mexico, 52% in Brazil, 32% in China, 13% in South Korea, 33% in Latvia, 11% in Hungary, and 20% in Russia saw entrepreneurial opportunities (Bulgaria was not included in the 2012
GEM study, while the results for India were not available in time for the report). This is in contrast to the innovation-driven Nordic countries of Europe, which are traditionally ranked among the most competitive economies in the world (World Economic Forum 2013). For example, 55% of the GEM respondents in Finland, 64% in Norway, and 66% in Sweden saw entrepreneurial opportunities. Similarly, the perceived social status of successful entrepreneurs in the Nordic countries in Europe was also higher. Thus, 86% of the respondents in Brazil, 54% in Mexico, 76% in China, 70% in South Korea, 74% in Hungary, 53% in Latvia, and 63% of the respondents in Russia reported that successful entrepreneurs enjoyed high social status, compared to 80% in Norway and 83% in Finland. It transpires that where the institutional environment is perceived as unfavorable, it gets reflected in the perceptions of feasibility and desirability of undertaking entrepreneurial activities.
Of course, we cannot rule out the effect of economic development on the perceptions of entrepreneurial opportunities and the resulting entrepreneurial intentions. The stage of a country's economic development influences the scope of entrepreneurial activity as well as the nature of entrepreneurial initiatives. The economists compiling The World Competive-ness Report (World Economic Forum 2013) classify economies into five stages of development: namely i) factor-driven, ii) in transition from factor-driven to efficiency-driven, iii) efficiency-driven, iv) in transition from efficiency-driven to innovation-driven, and v) innovation-driven. Data from the GEM studies show that entrepreneurial activity generally follows a curvilinear, «U»-shaped relationship with GDP per capita. At low levels of per capita GDP, the entrepreneurial sector provides job opportunities and potential for the creation of new markets (Audretsch 2007; Minniti 2010). As per capita income increases, the emergence of new technologies and economies of scale allow larger and more established firms to satisfy the increasing demand of growing markets and increase their relative role in the economy, while
Table 9
Model fit summary: Central and Eastern Europe
Model NPAR CMIN DF P CMIN /DF NFI Delta1 RFI rho1
Default 42 192,04 62 0,000 3,10 0,85 0,79
saturated 104 0,000 0 1,00
Independence 13 1313,47 91 0,000 14,43 0,00 0,00
IFI Delta2 TLI rho2 CFI P RATIO PNFI PCFI NCP
default 0,90 0,84 0,89 0,68 0,58 0,61 130,04
saturated 1,00 1,00 0,00 0,00 0,00 0,00
Independence 0,00 0,00 0,00 1,00 0,00 0,00 1222,48
FMIN RMSEA PCLOSE AIC BCC
default 0,62 0,08 0,00 276,04 280,03
saturated 0,00 208,00 217,87
Independence 4,25 0,21 0,00 1339,48 1340,71
ECVI MECVI HOELTER.05 HOELTER.01
default 0,89 0,91 131 147
saturated 0,67 0,71
Independence 4,34 4,34 27 30
Table 10
Means, standard deviations and results of ANOVA: Central and Eastern Europe
Country Institutional Profile Regulatory Cognitive Normative
Mean (Rank) s.d. Mean (Rank) s.d. Mean (Rank) s.d. Mean (Rank) s.d.
Bulgaria 2,75 (4) 0,78 2,54 (4) 0,87 2,74 (3) 0,99 2,97 (4) 1,01
Hungary 2,91 (3) 0,54 3,19 (1) 0,76 2,56 (4) 0,73 2,30 (3) 0,74
Latvia 3,10 (1) 0,47 3,04 (2) 0,54 2,83 (2) 0,87 3,44 (1) 0,75
Russia 3,02 (2) 0,70 2,85 (3) 0,79 3,19 (1) 0,84 3,03 (2) 0,94
F test 3,83** 10,06** 7,68** 2,03
Note: ** p < 0,01; * p < 0,1
the role of smaller and newer firms declines (Acs, Szerb 2007). Finally, in the third stage, the role played by the entrepreneurial sector in countries with higher GDP increases again, as more individuals have the resources to go into business in an economic environment that may present high-potential opportunities (Wennekers et al. 2005; Minniti 2010). Eight of the emerging economies included in our sample are ef-
ficiency-driven, and only the Republic of Korea could be considered innovation-driven. At the efficiency stage of economic development, large established firms play an increasingly important role in the economy, offering stable employment and are a viable alternative to starting an entrepreneurial business. This may partially account for university students' hesitant attitudes towards entrepreneurship generally.
0,53
Figure 3. confirmatory factor analysis: central and Eastern Europe
Surprisingly, and contrary to the «GDP per capita — level of entrepreneurial activity» hypothesis, the perception of entrepreneurial opportunities and the level of entrepreneurial intentions in South Korea, an innovation-driven economy, were markedly lower than those in the efficiency-driven economies, demonstrating that factors other than the level of economic development could affect the culture of entrepreneur-ship in a country. We'll address these surprising findings later on in the discussion.
The effect of perceived favorability of the institutional environment on the perceived feasibility and desirability of entrepreneurial behavior has important implications for theory. Models such as ours, based on the perceptions of the institutional environment for entrepreneurship, complement entrepreneurial intentions-focused models, such as Azjen's (1987) Theory of
Figure 4. confirmatory factor analysis: Asia
Planned Behavior (TPB). In the latter, entrepreneurial intentions are shaped by three influential factors vis-à-vis planned behavior: personal attitudes, social norms, and perceived behavioral control. Interestingly, as discussed earlier in the paper, extant empirical studies that had tested Azjen's model, used university student samples as is ours (Linân et al. 2011; Autio et al. 2001 ; Kolvereid 1996). Consistent with calls to extend the TPB model by including antecedents, such as the institutional influences on individual cognitions (Linân et al. 2011; Lim et al. 2010), we believe that complementing the TPB model with an institutional perspective might offer both a more insightful, and a more robust explanation of entrepreneurial intentions and entrepreneurial behavior among university students.
Our second finding is based on the interregional differences observed in the percep-
Table 11
Model fit summary: Asia
Model NPAR CMIN DF P CMIN /DF NFI Delta1 RFI rho1
Default 42 185,04 62 0,000 3,00 0,86 0,79
Saturated 104 0,000 0 1,00
Independence 13 1291,49 91 0,000 14,19 0,00 0,00
IFI Delta2 TLI rho2 CFI P RATIO PNFI PCFI NCP
Default 0,90 0,85 0,90 0,68 0,58 0,61 123,73
Saturated 1,00 1,00 0,00 0,00 0,00 0,00
Independence 0,00 0,00 0,00 1,00 0,00 0,00 1200,49
FMIN RMSEA PCLOSE AIC BCC
Default 0,65 0,08 0,00 269,73 274,05
Saturated 0,00 208,00 218,71
Independence 4,51 0,21 0,00 1317,49 1318,83
ECVI MECVI HOELTER.05 HOELTER.01
Default 0,94 0,96 126 140
Saturated 0,73 0,77
Independence 4,61 4,61 26 28
Table 12
Means, standard deviations and results of ANOVA: Asia
Country Institutional Profile Regulatory Cognitive Normative
Mean (Rank) s.d. Mean (Rank) s.d. Mean (Rank) s.d. Mean (Rank) s.d.
China 3,61 (1) 0,83 3,39 (2) 1,10 3,35 (1) 1,00 3,80 (2) 0,94
India 3,47 (2) 0,71 3,46 (1) 1,03 3,17 (2) 0,92 3,81 (1) 0,87
South Korea 3,04 (3) 0,57 3,30 (3) 0,97 2,66 (3) 0,72 3,17 (3) 0,72
F test 12,95** 0,71 13,80** 18,19**
Note: ** p < 0,01
tions of institutional environments for entrepre-neurship. Overall, Asia emerged as the region most conducive to entrepreneurship, followed by Central and Eastern Europe with the Latin American region lagging behind. We attribute these findings partially to the regional economic prospects at the time of the survey. Thus, the real GDP growth rate in 2006, the year of the survey, was 12.7% in China, 9.66% in India, and 5.18% in Korea, compared with 3.96% in Brazil
and 5.06% in Mexico (OECD 2011). The regional economic conditions may have rendered the respondents more optimistic about the environment for economic activity generally.
Significant differences were observed within each of the three regions as well. In Central and Eastern Europe, Latvia emerged at the top as most favorable environment for new firm formation, followed by Russia, Hungary, and Bulgaria in that order. In Latin America, Mexico was per-
ceived as more favorable for entrepreneurship than Brazil. As expected, in both of these regional subsamples, we also found that the differences were largely due to the perceived differences in the regulatory and cognitive dimensions of the institutional environment, whereas differences in the normative environment were not significant.
Within the Asian region, the institutional environment in China emerged as most conducive to entrepreneurship, followed by India and South Korea. This was due to the perceived differences in the normative and cognitive environments, whereas the regulatory environment did not emerge as a significant factor. In sum, the university students across the three regions were most sensitive to differences in the cognitive dimension (significant differences in all three regions), followed by the regulatory dimension (significant differences in two of the three regions), and finally the normative dimension of the institutional environment (significant differences only in one of the regions).
These findings confirm our initial premise that university students, because of their youthful age, would be more sensitive to differences in the institutional influences that they are most exposed to, namely the institutional arrangements governing the attainment of entrepreneurial knowledge and skills, as well as formal laws and regulations. A fruitful avenue for future empirical research would be to ascertain in greater depth the antecedents which shape these perceptions.
Finally, we noticed some interesting differences in the perceptions of university students across the three institutional settings. Notably, none of the nine countries received a uniform high rank across all three dimensions of the institutional environment, and some received contrasting rankings. For example, Hungary was accorded the highest score on the regulatory dimension and the lowest score on the cognitive dimension. In contrast, Russia was accorded the highest score on the cognitive dimension, but the second lowest score on the regulatory dimension of the institutional environment. This finding offers additional empirical evidence that the institutional environment across emerging economies
is in the process of shaping up, experiencing «highs» and «lows» in its various manifestations.
Paradoxically, the institutional environment in the Republic of Korea was consistently ranked as the least conducive to entrepreneur-ship in the Asian region, even though, according to objective indicators, such as those captured in the World Bank's 2012 «Doing Business» project, South Korea ranks 22nd among 185 countries in the ease of starting a new business, whereas China ranks 153rd and India a distant 169th (World Bank 2013a). Recent studies by Gupta et al. (2012a, 2012b) document similarly unfavorable perceptions. A potential explanation may lie in prior work by Begley and Tan (2001), who had used Earley's (1997) theory of face in order to explore the socio-cultural environment for entrepreneurship in six East Asian and four Anglo-Saxon countries. Begley and Tan (2001 ) found that fear of failure and the entrepreneur's perceived social status predicted interest in entrepreneurship more strongly in East Asia than in the West. Indeed, according to the 2012 Global GEM report, 43% of the respondents in South Korea reported they feared failure, compared to 36% in China, and 70% reported successful entrepreneurs enjoyed high social status compared to 76% in China. Consistent with this, 13% of the respondents in South Korea expressed entrepreneurial intentions compared to 20% in China (Xavier 2012). Our finding, therefore, reinforces the need for fine-grained and clearly defined constructs and scales to evaluate both the formal and the informal pillars of the institutional environment (Mayer, Peng 2005). Indeed, a recent study by Val-dez and Richardson (2013) documented that the descriptive power of normative and cultural-cognitive institutions in explaining entrepreneurial activity is higher than that of regulative institutions or per capita gross domestic product.
Limitations and future research
Our findings need to be interpreted within the boundaries and limitations of the study. As pointed out in our methods section, Busenitz et
al. (2000) adopted somewhat restrictive definitions of the constructs, which may not capture their rich connotations in the new institutional theory. Moreover, institutional idiosyncrasies preclude the straightforward generalization of our results across national contexts. We feel confident, however, in our finding that the institutional environment tends to be perceived as rather unfavorable for new venture formation across many emerging economies. Finally, coming from a cross-sectional study, our findings provide only a snapshot in time, while institutional profiles do change over time, albeit somewhat slowly in some respects and faster in others. For instance, the ease of starting a business has improved considerably in all nine countries since the time of our study. To take India as an example, even though the number of procedures needed to start a new business have gone up from 11 to 12, the time necessary to start a new business has decreased from 71 days to 27 days, while the cost of starting a new business as percent of per capita income has gone down from 62% to 49.8% (World Bank 2013a). We call for longitudinal studies to capture the dynamic coevolution of institutions and entrepreneurship in emerging economies.
Conclusion
Despite the foregoing limitations, our study does yield important implications for public policy. The university students in our sample, spread across three global regions and nine countries, uniformly felt that the institutional environment in their respective countries is largely unfavorable to entrepreneurship. While there are significant differences in the regulatory and cognitive dimensions across the nine countries, the normative dimension was perceived as generally unfavorable. There is thus an urgent need to enhance the formal as well as informal institutions to unravel entrepreneur-ship in emerging economies. In order to unlock the entrepreneurial ambitions of the educated youth, it is imperative to enact entrepreneur-friendly laws, invest in entrepreneurship educa-
tion, and promote social attitudes conducive to entrepreneurship in the emerging economies around the world.
Acknowledgements
We would like to thank our colleagues in Russia, Latvia, Hungary, Bulgaria, Brazil, and India for their invaluable help in collecting the data. Without their generous contribution of time and effort, this study would not have been possible. All errors and omissions remain our own.
Appendix. Survey items
Regulatory dimension
Regulatory 1: Government organizations in this country assist individuals with starting their own businesses.
Regulatory 2: The government sets aside government contracts for new and small businesses.
Regulatory 3: Local and national governments have special support available for individuals who want to start a new business.
Regulatory 4: The government sponsors organizations that help new businesses develop.
Regulatory 5: Even after failing in an earlier business, the government assists entrepreneurs in starting again.
Cognitive dimension
Cognitive 1: Individuals know how to legally protect a new business.
Cognitive 2: Those who start new businesses know how to deal with much risk.
Cognitive 3: Those who start new businesses know how to manage risk.
Cognitive 4: Most people know where to find information about markets for their products.
Normative dimension
Normative 1: Turning new ideas into businesses is an admired career path in this country.
Normative 2: In this country, innovative and creative thinking is viewed as a route to success.
Normative 3: Entrepreneurs are admired in this country.
Normative 4: People in this country tend to greatly admire those who start their own business.
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Ённи Р. Б., доктор делового администрирования, доцент кафедры управления, Янгстаунский государственный университет, Янгстаун, Огайо, США, [email protected]
Манолова Т. С, доктор делового администрирования, доцент, университет управления Бентли, Уолтхем, Массачусетс, США, [email protected]
ИНСТИТУЦИОНАЛЬНЫЙ КОНТЕКСТ ПРЕДПРИНИМАТЕЛЬСТВА В СТРАНАХ С РАЗВИВАЮЩЕЙСЯ ЭКОНОМИКОЙ: СРАВНЕНИЕ ВОСПРИЯТИЯ СТУДЕНТАМИ ВУЗОВ ДЕВЯТИ СТРАН
В этом исследовании, авторы сравнили и сопоставили восприятие институциональной среды развития предпринимательства студентами университетов в девяти странах с развивающейся экономикой трех глобальных регионов: Центральной и Восточной Европы (Болгария, Венгрия, Латвия, и Россия), Азии (Китай, Индия, и Республика Корея) и Латинской Америки (Бразилия и Мексика). Полученные результаты показывают, что институциональная среда воспринимается как в целом неблагоприятная для создания новых предприятий во всех трех глобальных регионах и составляющих их девяти странах. Однако институциональное окружение различается в разных измерениях. Причины таких расхождений можно проследить в различиях правовых систем, когнитивных структур и нормативных традиций в разных регионах и странах. Следовательно, институциональные среды представляют различные возможности и вызовы для студентов тех вузов, которые выбирают предпринимательскую карьеру. Авторы обсуждают теоретическое, управленческое и общественно-политическое применение своих выводов.
Ключевые слова: предпринимательство, институциональная среда, развивающиеся экономики, студенты вузов.
