ISSN 0798 1015

Vol. 38 (Nº 52) Year 2017. Page 2

International entrepreneurship under an institutional regulative dimension: a cross-national study

Emprendimiento internacional desde una dimensión regulativa institucional: Un estudio transnacional

TABARES, Alexander 1

Received: 13/06/2017 • Approved: 15/07/2017

Content

1. Introduction

2. Theoretical framework

3. Methodology

4. Results

5. Conclusions

Acknowledgments

Bibliographic references

1. Introduction

The clear increase in the volume of international businesses last two decades due to globalization has led public policy agendas to foster programs that could help firms and entrepreneurs become successful in foreign markets. The growing scholar interest to understand this international entrepreneurship in the context of not only SMEs but also multinationals has identified some determining factors from three major levels of analysis: individual (Zahra, Korri and Yu, 2005), firm (Tabares, Alvarez and Urbano, 2015) and environment (Gnyawali and Fogel, 1994), whether industry or country, as well as from different theoretical approaches. One of the most distinguishing frameworks analyzing this phenomenon has been the Institutional Theory which has proven to be especially helpful to entrepreneurship (Bruton, Ahlstrom and Li, 2010; Urbano and Alvarez, 2014) and international entrepreneurship research since institutional environment can define, create or limit entrepreneurial opportunities and its consequent entrepreneurial activity rates (Aldrich and Fiol, 1994; Dana 1987; Gnyawali and Fogel, 1994; Hwang and Powell, 2005; Manolova, Eunni and Gyoshev, 2008; Shapero and Sokol, 1982).

Although several scholars under this theoretical framework have analyzed three institutional dimensions (regulative, normative and cultural-cognitive) on the field of entrepreneurship (Busenitz, Gomez and Spencer, 2000; Spencer and Gomez, 2004; Gupta, Yayla, Sikdar and Cha, 2012; Kostova, 1997; Manolova et al., 2008; Scott, 1995), few authors have studied the impact of these institutional dimensions on international entrepreneurship, specifically the relevance of regulations in this process (Stephen, Urbano and Van, 2009) and much less using cross-national data (Lee, Lim and Pathak, 2011; Nielsen and Lassen 2012).

Thus, the main purpose of this article is to assess the efficiency of the regulative dimension on international entrepreneurship from an institutional framework. Since regulations (covering government finance, government policies in terms of support, tax and government programs, commercial-legal infrastructure, internal market burdens and entry regulation) have been applied to business activities without considering the development level of countries, the study intends to fill this gap by considering a cross-national sample of 9 Latin American emerging economies and 9 developed economies. Data for the comparative analysis are obtained from the Global Entrepreneurship Monitor (GEM) project (2015-2016) which has been one of the most important studies of entrepreneurship that provides high quality information and comprehensive reports based on over 200,000 interviews in 62 countries, specialists in entrepreneurship research, academic and research institutions.

In this paper it is empirically demonstrated that in Latin American emerging economies conditions in public policy regulations have a lower influence on entrepreneurial activity than in developed economies, probably because of their economy size in terms of GDP and its level of development. Concretely, the main findings of the current research indicate a higher influence of government tax-bureaucracy, the government programs and commercial-legal infrastructure both the developed and emerging economies, meanwhile, the government finance in both economies is assessed as the lowest regulative condition.

The article is structured as follows. After this brief introduction, in the second section, a theoretical framework introducing the relationship between institutional regulative dimension and international entrepreneurship is established and thus one hypothesis is proposed. In the third section, the details of the research methodology are presented. In the fourth section, the empirical results of the study are discussed. Finally, the article points out the most relevant conclusions and future lines of research.

2.1. International entrepreneurship versus institutional regulative dimension

International entrepreneurship is defined as the ability to discover, enact, evaluate, and exploit opportunities across national borders to create future goods and services. (De Carolis, Litzky and eddleston, 2009; McDougall and Oviatt, 2000; Shane and Venkataraman 2000; Zahra et al. 2005). Among multiple factors that influence, define and shape these international entrepreneurial opportunities, the social context (Cano, Tabares and Alvarez, 2017) and the institutional environment (Aldrich and Fiol, 1994; Gnyawali and Fogel, 1994; Hwang and Powell, 2005; Manolova et al., 2008; Mueller and Thomas, 2000; Reynolds, Hay and Camp, 1999; Reynolds, Hay, Bygrave, Camp and Autio, 2000; Reynolds, Camp, Bygrave, Autio and Hay, 2001; Valdez and Richardson, 2013; Welter, 2005; Welter and Smallbone, 2011) are considered important determining factors. According to North (1990, 2005), country institutions in the form of regulative, normative and socio-cultural dimensions could help defining, creating or limiting entrepreneurial opportunities and its consequent entrepreneurial activity rates national and internationally. Particularly, the institutional regulative dimension could enhance or repress this international entrepreneurial intention (Dana, 1987).

The regulative dimension consists of government policies, in terms of finance support, programs, taxes, commercial-legal infrastructure, internal market burdens and entry regulation, that provide support for new businesses, reduce the risks for individuals starting a new company and facilitate entrepreneurs’ efforts to acquire resources (Busenitz et al. 2000). Similarly, laws and regulations can specify the responsibilities of small business owners and assign property rights to go abroad and compete with sustainable competitive advantage (Spencer and Gomez 2004). There are different types of government policies to support entrepreneurship (Gnyawali and Fogel 1994). The first policy aims to lower the entry barriers to new firm formation, for example the time taken to start a business, the number and cost of the permits or licenses required, or the minimum capital requirements of a new firm (Van Stel, Storey and Thurik, 2007). Governmental regulation is generally perceived negatively by potential entrepreneurs (Gnyawali and Fogel 1994), who may be discouraged from starting a business if they have to follow many rules and procedures (Dana 1990). A second policy option aims to reduce the barriers to expansion and growth, including the difficulties over the hiring and firing of labor, the tax regime or closing a business (Van Stel et al. 2007). In fact, many empirical studies suggest that rigidities in labor regulations have a negative impact on entrepreneurial activity (Klapper, Laeven and Rajan, 2006; Stephen et al. 2009).

A third policy option aims to provide finance directly or indirectly, and to improve the access to credit. Thus, government programs focused on providing financial support, such as preferential treatment for entrepreneurial ventures (Ho and Wong 2007; Spencer and Gomez 2004), access to bank credit by lowering capital requirements, creation of investment companies, credit with low interest rates and credit guarantee schemes (Gnyawali and Fogel 1994), contribute to the promotion of new businesses. A fourth policy aims to provide information, training and other non-financing support to entrepreneurs. Particularly, entrepreneurs need assistance in preparing business plans and conducting market studies and advice on how to obtain loans and facilitate access to entrepreneurial networks (Gnyawali and Fogel 1994).

According to this logic and also reflecting the previously discussed research, it is proposed the following hypothesis:

Hypothesis 1: A favorable regulative dimension increases the probability of defining, creating or limiting entrepreneurial opportunities and its consequent entrepreneurial activity rates national and internationally.

As it is stated before, data analysis is obtained from the Global Entrepreneurship Monitor (GEM) project (2015-2016) which has been one of the most important studies of entrepreneurship that provides high quality information and comprehensive reports based on over 200,000 interviews in 62 countries, specialists in entrepreneurship research, academic and research institutions. Moreover, this global report covers results based on 62 economies and it is complemented with a National Expert Survey (NES), which considers the expert perception, knowledge and expectations on entrepreneurship and international entrepreneurship. Different from other studies that use the GEM study as their source, it is referred the established business ownership rate, which is taken from the total entrepreneurial activity rate (TEA), as the dependent variable of the study.

As such, GEM defines the established business owners as adults currently owning/managing and operating a young business (up to 3.5 years old). The independent variables are taken from the entrepreneurship ecosystem that originally represents the combination of 12 conditions that shape the context in which entrepreneurial activities take place. From these twelve conditions, it is selected six conditions related to the institutional regulative dimension (government finance, government support, government tax-bureaucracy, government programs, commercial-legal infrastructure and internal market burdens-entry regulation). The efficiency assessment is obtained from a Likert Scale, by which National Experts measure the six institutional regulative conditions and assign a grade to each one using a scale from 1 to 9, where nine (9) represents a highly sufficient condition and one (1) a highly insufficient condition to enhance entrepreneurship.

Additionally, it is used the Gross Domestic Product (GDP) as well as the SME contribution to this rate for a comparative purpose but they are not considered as independent variables nor moderator variables: they are only outlined to have a reference of the importance of this breed of firms in the economic growth of the respecting GDP economy. As mentioned in the introduction, the empirical analysis considers a cross-national sample of nine (9) Latin American emerging economies that the GEM report identifies and names as efficiency-driven economies and nine (9) developed economies identified and named as innovative-driven economies. The latter classification of economies is adapted from the World Economic Forum (WEF), but they correspond to the previous characterization of emerging economies and developed economies respectively. According to this WEF’s classification, the factor-driven phase is dominated by subsistence agriculture and extraction businesses, with a heavy reliance on (unskilled) labor and natural resources. In the efficiency driven phase, an economy has become more competitive with further development accompanied by industrialization and an increased reliance on economies of scale, with capital-intensive large organizations more dominant. As development advances into the innovation-driven phase, businesses are more knowledge-intensive, and the service sector expands.

It is first presented the 18 economies classified according to the economic development level and ranked based on their GDP. Later, it is introduced the SME contribution to GDP and analyze explanatorily their participation and influence in the economic growth. The table 1 presents two groups of economies classified according to the development level (Efficiency-driven economy and innovation-driven economy) and then they are ranked based on their GDP from the highest to the lowest. Next to the GDP, it is presented the SME percent contribution to that GDP.

Table 1. Economic Development Level Vs GDP Classification Comparative Table

In the table 1, it may be observed that the highest rates of GDP in the innovation-driven economies correspond to Germany, USA and China. This indicates that these three economies are strong enough to pull the world economy. Their SME contribution to the corresponding country’s GPD shows the relevance and the determining influence of these firms in the economic development with averages over 53%. By contrast, we can see smaller economies such as Italy and Netherland with a SME contribution higher than the first three powerful economies with 63% and 67% respectively. Surprisingly, Canada seems to have the lowest SME contribution to the GDP with 27%. 

Contrastingly, in the efficiency-driven economies, it may be observed that the highest rates of GDP correspond to Brazil and Mexico. This indicates that these two economies are strong enough to pull the region economy and they offer opportunities for entrepreneurs to get into their markets. The SME contribution to the corresponding country’s GPD show the relevance and the determining influence of these firms in Mexico with 52% different from Brazil with only 27%. Respecting to SME contribution to the GDP, it is observed that Peru, Argentina, Colombia and Uruguay show rates 40% far from the innovation-driven economies presented.

Respecting to the independent variables, Table 2 reports the institutional regulative dimension conditions in terms of government finance, government support, government tax-bureaucracy, government programs, commercial-legal infrastructure and internal market burdens-entry regulation. The following variables are used to assess the efficiency of the institutional regulative dimension.

Table 2 reports the descriptive assessment on the institutional regulative dimension conditions. In this table, it may be observed that the highest rates of these regulative conditions are in the developed economies in comparison with Latin American emerging economies. Meanwhile the innovation-driven economies show a total average of the six regulative conditions worth of 49%, the efficiency-driven economies show a total average worth of 39%, a 10% average difference that shows evidence that the developed economies are doing better than emerging economies in shaping entrepreneurship ecosystem or regulative conditions.

In the developed economies, it is found relatively important what Switzerland and Netherlands are doing since they are distinguished to be the two countries with more and higher conditions for entrepreneurship. Switzerland is distinguished by a well regulative dimension assessment in terms of government tax-bureaucracy, government programs and commercial-legal infrastructure meanwhile Netherland is distinguished by government finance, government support and internal market burdens-entry regulation. By contrast, economies such as Italy and South Korea show the lowest levels with averages of 4.4 and 3.6 % respectively being the Italy case very particular with the 4 lowest regulative conditions which are government finance, government support, government tax-bureaucracy and government programs.

Table 2. Institutional Regulative Dimensions on Economic Development Level scores

In the Latin American emerging economies, it is observed that Chile and Mexico are ahead with two regulative condition highest scores followed by Uruguay and panama. Chile is distinguished by a well regulative dimension assessment in terms of government tax-bureaucracy and government programs meanwhile Mexico is distinguished by government finance and government support. By contrast, economies such as Colombia, Brazil, Peru and Argentina show the lowest levels with averages below 3.8. Surprisingly, Brazil shows the lowest scores in three regulative conditions such as government tax-bureaucracy, government programs and internal market burdens-entry regulation, despite its biggest GDP reports. One supposition that could be relevant to analysis is the correspondence of the low SME participation in the country GDP with the low regulative conditions for entrepreneurship.

The principal results show that institutional regulative dimensions in terms of government finance, government support, government tax-bureaucracy, government programs, commercial-legal infrastructure and internal market burdens-entry regulation have a positive and significant influence on entrepreneurial activity in both the developed economies and in emerging economies. Since this influence is stronger in the developed economies than in the emerging economies, it may be concluded that the economy size in terms of GDP and its level of development are positively correlated with entrepreneurial activity. Due to this cross-sectional analysis, results contradict previous scholar studies that claim that government size and development level are not necessarily correlated with entrepreneurial activity (Nystrom, 2008). More specifically, it can be seen that the government tax-bureaucracy, the government programs and commercial-legal infrastructure are the three highest assessed regulative conditions both in the developed and in emerging economies. Contrastively, the government finance in both economies is assessed as the lowest regulative conditions, indicating that finance should be enhanced since this institutional support has been shown as significant driver for entrepreneurship. As such, the availability of credit for entrepreneurial activity should be provided from the banking sector. Some studies have shown evidence that developed economies leverage finance support from the banking sector while the emerging economies do from the informal sector, a situation that makes difficult for SMEs to create business local and internationally (Stephen et al.2009).

As expected, a favorable regulative dimension increases the probability of defining, creating or limiting entrepreneurial opportunities and its consequent entrepreneurial activity rates national and internationally. However, the coefficient is particularly higher in developed economies than in emerging economies. Therefore, the findings offer support for hypothesis.

Through a cross-national sample of 9 Latin American emerging economies and 9 developed economies, using data from the Global Entrepreneurship Monitor (GEM) project report (2015-2016) and from an institutional theoretical framework, the study aims to assess the efficiency of six regulative dimension (covering government finance, government policies in terms of support, taxes and government programs, commercial-legal infrastructure, internal market burdens and entry regulation) on international entrepreneurship.

The main findings show that in Latin American emerging economies conditions in public policy regulations have a lower influence on entrepreneurial activity than in developed economies, probably because of their economy size in terms of GDP and its level of development. Concretely, the main findings of the current research indicate a higher influence of government taxes-bureaucracy, the government programs and commercial-legal infrastructure both the developed and emerging economies, meanwhile, the government finance in both economies is assessed as the lowest regulative condition.

The study advances the literature by providing new information on the institutional regulative factors that affect international entrepreneurial activity in the light of institutional economics. Also, the research could be useful for designing policies to foster international entrepreneurship in different environments. This study suffers from a number of limitations.  As is typical of studies investigating panel data, published sources may not be accurate.  Moreover, the Global Entrepreneurship Monitor (GEM) report still misses other important institutional regulative dimensions that can be surveyed. Finally, due to time constraints, it is not possible to collect the data from other sources to triangle and have a convergent analysis of the data for a better reliability and validity.

Future research should improve the proxy for variables, especially for independent variables getting closer to the conceptualization of the institutional dimensions. Also, further scholar studies should use other reliable data sources and apply statistical analysis to validate this empirical work.

Acknowledgments

The author appreciates helpful comments by Professors in Doctorate Program in the previous versions of this manuscript. Also, the author acknowledges the financial support from Colciencias and Universidad de Medellin.

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1. Universidad de Medellín. Management Magister, Management Doctorate student. atabares@udem.edu.co