University of Groningen Faculty of Economics and Business
Master Thesis, MSc BA Small Business and Entrepreneurship
Fokelien Oosterhuis S2763958 Supervisor: dr. M. Wyrwich Co-assessor: S. Murtinu Date: 20th of January 2020 Word count: 10 2011
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Abstract
Research has recently been investigating the regional distribution of an entrepreneurship-prone personality profile. This kind of research has not been conducted for the Netherlands yet. In the Netherlands, policymakers have a particular interest in krimpregio’s because of the problems related to these specific areas in the Netherlands. Therefore, this paper studied regional differences in entrepreneurship-prone personality profiles in the Netherlands based on data from the Gosling-Potter internet project. Results show that regional differences in the Netherlands exist, with krimpregio’s having an entrepreneurship-prone personality profile that is further away from the ‘perfect’ entrepreneur. Additionally, this paper tried to establish whether a migration flow of entrepreneurial people out of the krimpregio’s towards the rest of the Netherlands existed. Indeed, the profile of the people moving out of the krimpregio’s is closer to the ‘perfect’ entrepreneur. However, when focussing on a younger subsample this conclusion does not hold.
3 Table of content
1. Introduction ... 4
2. Literature review ... 6
2.1 Personality trait theory ... 6
2.2 The Big Five Personality traits ... 6
2.2.1 Extraversion ... 6
2.2.2 Openness to Experience ... 7
2.2.3 Conscientiousness ... 7
2.2.4 Agreaableness ... 8
2.2.5 Neurotiscism ... 8
2.3 Krimpregio’s and related issues ... 9
2.4 Hypotheses ... 11
3. Data and methods ... 14
3.1 Data Collection and sample ... 14
3.2 Variables ... 14 3.3 Analysis plan ... 15 4. Results ... 17 4.1 Main analysis ... 17 4.2 Robustness check ... 21 5. Conclusion ... 25
5.1 Conclusions and contributions ... 25
5.2 Limitations and direction for future research ... 26
5.3 Policy implications ... 27
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1. Introduction
Research has given a lot of attention to entrepreneurship because it is thought to lead to economic development (Koellinger & Thurik, 2012; Lévesque & Minniti, 2011; Vivarelli, 2013), employment creation (Van Praag & Versloot, 2007; Vivarelli, 2013), productivity growth (Van Praag & Versloot, 2007), and high-quality innovation (Van Praag & Versloot, 2007). Additionally, entrepreneurship is believed to play a crucial role in regional development (Caliendo, Fossen & Kritikos, 2014; Kibler, Kautonen & Fink, 2014). Factors that could influence the decision to become an entrepreneur such as age (Kautonen, Down & Minniti, 2014; Lévesque & Minniti, 2006; Storey & Green, 2010), gender (Kibler et al., 2014; Koellinger, Minniti & Schade, 2013; Storey & Green, 2010), education (Storey & Green, 2010), previous job experience (Lévesque & Minniti, 2006; Storey & Green, 2010; Vivarelli, 2013), family background (Storey & Green, 2010; Vivarelli, 2013) and psychological characteristics such as locus of control, risk attitudes, and optimism (Caliendo et al., 2014; Lévesque & Minniti, 2006; Storey & Green, 2010) have been studied.
Recently, studies have investigated personality characteristics in constructs like the Big Five personality traits (Zhao & Seibert, 2006). An entrepreneurship-prone personality profile regarding the Big Five personality traits has been constructed (Fritsch, Obschonka & Wyrwich, 2019; Obschonka, Schmitt-Rodermund, Silbereisen, Gosling & Potter, 2013). This entrepreneurship-prone personality profile has been positively linked to actual entrepreneurial activity (Fritsch et al., 2019; Obschonka et al., 2013). Literature has indicated that regional differences exist in entrepreneurship-prone personality profiles (Fritsch et al., 2019; Obschonka et al., 2013; Rentfrow, Gossling & Potter, 2008) and that these regional differences have an effect on entrepreneurial activity like the formation of new businesses (Fritsch et al., 2019; Obschonka et al., 2013). Studies into the regional distribution of the entrepreneurship-prone personality profile and its link to entrepreneurial activity in the regions have been conducted for the USA (Obschonka et al., 2013), Germany (Fritsch et al., 2019; Obschonka et al., 2013) and the UK (Obschonka et al., 2013). No research has been done into the regional distribution in the Netherlands.
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problems and a decline of facilities (Hospers, 2012; Kuhlman et al., 2012; Notten, 2013; Verwest & van Dam, 2010; Verweij & van der Lucht, 2014). Leading to attention from the media and policymakers, resulting in public policy efforts like the actieplan bevolkingsdaling. The combination of research into the regional distribution of an entrepreneurship-prone personality profile lacking for the Netherlands and the attention for and problems associated with krimpregio’s leads to the main research question of this paper, which is defined as follows:
What is the difference in entrepreneurship-prone personality profile between regions in the Netherlands identified as krimpregio and other regions within the Netherlands and is there a migration flow of entrepreneurial people from these regions to regions with a higher entrepreneurship-prone personality profile?
This study contributes to the literature in several ways. Firstly, by investigating the regional distribution in the Netherlands this research will add to the existing research given that this topic has not been researched in the Netherlands yet. Secondly, this kind of research has never been done in a country as small as the Netherlands. In terms of inhabitants the countries where this research has been conducted, USA (329 million), Germany (83 million) and UK (67 million) are relatively large compared to the Netherlands (17 million) (worldometers, 2019). Therefore, if regional differences still exist in the Netherlands it will provide strong evidence for the existence of regional differences in the entrepreneurship-prone personality profile. Thirdly, this study also contributes to the recent literature by investigating whether there is a migration flow of entrepreneurial people from less entrepreneurship-prone regions to more entrepreneurship prone regions.
Using data from the Gosling-Potter internet project, regional differences in entrepreneurship-prone personality profile between the krimpregio’s and the other parts of the Netherlands are indeed found, with the krimpregio’s having higher scores. Additionally, some evidence is found confirming the migration flow of entrepreneurial people from krimpregio’s to other parts of the Netherlands.
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2. Literature review
The following literature review is divided into subsections about the personality trait theory, the Big Five personality dimensions and krimpregio’s. Subsequently, hypotheses about the regional distribution of an entrepreneurship-prone personality profile and migration are developed and discussed.
2.1 Personality trait theory
This paper builds on the personality trait theory. According to Guy, Kim, Lin, and Manocha (2011), personality trait theory suggests that a small number of underlying traits are the basis of variations in behaviour. Others (Hofstede & McCrae, 2004; McCrae, 2000) also suggest that the trait approach to psychology can be used to identify individual differences in ways of thinking and acting. Trait theories identify the traits that one could use to describe these variations in personality. A trait can be described as a way of thinking, behaving or emotion, with a habitual pattern (Guy et al., 2011). The personality of an individual can be described on the basis of their score on the different personality traits. These scores signal how weakly or strongly the individual shows this particular trait. (Guy et al., 2011).
Literature has suggested five primary traits (Guy et al., 2011; Hofstede & McCrae, 2004; McCrae, 2000). These five primary traits are Extraversion, Openness to Experience, Conscientiousness, Agreeableness, and Neuroticism. Following earlier research (Fritsch et al., 2019; Obschonka et al., 2013), in this paper, an entrepreneurship-prone personality profile will be constructed on the basis of the Big Five personality traits. Therefore, the following paragraphs will give a short explanation of each of the Big Five personality traits and their relation to entrepreneurship.
2.2 The Big Five Personality traits
The Big Five personality dimensions are Extraversion, Openness to Experience, Conscientiousness, Agreeableness and Neuroticism (Zhao & Seibert, 2006). Each of these five domains is constructed on the basis of more narrowly defined and specific traits (Zhao & Seibert, 2006).
2.2.1 Extraversion. Extraversion is the Big Five trait that describes the extent to which
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cheerful, liking people and large groups describes individuals scoring high on this dimension (Zhao & Seibert, 2006; Zhao et al., 2010). Whereas, people scoring low on extraversion are more reserved, quiet, independent and preferably spend more time alone (Zhao & Seibert, 2006).
It is believed that extraversion is positively related to entrepreneurial development and success (Caliendo et al., 2014). Firstly, since entrepreneurs have to take care of both internal and external relationships. Internally entrepreneurs have to interact with their partners and employees, have to build teams and assign roles (Caliendo et al., 2014; Zhao & Seibert, 2006). Externally, there are relationships with venture capitalists, customers, partners, as well as contracts that need to be negotiated (Caliendo et al., 2014; Zhao & Seibert, 2006). Additionally, in comparison with traditional jobs being an entrepreneur appears to be more stimulating and exciting (Zhao et al., 2010).
2.2.2 Openness to Experience. Openness to Experience is the dimension that reflects
whether individuals are intellectually curious, creative, able to seek new experiences, able to explore novel ideas and seek alternative values and aesthetic standards (Caliendo et al., 2014; Weisberg et al., 2011; Zhao & Seibert, 2006; Zhao et al., 2010). When scoring high on this dimension an individual can be characterized as curious, creative, innovative, imaginative, reflective and untraditional (Caliendo et al., 2014; Zhao & Seibert, 2006). Scoring low on Openness to Experience, an individual can be described as conventional, narrow in interest and unanalytical (Zhao & Seibert, 2006).
Innovation is one of the distinctive characteristics to describe entrepreneurs (Zhao & Seibert, 2006; Zhao et al., 2010). An innovative approach to products or processes, tackling new problems or exploring new ideas is most likely required from an entrepreneur when founding a new business (Caliendo et al., 2014; Zhao & Seibert, 2006). In addition to this, becoming self-employed is a non-traditional way of employment, which is more likely to seem attractive to people that are more open to new experiences (Zhao et al., 2010). Hence, scoring high on Openness to Experience will most likely be positively related to becoming an entrepreneur.
2.2.3 Conscientiousness. The third Big Five dimension, Conscientiousness, reflects an
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Zhao & Seibert, 2006).
Literature has indicated that people that have a high need for achievement or achievement motivation will be more likely to pursue self-employment instead of traditional forms of employment (Caliendo et al., 2014; Zhao & Seibert, 2006). First of all, because these individuals would prefer to be in situations in which they have control over outcomes and performance is due to their own effort (Zhao & Seibert, 2006; Zhao et al., 2010). Secondly, according to Caliendo et al. (2014) individuals with a high need for achievement are motivated to search for new or better solutions than currently provided in the environment, which results in the belief that they will become successful entrepreneurs. With regard to the dependability aspect (whether an individual is organized, deliberate and dutiful), some state that the aspects of dependability are negatively related to entrepreneurship (Caliendo et al., 2014), while others state that the self-directed environment in which entrepreneurs operate makes the dependability trait more important for entrepreneurs (Zhao & Seibert, 2006).
2.2.4 Agreeableness. Agreeableness is the dimension that evaluates an individual's
attitude and behaviour towards others (Lucas & Donnellan, 2009; Zhao & Seibert, 2006; Zhao et al., 2010). Trusting, forgiving, caring, cooperative, altruistic and gullible are words that can be used to describe somebody that scores high on Agreeableness (Caliendo et al., 2014; Zhao & Seibert, 2006; Zhao et al., 2010). At the low end of the dimension, an individual can be described by words like manipulative, self-centred, suspicious and ruthless (Caliendo et al., 2014; Zhao & Seibert, 2006; Zhao et al., 2010).
High scores on Agreeableness could positively influence becoming an entrepreneur, given that it may lead to being seen as trustworthy and help in building relationships with clients, suppliers and investors (Caliendo et al., 2014). On the other hand, high scores on Agreeableness might have a negative effect on a person’s willingness and ability to drive hard bargains and look out for their own interest (Caliendo et al., 2014; Zhao & Seibert, 2006). These negative consequences of high Agreeableness scores are even more important for entrepreneurs given the limited legal protection and limited financial resources (Zhao & Seibert, 2006).
2.2.5 Neuroticism. The last Big Five trait, Neuroticism, can be described as the degree
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et al., 2011; Zhao & Seibert, 2006; Zhao et al., 2010).
The entrepreneurial environment can be described as a relatively unstructured environment with uncertain outcomes (Caliendo et al., 2014; Zhao & Seibert, 2006). Additionally, entrepreneurs typically have a significant financial and personal stake in the enterprise (Caliendo et al., 2014; Zhao & Seibert, 2006). When starting up a business, entrepreneurs must manage to deal with these stress factors. Literature typically describes entrepreneurs as hardy, optimistic and steady when facing pressure, stress, and uncertainty. Entrepreneurs take on burdens and press ahead where other people might be discouraged because of obstacles or setbacks (Zhao et al., 2010). Therefore, it would be logical to assume that entrepreneurs would score low on Neuroticism.
Based on the given description of the Big Five personality traits and the discussed links with entrepreneurship it can be concluded that an entrepreneur is likely to have a high score on Extraversion, Openness to Experience and Conscientiousness and low scores on Agreeableness and Neuroticism. Previous literature has concluded the same, which can, for example, be seen from the fact that the used entrepreneurial reference profile consists of the highest possible scores on Extraversion, Openness to Experience and Conscientiousness and the lowest possible scores on Agreeableness and Neuroticism (Fritsch et al., 2019; Obschonka et al., 2013). Previous literature has found regional differences in individual Big Five personality traits (Rentfrow et al., 2008). Additionally, literature has indicated that a difference in entrepreneurship-prone personality profile, that is based on the Big Five personality traits, exists between regions in countries like the United States, Germany and the United Kingdom (Fritsch et al., 2019; Obschonka et al., 2013; Rentfrow et al., 2008). These regional differences in entrepreneurship-prone personality profiles have been linked to measures of entrepreneurial activity such as new venture start up, innovation, and self-employment rate (Fritsch et al., 2019; Obschonka et al., 2013). Based on previous literature indicating the regional difference in entrepreneurship-prone personality profile it is expected that a regional difference in entrepreneurship-prone personality profile will also be present in the Netherlands. Areas of interest in the Netherlands are the so-called krimpregio’s, therefore the next section will give a description of krimpregio’s and discusses the problems related to these areas.
2.3 Krimpregio’s and related issues
The Dutch government has identified 9 krimpregio’s in the Netherlands (Rijksoverheid, n.d).
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well as a decline in households. Most of the krimpregio’s are located in the edges of the Netherlands, primarily in the North and the South of the country, as can be seen in Figure 1.
Figure 1. krimpregio’s in the Netherlands.
The decline of population and households can be caused by a difference between birth- and mortality rates or can be caused by migration (Kuhlman et al., 2012; Verweij & van der Lucht, 2014). Literature has indicated that in the past, migration has been the biggest cause of the decline in population (Kuhlman et al., 2012). In addition to and as a result of the decline in population and the number of households, krimpregio’s suffer from a number of other problems.
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Secondly, the population decline can lead to a vacancy of houses and shops (Hospers, 2012; Kuhlman et al., 2014; Verwest & van Dam, 2010). This vacancy can possibly lower the price of houses. When the vacancy is long-lasting it could lead to deterioration of the entire neighbourhood (Hospers, 2012).
Another problem facing the krimpregio’s is the fact that the younger people leave the
krimpregio’s whereas the older inhabitants stay within the region, or as soon as they retire come
back to the region. This results in a population that becomes older on average (Hospers, 2012; Notten, 2013; Kuhlman et al., 2014). These demographic changes subsequently lead to a reduction in the number of inhabitants within the working age. This can lead to a shortage of employees, which results in difficulties for employers (Verwest & van Dam, 2010). This does not necessarily lead to a reduction in unemployment given that a mismatch could exist between demand and supply (Verwest & van Dam, 2010). An overrepresentation of lowly qualified workers exists in krimpregio’s (Verwest & van Dam, 2010).
Next to that, the health of the population of krimpregio’s is worse than that of people in the rest of the Netherlands (Verweij & van der Lucht, 2014).
Lastly, krimpregio’s can face a decline in facilities such as shops, health care facilities, education, or an increasing distance to such facilities (Kulhman et al., 2014; Notten, 2013).
2.4 Hypotheses
As already discussed, previous literature has found regional differences in individual Big Five traits (Rentfrow et al., 2008) as well as the entrepreneurship-prone personality profile (Fritsch et al., 2019; Obschonka et al., 2013; Rentfrow et al., 2008). This regional difference is also expected to be present in the Netherlands, especially between the krimpregio’s and the other parts of the Netherlands. As previously discussed, one of the major problems of krimpregio’s is the fact that the population ages. This is partly because the older people stay or settle in the region whereas the young, usually highly educated, inhabitants migrate towards the bigger cities. Given that literature indicates that the relationship between age and entrepreneurship has an inverted U-shape (Kautonen et al., 2014; Lévesque & Minniti, 2006; Lévesque & Minniti, 2011; Minola, Criaco & Obschonka, 2016), with a peak between the age of 30 and 50 (Storey & Green, 2010), it seems reasonable to assume that the entrepreneurship-prone personality profile of people in the krimpregio’s will be lower than the profile of people living in the rest of the Netherlands.
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identified as krimpregio than it will be in other regions in the Netherlands.
Literature has investigated factors that lead to migration. Economics factors like wage differences and unemployment have been studied (Boneva & Frieze, 2001; Canache, Hayes, Mondak & Wals, 2013; Fouarge, Özer & Seegers, 2019; Paulauskaitė, Šeibokaitė, & Endriulaitienė, 2010; Silventoinen et al., 2007) next to socio-demographic factors such as gender (Canache et al., 2013; Paulauskaitė et al., 2010), age (Boneva & Frieze, 2001; Fouarge et al., 2019; Paulauskaitė et al., 2010; Van Dalen & Henkens, 2013), education (Boneva & Frieze, 2001; Paulauskaitė et al., 2010; Silventoinen et al., 2007; Van Dalen & Henkens, 2013;), family characteristics (Boneva & Frieze, 2001; Fouarge et al., 2019; Paulauskaitė et al., 2010) and migration background (Boneva & Frieze, 2001; Fouarge et al., 2019). It is usually the younger, well educated people, who have social networks abroad, that migrate (Canache et al., 2013; Fouarge et al., 2019; Paulauskaitė et al., 2010; Silventoinen et al., 2007; Van Dalen & Henkens, 2013).
In addition to this, literature has argued that people that choose to emigrate or have the intention to emigrate possess a specific set of personality characteristics (Boneva & Frieze, 2001; Paulauskaitė et al., 2010). Boneva and Frieze (2001) claim that in comparison to people not feeling the desire to emigrate individuals who have the intention to emigrate have a higher achievement motivation, power motivation and work centrality whereas they have a lower family centrality. As discussed above, achievement motivation is one of the two parts of the Big Five personality trait conscientiousness. Therefore, higher achievement motivation would mean a higher score on conscientiousness and hence an entrepreneurship-prone personality profile that will be closer to the perfect entrepreneurship profile.
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effect of Conscientiousness but no significant effect of Neuroticism.
As already discussed, the ‘perfect entrepreneur’ scores high on Openness to Experience, Extraversion, and Conscientiousness and low on Agreeableness and Neuroticism. Given this fact and the above stated links between the Big Five personality traits and migration, it can be concluded that it is most likely the more entrepreneurial people that are prone to migrate. These people will have a personality that is closer to the profile of a ‘perfect entrepreneur’ and hence will have higher scores on the entrepreneurship-prone personality profile.
An underlying factor explaining geographical differences in personality could be historical migration patterns (Fritsch et al., 2019; Rentfrow et al., 2008). Rentfrow et al. (2008) argue that these regional patterns could have emerged because of selective migration. The reasoning of selective migration entails that people will move to groups that are close to their own needs or personality traits (Hofstede & McCrae, 2004; Rentfrow et al., 2008), resulting in immigrants migrating to places that are close to their needs. Along this line of reasoning Rentfrow et al. (2008) have indicated that the geographical differences in personality, as shown in for example the study of Fritsch et al. (2019), may persist because individuals relocate to an environment where certain psychological and behavioural tendencies are common. Or they might relocate in search of more job security or financial prosperity. In this line of reasoning, it could be expected that individuals that are more entrepreneurial would migrate from regions with a low prone personality profile to regions with a higher entrepreneurship-prone personality profile. In combination with the fact that it is most likely the more entrepreneurial people that are migrating this leads to the following hypothesis:
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3. Data and methods
3.1 Data Collection and sample
Data for the construction of an overall indicator of entrepreneurship-prone personality profile based on the Big Five personality traits is collected from the Gosling-Potter Internet project. Respondents voluntarily participated in the online survey and had to indicate on a five-point Likert scale whether they agreed or disagreed with 44 statements covering the Big Five personality traits (Fritsch et al., 2019). In this paper, the Dutch data collected from the Gosling-Potter Internet project will be used. The Dutch sample consists of 159 636 responses in total collected between 1998 and 2015.
In order to assign respondents from the sample to a particular region the cases that did not provide a zip code of the place they spend most of their youth, or of their current place of residence were excluded. Resulting in a sample of 112 224 cases. Given the fact that age and gender are used as control variables, cases that did not provide information on either of the variables have been eliminated as well, leading to a sample of 110 789 cases.
With regard to age, only cases within the ages of 15 and 67 were selected, leading to a final sample of 107 908 cases. The lower boundary of 15 was chosen given that it is the age at which adolescents have to choose their profile in high school. Entrepreneurial interests would likely already have developed or started to develop. Additionally, approximately from the age of 16 onwards, children are able to give more reliable self-reported personality structures (Allik, Laidra, Realo & Pullmann, 2004) The upper boundary of 67 was chosen, given that it is the legal retirement age in the Netherlands. Individuals older than 67 that choose to fill in the questionnaire likely have a special interest in entrepreneurship and do not represent the average person of that age. By choosing these boundaries primarily people within working age have been selected. In addition, it seems reasonable that people within these age boundaries can choose where they want to live, providing useful information with regard to the migration hypothesis.
3.2 Variables
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Experience, Conscientiousness, Agreeableness, and Neuroticism. The reference profile will have the highest possible scores on Extraversion, Openness to Experience, and Conscientiousness and the lowest possible scores on Agreeableness and Neuroticism (Fritsch et al., 2019; Obschonka et al., 2013). A person’s entrepreneurship-prone personality profile will be calculated by taking the difference between the individual’s scores on the Big Five personality traits and the reference profile and subsequently squaring these differences. Adding these squared differences and reversing the algebraic sign of this sum results in the individual’s entrepreneurship-prone personality profile (Fritsch et al., 2019; Obschonka et al., 2013). The closer a person’s entrepreneurship-prone personality profile is to zero the better the fit between the person’s profile and the reference profile. To calculate the regional entrepreneurship-prone personality profile, the individual entrepreneurship-prone personality profile scores will be summed and an average will be calculated for individuals that live in the particular region (Fritsch et al., 2019; Obschonka et al., 2013). The reliability and validity of this measure can be assumed given that it has been used by several authors like Fritsch et al. (2019) and Obschonka et al. (2013).
A couple of control variables will be used. First of all, the age of the respondents will be controlled for. Literature has shown that age differences are present in the Big Five personality traits (Donnellan & Lucas, 2008; Lucas & Donnellan, 2009; McCrae et al., 1999; McCrae et al., 2004; Noftle & Fleeson, 2010; Soto, John, Gosling & Potter, 2011). Given that the entrepreneurship-prone personality profile is computed on the basis of scores on the individual Big Five traits, age will likely have an effect on the entrepreneurship-prone personality profile as well. Gender is the second control variable that will be used, given the lower entrepreneurial propensity among women as indicated in literature (Kibler et al., 2014; Koellinger et al., 2013, Storey and Green, 2010), but more importantly given that gender differences are found in the Big Five personality traits (Costa, Terracciano & McCrae, 2001; Hofstede & McCrae, 2004; Soto et al., 2011; Vecchione, Alessandri, Barbaranelli & Caprara, 2012; Weisberg et al., 2011). Additionally, a dummy variable for provinces will be included to control for provincial differences like differences in policies (Fritsch et al., 2019).
3.3 Analysis plan
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due to chance, first of all, a dummy variable has been created to indicate whether people lived in a krimpregio, and additionally whether they lived in a krimpregio located in the North or the South of the Netherlands. An OLS regression will be conducted with entrepreneurship-prone personality profile as the dependent variable and the dummy variables krimpregio north and
krimpregio south as independent variables. In the second model, the control variables age and
gender will be added. In the third and last model, dummy variables for provinces will be added to the regression to control for provincial differences.
To answer the second part of the research question, about the migration of entrepreneurial people from krimpregio’s to non krimpregio’s dummy variables have to be created first. Based on the zip codes of their place of residence in their youth and current place of residence respondents are being categorized into one of the four following categories: 1) inward movers 2) outward movers 3) non movers non krimpregio’s 4) non movers
krimpregio’s. Respondents belong to the inward mover category when they spend most of their
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4. Results
4.1 Main analysis
As mentioned in the previous section the final sample consisted of 107 908 respondents in the Netherlands. These particular responses are collected between the years 2003 and 2015. Among the 107 908 respondents, the mean entrepreneurship-prone personality profile is -19.34. The average age of the respondents is 28.44. Of the respondents 37.6 % is male and 62.7% is female.
Table 1. Overview of means of the entrepreneurship-prone personality profile.
Current Youth
Region Mean N Std. Dev. Mean N Std. Dev.
Non krimpregio -19.31 100053 6.129 -19.31 98013 6.135
krimpregio -19.63 7855 6.409 -19.55 9895 6.291
North of the Netherlands -19.86 1985 6.462 -19.72 2754 6.467
South of the Netherlands -19.56 5870 6.390 -19.49 7141 6.222
Comparing the average entrepreneurship-prone personality profile of -19.31 for people currently living not in a krimpregio with the average of -19.63 for people currently living in
krimpregio’s, it can be concluded that the average score on the entrepreneurship-prone
personality profile is higher for people living in parts of the Netherlands not identified as
krimpregio than it is for people living in krimpregio’s. Meaning that people not living in
krimpregio’s have a closer fit with the reference profile of a ‘perfect’ entrepreneur. Further dividing the krimpregio into North of the Netherlands (krimpregio 1 up to 4) and South of the Netherlands (krimpregio 5 up to 9) shows that there even is a difference in entrepreneurship-prone personality profile within the krimpregio’s. When doing the same comparison on the basis of place of residence in their youth the same conclusions can be drawn.
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statistically significant coefficient. These results support hypothesis 1 that there is a regional difference in entrepreneurship-prone personality profile in the Netherlands and that the people in krimpregio’s have a lower entrepreneurship-prone personality profile than people in the rest of the Netherlands.
When the control variables age and gender are added in model 2 the magnitude of the effect of living in a different region changes. Additionally, the R-squared increases from 0.00 to 0.024 indicating a better explanatory power of the model. Not living in a krimpregio results in an average profile of -19.472. Whereas living in a krimpregio in the North of the Netherlands will worsen the profile with 0.550 and living in a krimpregio in the South will worsen the profile with 0.259. The coefficient for age is 0.041 indicating that the personality profile will increase with 0.041 for every year increase in age. Gender has a negative coefficient of -1.623 indicating that the profile decreases with 1.623 when the respondent is a woman. This means that women have a personality profile that is further from the ‘perfect’ entrepreneurship profile than men. Given that all the variables are significant at the 1% level model 2 also supports the first hypothesis.
Table 2. The relationship between the region and entrepreneurship-prone personality profile (OLS regression).
Model 1 Model 2 Model 3
Constant -19.312*** (0.019) -19.472*** (0.056) -19.415*** (0.068) krimpregio North -0.543*** (0.139) -0.550*** (0.138) -0.453*** (0.152) krimpregio South -0.248*** (0.083) -0.259*** (0.082) -0.091 (0.095) Age 0.041*** (0.002) 0.041*** (0.002) Gender -1.623*** (0.038) -1.615*** (0.038)
Province dummies included No No Yes
Observations 107908 107908 107908
R² 0.000 0.024 0.024
Adjusted R² 0.000 0.024 0.024
Standard errors are in parentheses. * statistically significant at the 10 % level, ** statistically significant at the 5% level, *** statistically significant at the 1% level.
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of model 3 support hypothesis 1 for living in a krimpregio in the North of the Netherlands but not for the South of the Netherlands. However, the adjusted R-squared does not increase when adding the province dummies, indicating no greater explanatory power of the model.
With regard to the migration of entrepreneurial people firstly, dummies were created to be able to identify the people that moved. When comparing the averages from table 3 it can be seen that the people staying in the krimpregio’s have an average profile of -19.70 which is much further away from the reference profile of a ‘perfect’ entrepreneur than the profile of people in non krimpregio’s with an average of -19.34. Both the outward migrants as the inward migrants have a profile that is even closer to the profile of a ‘perfect entrepreneur’ namely an average profile of -19.24. The fact that the inward migrants have a profile closer to the reference profile than people in krimpregio’s and in non krimpregio’s is not in line with expectations that can be formed based on the selective migration theory. However, the fact that outward movers have a profile that is closer to the ‘perfect’ entrepreneur is in line with the second hypothesis. When looking at the results of the OLS regression in table 4, a slightly different picture emerges.
Table 3. Overview of means of entrepreneurship-prone personality profile per migration category.
Category Mean N Std. dev.
Inward movers -19,24 1139 6,476
Outward movers -19,24 3179 6,053
Non movers non krimp -19,34 96874 6,131
Non movers krimp -19,70 6716 6,396
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describe more entrepreneurial people, that move as indicated in the literature.
However, when the control variables age and gender are included the results change. Belonging to the inward moving category still has a positive coefficient and hence a positive effect on the entrepreneurship-prone personality profile. However, these results are not significant. Therefore, there is no evidence that there is a difference between the inward movers and people that live in krimpregio’s. Belonging to the outward moving category still increases the entrepreneurship-prone personality profile with 0.377 and to the non-movers in the rest of the Netherlands with 0.372. Both are statistically significant at the 1% level. Being a female again worsens the entrepreneurship-prone personality profile with 1.623. The effect of every increase in years of age is 0.041. Both of the control variables are statistically significant at a 1% level. Adding the control variables increases the adjusted R-squared of the model from 0.000 to 0.024. Therefore, the explanatory power of the model increases. These results are in line with the second hypothesis.
Table 4. The relationship between migration category and entrepreneurship-prone personality profile (OLS regression).
Model 1 Model 2 Model 3
Constant -19.701*** (0.075) -19.840*** (0.091) -19.640*** (0.105) Inward movers 0.459** (0.197) 0.274 (0.195) 0.268 (0.195) Outward movers 0.458*** (0.132) 0.377*** (0.131) 0.296** (0.135) Non movers non krimp 0.387***
(0.078) 0.372*** (0.077) 0.228*** (0.086) Age 0.041*** (0.002) 0.041*** (0.002) Gender -1.623*** (0.038) -1.616*** (0.038)
Province dummy included No No Yes
Observations 107908 107908 107908
R² 0.000 0.024 0.024
Adjusted R² 0.000 0.024 0.024
Standard errors are in parentheses. * statistically significant at the 10 % level, ** statistically significant at the 5% level, *** statistically significant at the 1% level.
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entrepreneurship-prone personality profile in comparison with living in krimpregio’s but now only with 0.228. The results for age and gender are roughly the same as in model 2. Hence, model 3 also provides evidence in support of hypothesis 2.
4.2 Robustness check
As previously mentioned in the methodology, the analysis is also carried out for a subsample of respondents between the age of 15 and 30. This is done because literature has indicated that the prime age for individuals to start a business is between the age of 35 and 50. Hence, the subsample of individuals between 15 and 30, consisting of the future entrepreneurs that policy makers might want to target. This sample consisted of 70 086 respondents in the Netherlands. The responses are collected between the years 2003 and 2015. Among these 70 086 respondents, the mean entrepreneurship-prone personality profile is -19.69. The average age of the respondents is 21.01. Of the respondents 35.8 % is male and 64.2% is female.
Table 5. Overview of means of the entrepreneurship-prone personality profile.
Current Youth
Region Mean N Std. Dev. Mean N Std. Dev.
Non krimpregio -19.67 65119 6.014 -19.67 63784 6.025
krimpregio -19.98 4967 6.257 -19.92 6302 6.099
North of the Netherlands -20.13 1219 6.325 -19.94 1722 6.233
South of the Netherlands -19.93 3748 6.235 -19.91 4580 6.049
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variables are lower. When the control variables are added both krimpregio North and
krimpregio South are significant at the 5% level instead of a 1% level. As soon as the province
dummies are added the significance level of the variable krimpregio North drops from 1% level significance to only significant at the 10% level. Furthermore, the squared and adjusted R-squared are slightly lower than in the main analysis. Despite the abovementioned differences in results between the main analysis and the analysis with the younger subsample the results still provide evidence in support of the first hypothesis.
Table 6. The relationship between the region and entrepreneurship-prone personality profile (OLS regression).
Model 1 Model 2 Model 3
Constant -19.667*** (0.024) -20.481*** (0.129) -20.577*** (0.138) krimpregio North -0.461*** (0.174) -0.383** (0.173) -0.364* (0.188) krimpregio South -0.266*** (0.101) -0.204** (0.100) 0.002 (0.115) Age 0.089*** (0.006) 0.087*** (0.006) Gender -1.653*** (0.047) -1.647*** (0.047)
Province dummy included No No Yes
Observations 70086 70086 70086
R² 0.000 0.021 0.023
Adjusted R² 0.000 0.021 0.022
Standard errors are in parentheses. * statistically significant at the 10 % level, ** statistically significant at the 5% level, *** statistically significant at the 1% level.
Regarding the averages of the migratory categories presented in table 7, it can be concluded that again the younger subsample results in an average entrepreneurship-prone personality profile that is further away from the reference profile of a ‘perfect’ entrepreneur, in every migratory category.
Table 7. Overview of means of entrepreneurship-prone personality profile per migration category.
Category Mean N Std. dev.
Inward movers -19,69 550 6,463
Outward movers -19,68 1885 5,773
Non movers non krimp -19,67 63234 6,021
Non movers krimp -20,02 4417 6,231
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8 show that in the first model, belonging to the inward moving category will increase the entrepreneurship-prone personality profile with 0.324. However, this is not significant indicating no difference between the inward moving category and people that stayed in the
krimpregio’s. Belonging to the outward moving category and belonging to the non-movers non
krimp category increases the entrepreneurship-prone personality profile with 0.334, significant at the 5% level and 0.350 significant at the 1% level. These results support the second hypothesis.
However, when the control variables age and gender are added in model 2, the coefficient of the outward moving category becomes insignificant indicating no difference between outward movers and people staying in the krimpregio’s. Belonging to the non-movers not located in
krimpregio’s still increases the entrepreneurship-prone personality profile with 0.279.
When the regional controls are added in model 3 all three independent variables become insignificant indicating no difference between inward movers, outward movers, non-mover not located in krimpregio’s and non-movers located in krimpregio’s. Hence, not providing support for the second hypothesis. The adjusted R-squared increased from 0.000 to 0.021 when the control variables were added. Subsequently, the R-squared increased from 0.021 to 0.023 when the regional controls were included, indicating higher explanatory power of model 3 than model 1 and 2.
Table 8. The relationship between migration category and entrepreneurship-prone personality profile (OLS regression).
Model 1 Model 2 Model 3
Constant -20.017*** (0.091) -20.764*** (0.153) -20.707*** (0.167) Inward movers 0.324 (0.273) 0.243 (0.270) 0.251 (0.270) Outward movers 0.334** (0.166) 0.132 (0.165) 0.049 (0.169) Non movers non krimp 0.350***
(0.094) 0.279*** (0.093) 0.128 (0.103) Age 0.089*** (0.006) 0.088*** (0.006) Gender -1.652*** (0.047) -1.647*** (0.047)
Province dummy included No No Yes
Observations 70086 70086 70086
R² 0.000 0.021 0.023
Adjusted R² 0.000 0.021 0.022
24
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5. Conclusion
5.1 Conclusions and contributions
This paper has investigated what the difference in entrepreneurship-prone personality profile is between regions identified as krimpregio and the rest of the Netherlands. Next to that, this paper has investigated whether there is a migration flow of entrepreneurial people from these
krimpregio’s to other regions in the Netherlands, that are believed to have higher
entrepreneurship-prone personality profiles. The Dutch sample of the Gosling-Potter internet project has been used for this investigation.
The results in this paper confirm that there is a difference in the average entrepreneurship-prone personality profile between the krimpregio’s and the rest of the Netherlands. Finding a regional difference in entrepreneurship-prone personality profile is in line with the literature that has identified regional differences in entrepreneurship-prone personality profile in the USA (Obschonka et al., 2013), Germany (Fritsch et al., 2019; Obschonka et al., 2013) and the UK (Obschonka et al., 2013).
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people out of the krimpregio’s is primarily driven by older people or has taken place in the past. Additionally, it might be the case that the migration flow of younger people is primarily driven by the fact that Colleges and Universities are not nearby.
By investigating whether a regional difference exists in the Netherlands this paper has contributed to the recent literature. Firstly, because research into the regional distribution of entrepreneurship-prone personality profile has only been conducted in the USA (Obschonka et al., 2013), Germany (Fritsch et al., 2019; Obschonka et al., 2013) and the UK (Obschonka et al.,2013). Additionally, this paper contributes to recent literature by investigating whether regional differences exist in a country that is considerably smaller than the UK, USA, and Germany. Another contribution that this paper makes to the recent literature is provided by doing research into the difference in entrepreneurship-prone personality profile between so called krimpregio’s, regions that face a decline in population, households and a number of related issues, and the other parts of a country. This has not yet been seen in the literature. Next to that, this paper contributes to the literature by investigating whether there is a migration flow of entrepreneurial people from the krimpregio’s towards the other parts of the Netherlands that have higher entrepreneurship-prone personality profiles.
5.2 Limitations and direction for future research
While this paper has provided some insights, there are also a couple of limitations present in this study. First of all, the survey was a voluntary internet-based survey. The first results were collected in a time period in which the internet was not as popular or normal as it is nowadays. Combining this with the fact that the respondents participated in this survey voluntarily it could be the case that the people filling in the survey were people that either showed a particular interest in their scores on the Big Five traits or that had a particular entrepreneurial interest and a higher entrepreneurship-prone personality profile. Secondly, there were only 150 000 responses over the course of 10 years. Thirdly, within this study, only the place of residence where respondents spend most of their youth and current place of residence was known. Information about whether respondents moved in between these periods is not provided. Additionally, the younger participants could still be living with their parents and not have the choice yet to move to a place of their preference.
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countries as well. Additionally, future research could try to establish whether the relationship between entrepreneurship-prone personality profile and entrepreneurial activity as found in the USA, UK and Germany is also present in the Netherlands. Moreover, future research could investigate whether the people with a higher entrepreneurship-prone personality profile that move out of the krimpregio’s actually engage in entrepreneurial activity. Finally, literature could investigate more in depth what the underlying reasons are for individuals to move out of the krimpregio’s, specifically whether entrepreneurial people indeed move because of greater entrepreneurial opportunities in other regions.
5.3 Policy implications
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