Master’s Thesis Managing Multinationals

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Killing Dreams or Preventing Nightmares?

The Dual Effect of Institutional Quality on the Realization of Entrepreneurial Intentions.

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University of Groningen

Faculty of Economics and Business

Uppsala University

Faculty of Social Sciences Department of Business Studies

Author: Joren Kamerling Student number: S2958090 Supervisor: Dr. S.R. Gubbi

Co-assessor: Dr. L. Ge

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Abstract

The aim of this study is to analyze the influence of institutional quality on the realization process of entrepreneurial intentions. In this analysis a distinction is made between opportunity-based and necessity-based entrepreneurial intentions. Using Ajzen’s Theory of Planned behavior I hypothesized that Opportunity-based entrepreneurial intentions would better translate to actual entrepreneurship than necessity-based entrepreneurial intentions. Moreover, institutional quality was expected to directly influence both types of entrepreneurship and to moderate the realization of both types of intentions to actual entrepreneurship. In order to test these hypotheses, data from the Global Entrepreneurship Monitor, The Heritage Foundation, and The World Bank was adopted, and several regressions have been performed. The outcomes show that opportunity-based intentions and necessity-based intentions translate to entrepreneurship, but that opportunity intentions are not superior in determining levels of entrepreneurship. Moreover, institutional quality has shown to negatively influence necessity intentions, but not opportunity intentions. Finally, Institutional quality negatively moderates opportunity intentions, but not necessity intentions. In conclusion, this study contributes significantly to the literature by exposing this difference in domains in which institutional quality has an effect and by displaying the potential negative effect of institutional quality on realizing entrepreneurial intentions.

Keywords: Entrepreneurial Intentions, Opportunity Entrepreneurship, Necessity

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Introduction

Contextualizing entrepreneurship is imperative for understanding, how, when, and why entrepreneurship happens (Welter, 2011). However, the vast majority of literature has predominantly focused on entrepreneurs themselves and has overlooked the environment, which is of critical importance (Eckhardt & Shane, 2003; Aldrich & Ruef, 2006; Sine & David, 2010). Thus, there is a dearth of studies that analyze the environmental factors that stimulate entrepreneurial activity and the correlation between these factors and success (Sine & David, 2010). In recent years, the literature has started to answer to the call of contextualizing entrepreneurship. However, certain areas remain neglected. If one sheds light on the institutional environment, this can instantaneously be observed. For example, it has been found that institutional quality is a predictor for productive entrepreneurship, and that productive entrepreneurship, in turn, contributes to economic growth. Thus, entrepreneurship mediates between institutional quality and economic growth (Bosma, Content, Sanders, & Stam, 2018). Nevertheless, what remains untouched is the contextual influence on the realization of entrepreneurial intentions to actual entrepreneurship. For example, it is not unimaginable that institutional quality can either allow or restrict people’s entrepreneurial intentions to be realized into actual entrepreneurship, rather than directly influencing levels of entrepreneurship. Therefore, it is pertinent to know whether institutional quality directly affects intentions and subsequently levels of entrepreneurship. And whether it stimulates or limits the realization of these intentions. In this paper I accommodate the need of further exploration of such contextual influences on entrepreneurship. Hence, I will examine the influence of countries’ institutional quality on the realization of entrepreneurial intentions.

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realization from intentions to entrepreneurship as such can be seen as the ‘success rate’, that is, how well entrepreneurial intentions are actually translated into an established business.

Since opportunity and necessity intentions have socioeconomic differences and since they differ in terms of determinants, their translation into entrepreneurship is likely to differ as well. Following Ajzen’s (1991) argument that intentions are the best predictor of behavior, it is expected that in the context of entrepreneurship, both types of entrepreneurial intentions will positively translate into entrepreneurship. However, individuals with necessity-motivated intentions seem to face additional barriers to success. For example, opportunity entrepreneurs are reported to have less negative perceptions about financial support as compared to necessity entrepreneurs (van der Zwan, Thurik, Verheul, & Hessels, 2016). Consequently, opportunity-intentions are expected to better translate to entrepreneurship.

Moreover, a nation’s quality of institutions is expected to influence entrepreneurship in two ways. First, by directly influencing entrepreneurial intentions. Intentions remain the best predictor of behavior (Ajzen, 1991). Thus, institutional quality is expected to influence levels of entrepreneurship through entrepreneurial intentions. Secondly, it is also expected to moderate the realization of intentions to entrepreneurship. Here, institutional quality may limit or stimulate the realization of intentions to entrepreneurship.

Opportunity intentions are expected to be influenced positively by institutional quality through proper protection of property rights (Hessels, Van Gelderen, & Thurik, 2008; Bjornskov & Foss, 2013; Fuentelsaz, Gonzalez, Maicas, & Montero, 2015). Whereas, necessity intentions are expected to be negatively influenced by institutional quality because of the higher regulatory quality.

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Interestingly, the results show no such relation. It shows that institutional quality only moderates the opportunity intentions to entrepreneurship relation. However, this moderating effect is negative. Another interesting finding is the fact that institutional quality shows to influence different domains of entrepreneurship with respect to the realization of necessity and opportunity intentions. Where it has a direct, negative influence on necessity intentions, it shows to negatively moderate the opportunity-intention to entrepreneurship relation.

Consequentially, this research contributes to the literature by exposing the potential negative effect of institutional quality on realizing entrepreneurial intentions and by displaying the difference in domains in which institutional quality has an effect. It is a wakeup call to policy makers to remain critical in policy implementations and to keep assessing the possible negative externalities of said policies.

Entrepreneurial environment

To understand differences in the field of entrepreneurship, it is vital to look beyond the characteristics of the entrepreneur and include the environmental effects. This is something that was ignored before the beginning of this century. In the beginning of this century, attention shifted from the individual characteristics of the entrepreneur towards explaining the role a context plays in determining who becomes an entrepreneur, which structures are used, and which types of organizations are founded. One area of the environment where attention was redirected to was entrepreneurial opportunities emerging from the environment as an important influence (Eckhardt & Shane, 2003; Aldrich & Ruef, 2006). Simultaneously, researchers were examining institutional entrepreneurship, aiming to explain how new institutions arise or how existing ones transform. The aim was to explain the effect of entrepreneurship on institutions (Greenwood, Suddaby, & Hinings, 2002; Maguire, Hardy, & Lawrence, 2004). However, what has remained mostly untouched up until then was the effect that institutions might have on entrepreneurial processes of founding and managing new ventures (Sine & David, 2010).

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is that public investments in ‘infrastructure services’ could lead to an increase in productivity, as they complement the private investments that are undertaken by entrepreneurs (Bjornskov & Foss, 2013). Moreover, institutional quality has found to predict productive entrepreneurship, and entrepreneurship has found to contribute to economic growth (Bosma, Content, Sanders, & Stam, 2018). However, what remains unclear is the relationship between entrepreneurial intentions, institutional quality and actual entrepreneurship, and I elaborate on this in the next section.

Intentions and entrepreneurship

Why are some people determined to set up their own business and why do others prefer regular paid employment? Researchers have attempted to answer that question over the past decades. One pivotal argument that dominates the psychology literature on human behavior argues that one’s intentions are shaped by their attitude towards behavior, the subjective norm, and perceived behavioral control. Moreover, one’s intention is the main predictor of behavior (Ajzen, 1991). Thus, according to this theory, if an individual considers a certain behavior to be positive (attitude towards behavior) and this is considered by others to be positive (subjective norm), and the individual perceives to be in control of his behavior (perceived behavioral control), his intention will be to behave in that certain way. According to Ajzen’s theory intentions are the main predictor of behavior. Thus, the above three aspects are said to shape intentions, which in turn, is likely to result in actually behaving accordingly.

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Entrepreneurial intentions

One can consider an opportunity of receiving monetary rewards to be a motive of setting up an own venture. Thus, we can apply Ajzen’s theory to predict behavior in this setting. First of all, setting up a business has the potential to be considered a positive action by the individual and his social group. Additionally, the individual has the potential to perceive to be in control of his behavior. If this is the case, entrepreneurial intentions can be formed. Consequently, the individual may behave accordingly and start engaging in entrepreneurial activity.

However, motives for engaging in entrepreneurship differ between individuals. Not everyone views entrepreneurship as an opportunity to expand their abilities and to capitalize from it. In other cases, the individual intends to engage in entrepreneurship merely as an escape from dissatisfaction of previous jobs (Stoner & Fry, 1982). This is referred to as necessity-motivated entrepreneurship.

Interestingly, it has been found that there are strong differences in determinants of economic success between necessity and opportunity motives. For example, labor market experience and schooling are highly relevant for opportunity entrepreneurs, but not so much for necessity entrepreneurs. Additionally, research concludes that opportunities are better exploited by opportunity entrepreneurs, and that socioeconomic differences exist. Thus, to better identify the drivers of entrepreneurial success, a distinction between opportunity and necessity-based intentions should be made (Block & Wagner, 2010).

Opportunity-based entrepreneurial intentions

Opportunity-based entrepreneurship is associated with pull factors for setting up a new business. Pull factors can be for example the ambition to be independent or the need for achievement (van der Zwan, Thurik, Verheul, & Hessels, 2016).

Moreover, one’s decision to engage in entrepreneurship can be seen as a utility maximizing response (Douglas & Shepherd, 1999). Opportunity-based motives aim to capitalize off opportunities and thus maximize utility.

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Secondly, it is influenced by the attitude of others towards this behavior. Finally, the degree to which one perceives to be able to act upon the presented opportunity shapes the intentions. If personal and other’s perception towards setting up the business as result from the opportunity is positive, and the individual perceives to be in control, it is likely that opportunity-based intentions are formed.

However, not everyone acts upon opportunities that emerge. There are numerous reasons why people do not act upon such opportunities. Fundamentally, one needs to identify opportunities before one could act. Identifying opportunities is something that can be learned, both in terms of number of opportunities identified and the quality of opportunities (Saks & Gaglio, 2002). Identifying more entrepreneurial opportunities implies that there is a wider selection of opportunities to act upon. Thus, there is a higher chance that one of those opportunities fits with the personal preferences of the individual and is likely to positively influence one’s attitude towards behavior. Furthermore, identifying opportunities of higher quality may also increase one’s attitude towards behavior positively.

Moreover, opportunity-motivated entrepreneurs differ in terms of personality, socioeconomic characteristics and perceptions of entrepreneurial support. In terms of socioeconomic differences, opportunity-motivated entrepreneurs are younger, wealthier and more likely to be male. In terms of personality, opportunity-motivated entrepreneurs are more prevalent. Finally, opportunity entrepreneurs are more positive about the availability of start-up information and financial sstart-upport (van der Zwan, Thurik, Verheul, & Hessels, 2016).

Necessity-based entrepreneurial intentions

Setting up a new business does not per definition imply following a lifelong dream and capitalizing from opportunities. Some business owners have set up their business out of necessity. Having a necessity motive implies engaging in entrepreneurship because of the absence of alternative employment opportunities available (Block, Kohn, Miller, & Ullrich, 2014). This means becoming an entrepreneur as a last resort, as there is no alternative satisfactory option for economic activity present (Wong, Ho, & Autio, 2005). Necessity entrepreneurs are moderately more likely to desire to switch back to paid employment in a later stage of their entrepreneurial career (Kautonen & Palmroos, 2010).

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Secondly, because individuals seem to not only care about their work and work outcomes, but also about the whole process that leads to their decision to start a venture in the first place.

Necessity-motivated individuals often do not inherently want to set up their own business. However, as it is the best possible alternative, one’s attitude towards this behavior can still be considered to be positive. Some necessity entrepreneurs are ‘pushed’ into entrepreneurship by family pressure (van der Zwan, Thurik, Verheul, & Hessels, 2016), which can be considered part of the subjective norm that shapes entrepreneurial intentions.

Necessity-entrepreneurship requires significant planning and setting up a business still takes time. However, the motivation for engaging in entrepreneurship may be less relatable to a theory of planned behavior than when one freely decides to engage in entrepreneurship, as that behavior is not as much planned, as compared to opportunity-intentions. However, following Ajzen’s reasoning, the individual can make a judgement of how well he or she is able to execute the required actions, that is, to set up a business. This judgement can be considered to be their perceived behavioral control in this situation.

Entrepreneurial intentions and entrepreneurship

The vast literature on intentions agrees on two main points. Intentions are the best predictor of behavior (Bagozzi, Baumgartner, & Yi, 1989) and intentions and attitudes are perception based (Krueger Jr. & Brazeal, 1994). Setting up a new business takes time and involves some significant planning. Therefore, entrepreneurship is perfectly fit for applying intention models (Krueger Jr., Reilly, & Carsrud, 2000). Following this line of reasoning, entrepreneurial intentions are the best predictor of actual entrepreneurship. However, it is found that the entrepreneurial intentions derived from opportunity rather than necessity are performing better, and socioeconomic differences between the two exist. Thus, to better identify the drivers of entrepreneurship, a distinction should be made (Block & Wagner, 2010). In this section I will examine the ‘success rate’ of entrepreneurship. That is, the realization rate from intentions to actual entrepreneurship. Thus, I will analyze how well entrepreneurial intentions for both motives lead to actual entrepreneurship.

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are some fundamental differences between the two that are expected to influence the intensity of each relationship.

First of all, opportunity entrepreneurs responded more positively about the availability of start-up information (van der Zwan, Thurik, Verheul, & Hessels, 2016). This implies, that comparatively, necessity entrepreneurs can either base their decisions on limited information or spend additional time and resources to acquire the same level of information. Having information about setting up a business readily available allows opportunity entrepreneurs to better ground their decisions. If a decision is made based on inaccurate information, it is more likely to fail. Thus, in this case opportunity entrepreneurs are better grounding their decisions and thus are more likely to succeed.

Alternatively, necessity entrepreneurs could spend additional time and/or resources to come level. However, opportunity entrepreneurs can spend similar time and resources on the development of their business. Hence, in both cases opportunity entrepreneurs have a head start in the realization of intentions to actual entrepreneurship.

Moreover, opportunity-motivated entrepreneurs are generally wealthier and are more positive about receiving financial support (van der Zwan, Thurik, Verheul, & Hessels, 2016). Acquiring financial funds is of critical importance for setting up a new business. Since, making substantial capital investments is critical for the growth of new business ventures (Kor, Mahoney, & Michael, 2007). Hence, having more funds readily available implies facing less barriers in the journey to success. Necessity entrepreneurs either face the additional barrier of acquiring external funds or they are limited in their choices, and essentially limited in the growth of their venture by having less funds available for setting up their business.

Finally, opportunity entrepreneurs are more proactive as compared to necessity entrepreneurs (van der Zwan, Thurik, Verheul, & Hessels, 2016). Entrepreneurial proactiveness allows the organization to anticipate to the market’s needs and allows the company to respond better to competitors’ actions. This could lead to a first mover advantage, of which the company can capitalize. A positive relation between entrepreneurial proactiveness and business performance does exist (Blesa & Ripolles, 2003).

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H1a: Opportunity-based entrepreneurial intentions have a positive influence on levels of

entrepreneurship.

H1b: Necessity-based entrepreneurial intentions have a positive influence on levels of

entrepreneurship.

H1c: Opportunity-based entrepreneurial intentions are superior to necessity-based

entrepreneurial intentions in determining levels of entrepreneurship.

Institutional quality

The conceptualization of institutions in the international business field is dominated by three institutional approaches: (1) new institutional economics, (2) new organizational institutionalism, and (3) comparative institutionalism (Hotho & Pedersen, 2012). First of all, new institutional economics considers institutions to be the ‘rules of the game’ and predominantly emphasizes the formal rules and regulations, analyzed on the country level. Secondly, new organizational institutionalism focuses on organizational forms and organizational practices. Here, institutions are viewed as intra-organizational patterns and activities, which makes the organization the main unit of analysis. Finally, comparative institutionalism seeks to explain differences in socio-economic organizations between countries, which is also analyzed from a country level. In this paper I will adopt the viewpoint of new institutional economics. Thus, institutions are considered the set of constraints set by humans that shape human interaction or, in short, ‘the rules of the game’ (North, 1990). Nevertheless, these constraints shape the business setting and thereby determine the opportunities for organizations. Thus, institutions can both constrain or facilitate organizational performance.

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1997). Since the institutional environment significantly influences a firm’s competitive advantage it is of critical importance to take into account (Oliver, 1997). In the following sections the effect of institutions on entrepreneurial intentions and on the success rate will be analyzed.

Institutional quality and entrepreneurial intentions

An important aspect of institutional quality with respect to entrepreneurship is the effective protection of property rights. Protection of property rights is a key institution of a government as it guarantees incentives for entrepreneurs to engage in entrepreneurship. Proper protection of property rights benefits entrepreneurship, as it will allow businesses to operate in a safer way. Therefore, it provides an incentive to engage in both types of entrepreneurship (Fuentelsaz, Gonzalez, Maicas, & Montero, 2015). However, since a good protection of property rights allows for risk-taking and innovative behavior (Bjornskov & Foss, 2013), and this is a treat that is generally more prevalent in opportunity-motivated entrepreneurs (Hessels, Van Gelderen, & Thurik, 2008), it is expected to have a stronger effect on the development of opportunity intentions.

Moreover, educational institutions can teach students to identify a profitable and feasible business concept. In that way, educational institutional quality can foster the identification of entrepreneurial intentions (Saks & Gaglio, 2002). Individuals can learn to spot entrepreneurial opportunities of higher quality (DeTienne & Chandler, 2004). This is likely to affect the perceived feasibility of the opportunity entrepreneur. Which stimulates the formation of entrepreneurial intentions. This is especially relevant for opportunity entrepreneurs, as these are competences that improve the identification of opportunities.

Additionally, individuals can learn to spot more opportunities through education (DeTienne & Chandler, 2004). Identifying more opportunities increases the chance that there is one opportunity that is considered to be desirable by the entrepreneur. Hence, it is likely to increase the opportunity-based entrepreneurial intentions.

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In conclusion, it expected that institutional quality positively influences opportunity entrepreneurial intentions and negatively influences necessity-intentions. Hence, the following hypotheses are formulated:

H2a: Institutional quality has a positive direct effect on opportunity-motivated entrepreneurial

intentions.

H2b: Institutional quality has a negative direct effect on necessity-motivated entrepreneurial

intentions.

When combining all previously formulated hypotheses we can expect entrepreneurial intentions to mediate between institutional quality and entrepreneurship. Hence, two additional hypotheses have been formulated.

H2c: Opportunity-motivated entrepreneurial intentions mediates between institutional quality

and entrepreneurship

H2d: Necessity-motivated entrepreneurial intentions mediates between institutional quality and

entrepreneurship

Institutional quality and realizing entrepreneurial intentions

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advantage. Furthermore, training in business skills may help entrepreneurs to successfully run a new business.

Moreover, institutions significantly impact business growth, as they can provide both opportunities and difficulties (Baumol & Strom, 2007). Low quality institutions are characterized by unpredictable governmental actions and with a lack of mechanisms that enforce contracts (Khanna & Palepu, 1997). When there are no mechanisms in place that sufficiently enforce contracts and government actions are rather unpredictable, it is highly risky to own a business. Thus, low quality institutions limit the chance of survival of new businesses. Institutions that are well-developed and are associated with low levels of corruption, high investment and business freedom show higher levels of entrepreneurial action (Nikolaev, Boudreaux, & Palich, 2018). Institutional quality has found to explain differences in levels of entrepreneurship between Japan, the USA, France, and India. Where India and France show lower levels of entrepreneurship as compared to the United States and Japan, as their institutions do not sufficiently encourage entrepreneurial activity (Paul, Hermel, & Srivatava, 2017). Hence, countries with well-developed institutions are expected to have higher levels of education and are generally a safer place to be for entrepreneurs, due to better mechanisms that enforce contracts. Thus, it is likely that institutional quality will contribute to realizing entrepreneurial intentions to actual entrepreneurship.

Nevertheless, there is reason to believe that the intensity of this predicted moderation effect differs for opportunity and necessity-motivated entrepreneurs. Educational institutions can teach students to identify a profitable and feasible business concept. In that way, educational institutional quality can foster the identification of entrepreneurial opportunities (Saks & Gaglio, 2002). By following these educational programs, individuals can improve both the innovativeness of their ideas and increase the number of ideas that they generate (DeTienne & Chandler, 2004). Hence, opportunity-motivated entrepreneurs may select better or more feasible start-up areas. Thus, if institutional quality is high, opportunity-entrepreneurs are likely to follow opportunities that are of higher quality.

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However, on the other hand it has been found that education does not influence whether or not an individual will be a necessity or opportunity entrepreneur, and that they enjoy the same level of education (Block & Wagner, 2010). Nevertheless, even though both types of entrepreneurs may have enjoyed similar education, education could potentially yield more value to opportunity-entrepreneurs. They freely choose to engage in entrepreneurship. Thus, they are more likely to be able to exploit their knowledge gained during their education as they have the possibility to match their knowledge with the right opportunity. Whereas, necessity entrepreneurs might be forced in a sub-optimal or non-optimal entrepreneurial situation as they are forced into entrepreneurship, even though having experienced similar education. Hence, as institutional quality increases, opportunity-based entrepreneurs are expected to have a bigger chance of success as compared to their necessity-based colleagues.

Therefore, it is expected that countries with well-developed institutions are expected to be better in realizing entrepreneurial intentions to actual entrepreneurship. However, necessity-motivated intentions are still expected to translate to entrepreneurship, but at a lower rate. This is summarized in the following hypotheses:

H3a: Institutional quality has a strong, positive moderation effect on the relation between

opportunity-motivated entrepreneurial intentions and actual entrepreneurship.

H3b: Institutional quality has a moderate, positive moderation effect on the relation between

necessity-motivated entrepreneurial intentions and actual entrepreneurship.

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Figure 1: Conceptual model of institutional quality affecting entrepreneurial intentions and the translation of intentions to entrepreneurship.

Figure 2: Simplified version of conceptual model

Methodology

Data and Variable Description

The analysis is based on a dataset that combines multiple sources. First of all, the Global Entrepreneurship Monitor (GEM) has been utilized. The data is survey based. This is one of few datasets about entrepreneurial activity that allows for cross-national entrepreneurship research (Schmutzler, Andonova, & Diaz-Serrano, 2019). Each country included in the GEM database has at least 2000 participants that completed the survey (Global Entrepreneurship Monitor, 2019). The dataset is complemented with data obtained from the Heritage Foundation Index of Economic Freedom. This index is computed from 10 distinct components (Miller, Holmes, & Feulner, 2013), three of which are utilized in this research. Finally, data concerning the control variables has been obtained from The World Bank. All data is obtained for the year 2013, except for the proxy for entrepreneurship. This variable was obtained from the year 2015 to include a time gap. The total number of countries with values for all variables is 41.

Dependent variable

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Business Ownership has been obtained from the GEM to serve as a proxy for entrepreneurship. The variable is a percentage of the working population (individuals of an age between 18 and 64) who are a manager or owner of a business for over three and a half years. The company must have paid wages, salaries, or other sorts of payments to the owner for these three and a half years. Looking at businesses that exist for at least three and a half years allows us to better identify how well entrepreneurial intentions translate into actual entrepreneurship, as it includes the survival of the new venture for at least three and a half years. The most recent data published by the GEM with respect to Established Business Ownership is utilized for this research, that is, the year 2015. This variable covers 58 countries.

With respect to the variables concerning entrepreneurial intentions (opportunity and necessity based), data from the Global Entrepreneurship Monitor has been adopted. These variables serve mainly as independent variables in Hypotheses 1a, 1b, 3a, and 3b, but can be seen as dependent variables in Hypotheses 2a and 2b, and as mediation variables in Hypotheses 2c and 2d. The variables are measured as either opportunity motivated or necessity motivated total early-stage entrepreneurial activity. These variables are a percentage of the working population (individuals of an age between 18 and 64) who are either involved in setting up a business or are a manager or owner of a recently established firm. A recently established firm here implies a firm that exists for less than three and a half years. These variables are taken from the year 2013 and cover both 70 countries. This implies a two-year time gap with the dependent variable Entrepreneurship. Information on how these variables are constructed can be found in appendix

4.

Independent variables

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absence of tariffs and trade barriers that directly affect exports. The data from these components has been utilized for the year 2013.

Control variables

Three variables are being controlled for, as they are found to have an influence on levels of entrepreneurship. First of all, wealth growth has been found to influence levels of entrepreneurship (Fuentelsaz, Gonzalez, Maicas, & Montero, 2015). Hence it is being controlled for. The data for this variable is obtained from The World Bank. It is measured as a percentage of GDP growth, based on the local currency. This implies that in case of GDP decline, the percentage can be negative. It is market price based and calculated as the sum of gross value added by all local producers in the economy with product taxes added. Moreover, subsidies that are not included in the product value are subtracted (The World Bank, 2013). The GDP growth data from the year 2013 has been utilized.

Moreover, population growth is being controlled for, as it has found to have a strong and significant influence on the most important measures of start-up activity. It provides opportunities from new economic activity, and the need of the growing population to engage in new economic activity to survive (Hunt & Levie, 2013). The data for population growth is obtained from The World Bank as an annual percentage derived from the total population. It is calculated as a percentage for the year t as the exponential growth rate of the population from midyear t-1 to t. Population here, includes all residents of a country, regardless of citizenship or legal status (The World Bank, 2013).

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Data analysis

Table 1 displays the descriptive statistics of the variables utilized in the analysis. From this table, we can observe that opportunity intentions has a higher mean as compared to necessity intentions. The mean of entrepreneurship is in-between the two, but is closer to the mean of opportunity intentions. The same holds for the variability. We observe the highest variability for opportunity intentions and the lowest for necessity intentions, with entrepreneurship in-between. This implies that the percentage of people who are either involved in setting up a business or are a manager or owner of a recently established firm with an opportunity motive, on average, is higher than a necessity motive. These values for opportunity intentions and necessity intentions of 9,57 and 3,54 respectively show that on average for every individual that is setting up a business out of necessity, more than 2,5 people are setting up a business with an aim to capitalize off of opportunities.

Moreover, Table 2 displays the correlation matrix of the variables used in the analysis. Since, the main independent variables, opportunity and necessity intentions show a high significant correlation, this could signal a potential issue of multicollinearity. Hence, those variables will not be included in the same regression simultaneously. Instead, separate regressions will be executed.

Table 1 Descriptive statistics.

Variable Mean Std. Deviation Minimum Maximum N

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Table 2 Correlation matrix. Variable 1 2 3 4 5 6 7 8 9 10 Entrepreneurship 1 Opportunity intentions 0,41* 1 Necessity Intentions 0,35* 0,73* 1 Institutional Quality -0,28* -0,32* -0,48* 1 Trade Freedom -0,35* -0,40* -0,39* 0,74* 1 Freedom from Corruption -0,25 -0,31* -0,50* 0,86* 0,45* 1 Financial Freedom -0,18 -0,17 -0,30* 0,90* 0,60* 0,66* 1 GDP Growth 0,08 0,44* 0,48* -0,12 -0,07 -0,16* -0,04 1 Population Growth 0,36* 0,51* 0,46* -0,28* -0,25* -0,25* -0,16* 0,29* 1 Unemployment Rate -0,23 -0,33* -0,33 0,07 0,12 0,01 0,10 -0,43* -0,43* 1 * p <0,05

Results

In order to test for the hypotheses several ordinary least squares (OLS) regressions have been performed, of which the outcomes are presented in this section. Model 2 in Table 3 demonstrates the results of a regression of opportunity intentions on entrepreneurship, controlled for GDP growth, population growth, and unemployment. The model is highly statistically significant and shows an adjusted R2 of 0,243. This implies that 24,3% of the variance in entrepreneurship can be explained by the model. Moreover, the results show a highly significant standardized beta for the variable of interest, opportunity intentions. The positive value of 0,621 for opportunity intentions suggests that levels of entrepreneurship are higher when opportunity-based entrepreneurial intentions are present.

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Table 3 – OLS regression results (dependent variable: Entrepreneurship) (1) (2) (3) Opportunity intentions 0,621*** (0,171) Necessity intentions 0,569*** (0,389) Controls GDP growth -0,144 (0,356) -0,403** (0,369) -0,479** (0,412) Population growth -0,033 (980) 0,037 (1,011) 0,007 (1,046) Unemployment Rate -0,321 (0,126) -0,177 (0,122) -0,395** (0,127) F-Statistic 1,120 4,289*** 3,403** N 48 42 42 Adjusted R2 _0,008 _0,243 _0,190 *** p < 0,01, ** p < 0,05, * p <0,10; two-tailed significance

This implies that, both opportunity and necessity intentions are strongly related to levels of entrepreneurship.

However, as hypothesized, opportunity intentions display a higher standardized beta coefficient as compared to necessity intentions. In order to test whether the regression coefficients significantly differ a Z-test is performed. The equation to test for equality of regression coefficients formulated by (Clogg, Petkova, & Haritou, 1995) and explained by (Paternoster, Brame, Mazerolle, & Piquero, 1998) is utilized.

𝑍 = 𝛽1−𝛽2

√(𝑆𝐸𝛽1)2+ (𝑆𝐸𝛽2)2

𝑍 = 0,052

√(0,171)2_{+ (0,389)}2

𝑍 = 0,12

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Table 4, model 2 displays the results of an OLS regression of institutional quality on opportunity intentions, controlled for GDP growth, population growth, and unemployment. The model is highly significant and explains 32,7% of the variance in opportunity intentions. Where the control variable GDP growth shows significance, the variable of interest (institutional quality) has found to be insignificant. Opposing what is hypothesized, this implies that when institutional quality increases, this does not significantly affect levels of opportunity intentions. Therefore, hypothesis 2a is rejected.

Moreover, from Table 4, Model 4, the outcome of the regression of institutional quality on necessity intentions becomes clear. The model explains a high percentage of the variation in necessity intentions, as it significantly shows an adjusted R2 of 0,457. In this model, institutional quality shows a negative significant standardized beta coefficient of -0,360. This suggests that the probability of forming necessity intentions of entrepreneurship is smaller in countries with higher institutional quality. Hence, hypothesis 2b is accepted.

Table 4 – OLS regression results

Dependent variable: Opportunity intentions

Dependent variable: Necessity intentions

(1) (2) (3) (4) Institutional Quality -0,175 (0,050) -0,360*** (0,022) Controls GDP growth 0,418*** (0,301) 0,356** (0,314) 0,566*** (0,144) 0,439*** (0,139) Population growth 0,223 (0,782) 0,201 (0,802) 0,236* (0,375) 0,176 (0,356) Unemployment Rate -0,034 (0,110) -0,066 (0,111) 0,336*** (0,053) 0,265** (0,049) F-Statistic 9,906*** 8,061*** 11,794*** 13,227*** N 60 59 60 59 Adjusted R2 _0,312 _0,327 _0,354 _0,457 *** p < 0,01, ** p < 0,05, * p <0,10; two-tailed significance Mediation testing

In order to test for the following mediation, several analyses have been performed. In tables 5 and 6 the outcomes for Sobel’s, Aroian’s, and Goodman’s tests can be found. Sobel’s test assumes the product of 𝑠_𝑎2_{and 𝑠}

𝑏2 to be negligible. Hence, Aroian’s and Goodman’s

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This implies that it may unfortunately yield a negative variance estimate sometimes. This can be observed in the formulas below.

Sobel’s test equation: 𝑍𝑣𝑎𝑙𝑢𝑒 = a∗b

√𝑏2_+𝑠𝑎2_+𝑎2_∗𝑠 𝑏2)

Aroian’s adjustment: 𝑍𝑣𝑎𝑙𝑢𝑒 = a∗b

√𝑏2_+𝑠

𝑎2+𝑎2∗𝑠𝑏2+𝑠𝑎2∗𝑠𝑏2)

Goodman’s adjustment: 𝑍𝑣𝑎𝑙𝑢𝑒 = a∗b

√𝑏2_+𝑠𝑎2_+𝑎2_∗𝑠

𝑏2−𝑠𝑎2∗𝑠𝑏2)

Table 5 – Mediation outcomes for Institutional Quality → Opportunity Intentions →

Entrepreneurship.

Test Uncontrolled Controlled

Test statistic Std. Error P-value Test statistic Std. Error P-value

Sobel -1,793 0,025 0,073 -1,376 0,031 0,169

Aroian -1,728 0,026 0,084 -1,330 0,032 0,183

Goodman -1,865 0,024 0,062 -1,427 0,030 0,153

Table 6 – Mediation outcomes for Institutional Quality → Necessity Intentions →

Entrepreneurship.

Test Uncontrolled Controlled

Test statistic Std. Error P-value Test statistic Std. Error P-value

Sobel -1,299 0,044 0,194 -1,913 0,041 0,056

Aroian -1,270 0,045 0,204 -1,860 0,042 0,063

Goodman -1,329 0,043 0,184 -1,971 0,040 0,049

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before. With respect to necessity intentions, we observe that the values are really close to the 0,05 cutoff points when controlled for the three previously introduced variables. Moreover, the Goodman test even shows significance. However, it has been demonstrated that Sobel’s test for mediation may not be the optimal test in smaller samples (Preacher & Hayes, 2008). In this study there are 41 countries with values for all variables, which can be considered a small sample. For that reason, one additional test for mediation will be performed to see whether mediation is going on. When the direct effect of the IV on the DV is greater than 0, the test by Baron and Kenny performed better or equal to Sobel’s test. It required a smaller sample size to get an equal statistical power (Fritz & MacKinnon, 2007). Hence, Baron and Kenny’s (1986) steps have been performed to test for mediation. Step one entails a regression that shows the independent variable has a significant effect on the dependent variable. Additionally, the independent variable should significantly influence the mediator. Finally, the dependent variable should be regressed on both the independent and the mediator. This should show that the mediator predicts the dependent variable and that the independent variable that was significant in step one is now reduced in significance.

Table 7 – Baron and Kenny’s test for mediation. Institutional quality → Opportunity

Intentions → Entrepreneurship. Without control variables

Standardized beta coefficient (coefficent standard error) Condition met

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Table 8 – Baron and Kenny’s test for mediation. Institutional quality → Necessity

Intentions → Entrepreneurship. Without control variables

Step 1 -0,284** (0,054) TRUE Step 2 -0,475*** (0,024) TRUE Step 3a 0,239 (0,390) FALSE

Table 9 – Baron and Kenny’s test for mediation. Institutional quality → Opportunity

Intentions → Entrepreneurship. With control variables

Step 1 -0,330** (0,056) TRUE Step 2 -0,175 (0,050) FALSE

Table 10 – Baron and Kenny’s test for mediation. Institutional quality → Necessity

Intentions → Entrepreneurship. With control variables

Step 1 -0,330** (0,056) TRUE Step 2 -0,360*** (0,022) TRUE Step 3a 0,469** (0,447) TRUE Step 3b -0,204 (0,068) TRUE

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control variables are utilized. However, when controlled for GDP growth, Population Growth and Unemployment rate this changes. We then observe that necessity intentions mediates between institutional quality and entrepreneurship as in line with previous results. Since, H1b and H2b have been accepted. The results show that we can cautiously accept that necessity intentions fully mediates between institutional quality and entrepreneurship. Thus, hypothesis 2d is accepted.

Moderation testing

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Table 11 – OLS regression results (dependent variable: Entrepreneurship) (1) (2) (3) (4) (5) Opportunity intentions 0,621*** (0,171) 0,566*** (0,165) 1,301 (0,832) 1,385*** (0,367) Institutional quality -0,311** (0,055) -0,038 (0,123) Opportunity intentions * Institutional quality -0,693 (0,014) -0,770** (0,006) Controls GDP growth -0,144 (0,356) -0,403** (0,369) -0,533*** (0,365) 0,522*** (0,367) -0,518*** (0,354) Population growth -0,033 (980) 0,037 (1,011) 0,071 (1,000) -0,086 (1,008) -0,087 (0,993) Unemployment Rate -0,321 (0,126) -0,177 (0,122) -0,294* (0,119) -0,280 (0,120) -0,276 (0,116) F-Statistic 1,120 4,289*** 4,726*** 4,057*** 5,007*** N 48 42 41 41 41 Adjusted R2 0,008 0,243 0,318 0,314 0,334 *** p < 0,01, ** p < 0,05, * p <0,10; two-tailed significance

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Table 12 – OLS regression results (dependent variable: Entrepreneurship) (1) (2) (3) (4) (5) Necessity intentions 0,569*** (0,389) 0,469** (0,447) 0,934 (1,752) 1,164** (1,124) Institutional quality -0,204 (0,068) -0,098 (0,095) Necessity intentions * Institutional quality -0,436 (0,034) -0,624 (0,025) Controls GDP growth -0,144 (0,356) -0,479** (0,412) -0,519** (0,408) -0,453* (0,459) -0,418* (0,419) Population growth -0,033 (980) 0,007 (1,046) -0,083 (1,081) -0,119 (1,156) -0,130 (1,125) Unemployment Rate -0,321 (0,126) -0,395** (0,127) -0,450** (0,127) 0,411** (0,136) -0,386** (0,126 F-Statistic 1,120 3,403** 3,043** 2,550** 3,107** N 48 42 41 41 41 Adjusted R2 0,008 0,190 0,203 0,189 0,208 *** p < 0,01, ** p < 0,05, * p <0,10; two-tailed significance Robustness check

In order to somewhat test for the validity of the outcomes of the regression analysis, several robustness tests have been performed. As in line with previous studies (Lu & White, 2014), I examined how the variables of interest behave when regressors were removed. Several additional tests have been performed by rerunning the tests whilst gradually removing control variables.

In appendix 1, tables 13 through 16 present the results of rerunning all models without controlling for the unemployment rate. Seven out of eight models remain significant at the 5% level, and all conclusions remain the same. Model seven turns slightly insignificant at the 5% level, but remains significant at the 10% level.

In appendix 2, tables 17 through 20 outline the results of dropping one additional variable. That is, the analysis without controlling for both the unemployment rate and for GDP growth. Similarly, all conclusions remain the same. However, models 2 and 7 turn slightly insignificant at the 5% level, but remain significant at the 10% level.

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variables are controlled for. However, the model only shows to explain a rather small percentage of the variation opportunity intentions, as the adjusted R2 is only 0,089. In conclusion, the results show to be relatively robust when regressors are removed.

Discussion and Conclusion

The aim of this study was to examine the different effects, both direct and moderating, of institutional quality on the realization of entrepreneurial intentions to actual entrepreneurship. In doing so I react to the call of contextualizing entrepreneurship and find different effects for different types of entrepreneurship. At the heart, using Ajzen’s theory of planned behavior, it was predicted that both opportunity and necessity types of entrepreneurial intentions would translate into actual entrepreneurship. However, since necessity-motivated entrepreneurs would face additional barriers in their journey to entrepreneurship, it was expected that opportunity-entrepreneurs would be slightly better in realizing their intentions. This was hypothesized in H1a through H1c. The results supported H1a and H1b, but not H1c. Both types of intentions seem to translate into entrepreneurship, but the coefficients did not significantly differ.

Moreover, it was predicted that institutional quality would positively influence opportunity intentions, and simultaneously have a negative effect on necessity intentions. Institutional quality was expected to lead to a better identification of opportunities and consequently increase opportunity-motivated entrepreneurial intentions. Moreover, through proper protection of property rights in countries with high quality institutions, opportunity-motivated entrepreneurial intentions were hypothesized to increase accordingly. Whereas, institutional quality was expected to lower levels of necessity intentions. However, the analysis only shows support for the latter.

Finally, institutional quality was expected to facilitate the realization of both types of entrepreneurial intentions. Nevertheless, no significant moderation effect has been found with respect to necessity intentions. However, a negative moderation effect of institutional quality has been found for the opportunity intentions to entrepreneurship relation.

The negative moderation effect is in interesting finding and could be further explored in future research.

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entrepreneurship. Entrepreneurs that engage in entrepreneurship because there are no better alternatives available are significantly less satisfied with their business (Block & Koellinger, 2009). Thus, on one hand institutional quality prevents dissatisfaction of necessity entrepreneurs, by lowering necessity intentions. While simultaneously hindering the realization of dreams of opportunity entrepreneurs. One could say institutional quality may both kill dreams and prevent nightmares for opportunity and necessity entrepreneurs respectively.

Theoretical and managerial implications

This study has examined the different effects of institutional quality entrepreneurial intentions and on the success rate of entrepreneurial intentions. Which has been neglected by previous research. Previous research has predominantly focused at the effect of the institutional environment on entrepreneurship itself, failing to explain underlying forces. At the heart, this study adopts the theory of planned behavior. As in line with this intention model, I confirm that both types of entrepreneurial intentions show a positive relation with entrepreneurship. Moreover, a key finding is that institutional quality affects different domains with respect to opportunity and necessity entrepreneurship. This signals that the influence of institutional quality on entrepreneurship (and consequently economic growth) is more comprehensive than previously thought. Thus, this study contributes to the literature by exposing this difference in domains in which institutional quality has an effect.

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The results of this research and implications are especially important for governmental policy makers. Institutional quality shows to negatively influence the realization of entrepreneurial intentions. This could hint that some policies form roadblocks for nascent entrepreneurs. It reminds policy makers to critically assess the possible negative external effects of implemented policies.

Limitations and Further research

The key findings of this research contradict some earlier research. Therefore, it would be interesting to further explore the possible negative effect of institutional quality on entrepreneurial intentions and subsequently entrepreneurship. A limitation of this research is the fact that it bases its analysis on cross-sectional data. Using panel data has the possibility to yield different results. A replicative study with panel data would be valuable to explore in the future. Moreover, to capture institutional quality a proxy averaging capturing freedom from corruption, financial freedom, and trade freedom as per Shinkle & Kriauciunas (2010) has been utlized. Replicating this study with a different measure for institutional quality to examine how that would influence the results can be interesting for further research.

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Appendices

Appendix 1: Tables 13 through 16 show the results of all models without controlling for

Unemployment rate.

Table 13 – OLS regression results (dependent variable: Entrepreneurship)

(1) (2) (3) Opportunity intentions 0,623*** (0,160) Necessity intentions 0,522*** (0,379) Controls GDP growth -0,075 (0,292) -0,417** (0,311) -0,364* (0,326) Population growth 0,393*** (0,653) 0,108 (0,967) 0,133 (1,010) F-Statistic 4,294** 5,184*** 3,483** N 57 47 47 Adjusted R2 0,105 0,214 0,139 *** p < 0,01, ** p < 0,05, * p <0,10; two-tailed significance

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Table 15 – OLS regression results (dependent variable: Entrepreneurship) (1) (2) (3) (4) (5) Opportunity intentions 0,623*** (0,160) 0,591*** (0,155) 1,531* (0,739) 1,356*** (0,330) Institutional quality -0,265* (0,051) 0,078 (0,114) Opportunity intentions * Institutional quality -0,919 (0,012) -0,751** (0,005) Controls GDP growth -0,075 (0,292) -0,417** (0,311) -0,462*** (0,300) -0,432** (0,301) -0,440** (0,293) Population growth 0,393*** (0,653) 0,108 (0,967) 0,018 (0,973) -0,009 (0,977) -0,005 (0,961) F-Statistic 4,294** 5,184*** 5,116*** 4,463*** 5,692*** N 57 47 46 46 46 Adjusted R2 _0,105 _0,214 _0,268 _0,278 _0,294 *** p < 0,01, ** p < 0,05, * p <0,10; two-tailed significance

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Appendix 2: tables 17 through 20 show the results of all models without controlling for GDP

growth and Unemployment rate.

(1) (2) (3) Opportunity intentions 0,421*** (0,143) Necessity intentions 0,348** (0,333) Controls Population growth 0,364*** (0,599) -0,028 (0,939) 0,008 (0,954) F-Statistic 8,394*** 4,497** 3,075* N 57 47 47 Adjusted R2 _0,117 _0,132 _0,083 *** p < 0,01, ** p < 0,05, * p <0,10; two-tailed significance

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Table 19 – OLS regression results (dependent variable: Entrepreneurship) (1) (2) (3) (4) (5) Opportunity intentions 0,421*** (0,143) 0,377** (0,144) 1,600* (0,785) 1,103*** (0,339) Institutional quality -0,220 (0,054) 0,217 (0,119) Opportunity intentions * Institutional quality -1,177 (0,013) 0,709** (0,006) Controls Population growth 0,364*** (0,599) -0,028 (0,939) -0,120 (0,976) -0,143 (0,966) -0,140 (0,959) F-Statistic 8,394*** 4,497** 3,829** 3,544** 4,632*** N 57 47 46 46 46 Adjusted R2 0,117 0,132 0,159 0,184 0,195 *** p < 0,01, ** p < 0,05, * p <0,10; two-tailed significance

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Appendix 3: Tables 21 through 24 show the results of all models without all control variables.

(1) (2) Opportunity intentions 0,405*** (0,132) Necessity intentions 0,347** (0,311) F-Statistic 9,016*** 6,310** N 48 48 Adjusted R2 _0,146 _0,102 *** p < 0,01, ** p < 0,05, * p <0,10; two-tailed significance

Dependent variable: Opportunity intentions Dependent variable: Necessity intentions

(1) (2) Institutional quality -0,320*** (0,051) -0,475*** (0,024) F-Statistic 7,620*** 19,549*** N 69 69 Adjusted R2 0,089 0,214 *** p < 0,01, ** p < 0,05, * p <0,10; two-tailed significance

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Table 24 – OLS regression results (dependent variable: Entrepreneurship) (1) (2) (3) (4) Necessity Intentions 0,347** (0,311) 0,239 (0,390) 1,217* (1,414) 1,046** (0,903) Institutional Quality -0,165 (0,066) 0,082 (0,087) Necessity Intentions * Institutional Quality -0,880 (0,025) -0,750* (0,018) F-Statistic 6,310** 3,345** 3,150** 4,758** N 48 47 47 47 Adjusted R2 _0,102 _0,093 _0,123 _0,140 *** p < 0,01, ** p < 0,05, * p <0,10; two-tailed significance Dependent variable: Entrepreneurship

Appendix 4: Table 25 shows how the variables obtained from GEM with respect to

entrepreneurial intentions are composed. Since they refer back to other variables, descriptions of these variables have been included in Table 26.

*Note ‘yy’ in the variable name is replaced by a two digit year indicator.

Table 25 – Composition of main variables obtained from GEM

Variable name

Code Variable label Note

TEAyyOPP INVOLVED IN OPPORTUNITY

EARLY-STAGE ENTREPRENEURIAL ACTIVITY TEAyyOPP=1 IF TEAyy=1 AND SUREASON/OMREASON=1, 3,OR 4 0 NO 1 YES

TeayyNEC INVOLVED IN NECESSITY

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Table 26 – Composition of GEM supporting variables

Variable name Code Variable label Note

TEAyy INVOLVED IN TOTAL

EARLY-STAGE ENTREPRENEURIAL ACTIVITY

THIS VARIABLE

IDENTIFIES TEA TEA =1 IF SUBOANW=1 OR BABYBUSO=1

0 NO

1 YES

SUREASON Q1K1 (Other reasons involved in

this start-up)

1 TAKE ADVANTAGE OF

BUSINESS OPPORTUNITY 2 NO BETTER CHOICE FOR

WORK

3 COMBINATION OF BOTH OF THE ABOVE

4 HAVE A JOB BUT SEEK BETTER OPPORTUNITY 5 OTHER - ASK DETAILS

PLACE IN OPEN ENDED FILE -1 DON’T KNOW

-2 REFUSED

OMREASON Q2K1 (Other reasons for

involvement in this firm)

1 TAKE ADVANTAGE OF

BUSINESS OPPORTUNITY 2 NO BETTER CHOICE FOR

WORK

3 COMBINATION OF BOTH OF THE ABOVE

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5 OTHER - ASK DETAILS PLACE IN OPEN ENDED FILE -1 DON’T KNOW

Master’s Thesis Managing Multinationals

Abstract

Contents

Introduction

Entrepreneurial environment

Intentions and entrepreneurship

Entrepreneurial intentions

Methodology

Results

Discussion and Conclusion

Bibliography

Appendices