Master Thesis of R.D.A. Rosink
Personality traits and Regulatory Focus Theory; a comparison
between innovative and non-innovative entrepreneurs
Do innovative entrepreneurs differ as opposed to non-innovative entrepreneurs
in terms of personality traits?
Author and student number
R.D.A. (Rodney) Rosink - S3857050
MSc-BA Small Business and Entrepreneurship Supervisor | PD. Dr. M. (Michael) Wyrwich
Co-Assessor | Dr. M. (Maria) Kristalova
Faculty of Economics and Business University of Groningen
ABSTRACT
Based on a large, representative German household panel, this study tends to contribute to the understanding of differences between innovative and non-innovative entrepreneurs in terms of personality traits by using the Five Factor Model (FFM) and Regulatory Focus Theory (RFT). The main focus of this study is on the five fundamental personality traits; neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness. Regulatory Focus Theory is applied from a theoretical perspective and serves as a foundation and bridge between personality traits and explanations of differences between the entrepreneurial populations. In a nutshell, RFT consists of two elements; promotion- and prevention orientation, whereby innovative entrepreneurs are more promotion orientated and non-innovative entrepreneurs are more prevention orientated. In addition, a promotion orientation is associated with exploratory entrepreneurial activities and a prevention orientation is associated with more exploitative entrepreneurial activities. This research intends to contribute to a better understanding of personality differences between innovative and non-innovative entrepreneurs. Empirical results reveal significant differences between the two populations on three of the five fundamental dimensions of personality. Innovative entrepreneurs scored lower on neuroticism and higher on openness to experience and conscientiousness. From a reversed theoretical perspective, additional empirical results showed that the same three traits have a positive effect on individuals attracted to an innovative entrepreneurial career. All empirical results were insignificant regarding the traits extraversion and agreeableness. Empirical findings suggest that personality is an important component to differentiate innovative from non-innovative entrepreneurs. More generally, the findings contribute to the ongoing efforts to understand how personality affects innovative entrepreneurship on an individual level but for future research I suggest to further explore these concepts in a multidimensional model of variables, processes and environmental factors affecting innovative entrepreneurship and associated activities interlinked with innovative entrepreneurship.
TABLE OF CONTENT
1 INTRODUCTION ... 4
2 CONCEPTUAL FRAMEWORK ... 6
2.1 HISTORYANDORIGINOFREGULATORYFOCUSTHEORY ... 6
2.2 REGULATORYFOCUSTHEORYANDPERSONALITYCONSTRUCTS ... 6
2.3 REGULATORYFOCUSTHEORYANDINNOVATIVEANDNON-INNOVATIVE ENTREPRENEURS ... 8
2.4 FIVEFACTORMODELANDENTREPRENEURIALDIFFERENCES ... 9
3 METHODOLOGY ... 13
3.1 DATADESCRIPTION ... 13
3.2 MEASUREMENTOFPERSONALITYCONSTRCUTS ... 14
3.3 METHODOFANALYSIS ... 16
3.4 CORRELATIONANDVALIDITYCHECKS ... 16
4 EMPRICAL RESULTS ... 17
4.1 DESCRIPTIVESTATISTICSANDSAMPLEDESCRIPTIVES ... 17
4.2 MEANCOMPARISONANALYSESOFPERSONALITYCONSTRUCTS ... 18
4.3 MAINREGRESSIONANALYSESRESULTS ... 19
4.4 ADDITIONALREGRESSIONANALYSESRESULTS ... 21
5. DISCUSSION & CONCLUSION ... 25
5.2 PRACTICALIMPLICATIONS ... 28
5.3 LIMITATIONSANDFUTURERESEARCH ... 29
REFERENCES ... 32
1 INTRODUCTION
Individuals starting a self-employed activity play an important role in a dynamic and modern economy (Nissan et al. 2011). Entrepreneurs and specifically innovative entrepreneurs are particularly important for economic growth and welfare, and are rare species (Acs and Audretsch, 2010). Failure as an entrepreneur can be costly to society in terms of missed opportunities and lost resources that can be devastating to the individual entrepreneur in terms of its financial and psychological impact (Szerb, 2003). Entrepreneurs – and in particular innovative entrepreneurs – contribute in numerous ways to economic development. One-way entrepreneurs contribute to a modern economy is through innovative activities, which entails the development of new products, new processes, new sources of supply, but also the exploration and exploitation of new markets, as well as the development of novel ways to structure and organize their business. Multiple studies have found supporting evidence that concepts of entrepreneurship and innovation is interlinked (e.g., Santandreu-Mascarell, Garzon & Knorr, 2013).
An entrepreneur, however, is described as someone who is profit and growth orientated, can bear calculated risk, and who has innovative vein (Szerb, 2003). Entrepreneurship in general can be seen as “a process of creating new and valuable things” (Hirsch and Peters, 1989 cited in Szerb, 2003). By creating new and valuable things, the entrepreneur can be seen as a “key figure of economic growth”, whereby entrepreneurship in general can be marked as an engine for economic development (Schumpeter, 1934). Entrepreneurship can be seen as a driving force of innovation and is an important mechanism to achieve growth according to entrepreneurship literature. However, it should be noted that not all entrepreneurs desire growth and profit maximizations. Therefore, it is interesting to examine why not all entrepreneurs are focused on growth and innovation activities and why they have different orientations. Some previous conducted research in this area, supports the notion that it is due to personality and characteristics of entrepreneurs that might explain why some entrepreneurs are more promotion orientated and choose for innovative activities and why others have, for instance, a prevention orientation and choose for exploitation activities (Sizermai et al. 2010).
Despite the fact that previous studies researched the role of personality in the field of entrepreneurship as for instance, in the entry and exit decision to become and stay self-employed (e.g., Caliendo et al. 2013), and made the effort to differentiate entrepreneurs from non-entrepreneurial populations, no research to date, examined the role of personality differences between specifically innovative and non-innovative entrepreneurs. Therefore, the objective of this research is to contribute to the understanding of differences between innovative and non-innovative entrepreneurs by focusing on the fundamental personality traits1. This research will use the FFM also
referred to as the Big Five personality traits, and focus on the following personality traits; neuroticism, extraversion, openness to experience, agreeableness and conscientiousness. However, in order to make a distinction between innovative and non-innovative entrepreneurs from a theoretical perspective, Regulatory Focus Theory (RFT) will be applied. RFT is an appropriate theory to apply as it has been used to study various phenomena in entrepreneurship literature in combination with personality constructs (Brockner et al. 2014). Manczak, Zapata-Gietl and McAdams (2014), suggest that RFT and personality is interlinked and therefore, serves as a foundation and bridge between personality traits and explaining differences between innovative and non-innovative entrepreneurs from a theoretical perspective while using the FFM. In a nutshell, RFT has been introduced by Higgins (1997) and outlines the way in which people attempt to achieve the presence of positive outcomes which is referred to as promotion or preserve the absence of negative outcomes which is referred to as prevention. Subsequently, RFT outlines the way in which people enact goals and experience associated emotions related to attaining positive (promotion) or thwarting negative (prevention) outcomes. RFT finds its origin in the older conception of the approach-avoidance concept and begins with the hedonic principle (Manczak et al. 2014); people are assumed to act in ways aimed to maximize pleasure and minimize pain (Higgins, 1997).
The hypotheses in this study are derived from entrepreneurial literature combined with RFT and the FFM. RFT suggests that innovative entrepreneurs have the behavioral intention of a promotion orientation (i.e. entrepreneurial focus on growth and advancements as well as the desire to maximize the number of achieved “hits”). In contrary, non-innovative entrepreneurs will have more a prevention orientation (i.e. focus of an entrepreneur to avoid failure and minimize the number of losses) (Kammerlander et al. 2015). For instance, an entrepreneur associated with a promotion orientation would be high in openness to experience and an entrepreneur with a prevention orientation would be high in neuroticism (i.e. focus on stability and security) (Gorman et al. 2012). In-depth explanations will be provided in section 2. In an effort to better understand potential differences in personality traits between innovative and non-innovative entrepreneurs both populations will be compared. The following research question is formulated for this master thesis.
RQ: Do innovative entrepreneurs differ in terms of personality traits as opposed to non-innovative entrepreneurs?
The rest of the paper is organized as follows. Based on empirical evidence and literature, in Section 2. a conceptual framework and hypotheses of differences of personality traits between innovative and non-innovative entrepreneurs will be presented. In Section. 3, a description will be provided of the SOEP panel data used in the analyses and subsequently, the used methods of analyses for hypotheses testing. Section 4 is devoted to the presentation of results. Section 5 provides a discussion based on the presented hypotheses as well as conclusions. Concluding, Section 5 will provide practical implications based on conclusions, as well as limitations and suggestions for future research.
1 Personality traits refer to the coherent and constant structure of feelings, thoughts, and forms of behavior that influence
2 CONCEPTUAL FRAMEWORK
2.1 HISTORY AND ORIGIN OF REGULATORY FOCUS THEORYPeople are motivated to approach pleasure and to avoid pain. From the ancient Greeks, through 17th- and 18th-
century British philosophers, to 20th- century psychologists, this hedonic or pleasure principle has dominated
scholars’ understanding of people’s motivation. It is the basic motivational assumption of theories across all areas of psychology (Gray, 1982). One of the earliest uses of the hedonic principle was a lawful description of orderly event patterns. Careful observations indicated that when a situated behavior produced pleasure it was more likely to be repeated in that situation, whereas when a behavior produced pain it was less likely to be repeated in that situation. These observed events led to summary statements like “pleasure stamps in” and “pain stamps out” (Thorndike, 1935). The theory of regulatory focus begins by assuming that the hedonic principle should operate differently when serving fundamentally different needs, such as the distinct survival needs of nurturance (e.g., nourishment) and security (e.g., protection) (Higgins, 1997). For instance, human survival requires adaptation to the surrounding environment, especially the social environment (Buss, 1996). Higgins (1997) derived – and further elaborate on regulatory focus theory - from the hedonic principle, which expands theory about the approach motivation (i.e. the attempt to reduce discrepancies between the current states and desire end-states).
Regulatory Focus Theory (RFT) proposes that self-regulation in relation to strong ideals versus strong oughts differs in regulatory focus. Ideal self-regulation involves a promotion focus, whereas ought self-regulation involves a prevention focus. People are motived to approach desired end-states, which could be either promotion-focus aspirations and accomplishments or prevention-promotion-focus responsibilities and safety. But with this general approach toward desired end-states, regulatory focus can induce either approach or avoidance inclinations. Because a promotion focus involves sensitivity to positive outcomes (their presence and absence), an inclination to approach matches to desired end-states is the natural strategy for promotion self-regulation. In contrast, because a prevention focus involves sensitivity to negative outcomes (their absence and presence), an inclination to avoid mismatches to desired end-states is the natural strategy for prevention self-regulation (Higgins, Roney, Crowe & Hymes, 1994).
In summary, regulatory focus is concerned with how people approach pleasure and avoid pain in different ways. RFT implies that differences in performance, emotions, decision making, and so on, could occur as a function of regulatory focus independent of the hedonic principle per se. It even implies that some phenomena traditionally interpreted in hedonic terms has been replaced in terms of regulatory focus. Within the originality of RFT, a promotion focuses yields sensitivity to the presence or absence of positive outcomes and approach as strategic means, whereas a prevention focus yields sensitivity to the absence or presence of negative outcomes and avoidance as strategic means (Higgins et al. 1998).
2.2 REGULATORY FOCUS THEORY AND PERSONALITY CONSTRUCTS
hedonic principle (Manczak et al. 2014); “people are assumed to act in ways aimed to maximize pleasure and minimize pain”. But theory adds that pursuing these contrasting goals is experienced in fundamentally different ways, each subsuming both approach and avoidance impulses.
Promotion motivation attempts to move toward opportunities for reward and away from the absence of
reward (Higgins, 1997). To put promotion motivation more into perspective an example will be given. Assume that when approaching physical fitness, an individual with a promotion orientation might take up running to see if he could compete in a marathon one day. If one needs to make decisions, eagerness becomes the preferred detection strategy for identifying targets that might further enhance the achievement of promotion goals, thereby producing a tendency to experience ‘false positives’ rather than missed opportunities (Molden and Higgins, 2008). The rate of success involving a promotional goal elicits feelings of pleasure, and failure results in sadness.
Conversely, prevention motivation attempts to move away from the presence of negative outcomes and toward the preservation of its absence (Higgins, 1997). To put prevention motivation more into perspective, the aforementioned example will be used but from an opposite perspective. A person who has a prevention orientation to physical fitness might similarly try to run but do so with the goal of preventing weight gain or preserving health. To this end, a vigilant strategy is utilized, often resulting in more missed rewards of service of preventing losses. Feelings of calmness occur when prevention goals are achieved, and anxiety arises when they are thwarted (Manczak et al. 2014).
More importantly, promotion and prevention orientation can be subjected to chronic motivations. Chronic motivation is one’s tendency to pursue promotion or prevention goals which can be shaped by the demands of the environment but can also exist as a more-or-less stable and persistent preference within an individual across time and situations. The study of Lisjak, Molden, and Lee (2012), pointed out that although there are differences in induced motivations and consistent findings in individual differences regarding regulatory focus, their study results suggest a natural intersection with personality preferences related to chronic motivations.
The study of Manczak et al. (2014), revealed that using the Big Five trait taxonomy in order to link personality traits to RFT serves as the best bridge between personality traits and RFT. As far as theory is concerned, promotion and prevention focus would appear to share conceptual ground with some traits in particular; extraversion, neuroticism, and openness to experience. Further elaborating on Grey’s (1978) Reinforcement Sensitivity Theory, contended that extraversion (E) best captures personality features associated with approach motivations. For instance, Individuals high in E have greater orientation to opportunities and potential for reward, much like promotion focus. In contrast, individuals low in E, are more attuned to potential for punishment, similar to prevention focus. Neuroticism (N), was expected to relate to RFT through its overlap with prevention orientation, a relationship also demonstrated in Gorman et al. (2012) meta-analysis. Individuals high in N, like those with greater prevention orientation, experience frequent anxiety and employ vigilance towards against perceived threats. In RFT, anxiety is viewed to be a signal of threat, motivating the organism to withdraw from potential dangers in the environment and to remain especially ware and vigilant. Next, openness to experience (O) has been proven to share a conceptual space with regulatory focus. People high in O, attempt to explore and understand their experiences, exhibiting intellectual curiosity, non-conformity and a preference for novelty (Vaughn et al. 2008). In contrast, people low in O, prefer predictable and familiar experiences and are distrustful of change, echoing the caution conveyed in prevention focus. Consistent with this overlap, Vaughn et al. (2008) demonstrated that higher O was related to increased pursuit of promotion-related goals and reduced pursuit of prevention-related goals for participants’ ratings of both actual and imagined goals.
As presented, RFT is explained more in-depth and linked to the concept of fundamental personality traits. Suggesting that promotion orientation has been consistently linked to more positive constructs (e.g., creativity, flexibility, self-esteem and optimism), whereas prevention orientation has been related to more negative constructs (e.g., reduced job satisfaction and negative effects) (Gorman et al. 2012; Liberman et al. 2001). In section 2.3, I will further elaborate on RFT and personality concepts but from an entrepreneurial perspective in order to explain – and make a distinction – between innovative and non-innovative entrepreneurs from a theoretical point of view.
2.3 REGULATORY FOCUS THEORY AND INNOVATIVE AND NON-INNOVATIVE ENTREPRENEURS
In this case, entrepreneurs/individuals with high levels of promotion focus are driven to maximize achievements, whereas entrepreneurs/individuals with high levels of prevention focus strive to meet their obligations and avoid failures (Brockner and Higgins, 2001).
Promotion focus. Entrepreneurs with high degrees of promotion focus are motivated by the need for
growth and advancement (Crowe and Higgins, 1997). They concentrate on potential gains and strive to maximize their achievements or “hits”—a “hit” is a positive outcome provoked by an entrepreneurs’ decision and actions (Brockner et al. 2004). In other words, entrepreneurs with high levels of promotion focus are motivated by the perceived potential for positive outcomes and aim to maximize rewards for their efforts, while the motivation of entrepreneurs with low levels of promotion focus remains largely unaffected by the possibility of maximizing hits. The absence of achievements leaves entrepreneurs with high levels of promotion focus with negative feelings. Subsequently, promotion focus involves a more exploratory nature which is typically associated with search, experimentation and variation (Lavie et al. 2010). Exploratory entrepreneurial activities or innovative activities, include for instance, exploring new technologies, expand the business portfolio, targeting new customer groups or venturing into new market segments. The study of Kammerlander et al. (2015), pointed out that innovative entrepreneurs pursue higher levels of promotion focus (promotion orientation) and utilize more exploratory activities.
Prevention focus. In contrast, entrepreneurs with high levels of prevention focus are driven by the need
for security, safety, and responsibility and thus strive to avoid any failures or potential negative outcomes (Brockner et al. 2004). To this end, entrepreneurs are driven by the fear of punishment for caused failures, for instance by negligence instead of being motivated by rewards for their successful activities. The absence of failures creates the positive feeling of calmness amongst entrepreneurs with high levels of prevention focus, whereas the presence of failure leads to negative feelings or tensions (Idson et al. 2000). Subsequently, prevention focus involves a more exploitative nature which refers to enhancements of productivity and efficiency through choice, execution, and variance reduction (Lavie et al. 2010). Exploitative entrepreneurial activities for instance are, cost-cutting or quality-improving activities as well as attempts to increase the level of automation (Lubatkin et al. 2006). Non-innovative entrepreneurs pursue higher levels of prevention focus (prevention orientation) and utilize more exploitative activities, according to the study of Kammerlander et al. (2015).
Table 1 – summary of difference between innovative and non-innovative entrepreneurs Innovative entrepreneurs Non-innovative entrepreneurs Pursuit higher levels of promotion focus, which refers to the
desire for growth, advancements and achievements of “hits—i.e. is a positive outcome provoked by an entrepreneurs’ decisions and actions”. They possess a more explorative character and undertake more exploratory activities.
Pursuit higher levels of prevention focus, which is associated with the desire to avoid failures and to minimize the number of losses. They possess a more exploitative character and undertake more exploitative activities.
Note. A brief summery about the distinction between innovative and non-innovative entrepreneurs 2.4 FIVE FACTOR MODEL AND ENTREPRENEURIAL DIFFERENCES
taxonomy of personality (Costa and McCrae, 1992). Each personality dimension describes a broad domain of psychological functioning that is composed from a set of more specific and narrow traits. The FFM brings together over 40 years of research on emotional, interpersonal, experiential, attitudinal, and motivational style of the individual. The work of Costa and McCrae (1992), has provided what is perhaps the most developed operationalization of the FFM to date. The FFM is particularly suited to describe human personality traits in terms of individually differing behaviors and experiences.2 The FFM serves as the foundation combined with RFT for
the hypotheses that will follow (see Table 2 for an overview of hypotheses).
Neuroticism. Neuroticism represents individual differences in adjustment and emotional stability. Individuals that
score high on neuroticism tend to experience a number of negative emotions including anxiety, hostility, self-consciousness, impulsiveness and vulnerability. People who score low on this dimension can be characterized as self-confident, calm, relaxed and emotional stable (Costa and McCrae, 1992). Once individuals conduct entrepreneurial activities, they must be able to manage stress and uncertainty while they are working in an unstructured environment with uncertain outcomes. Moreover, entrepreneurs usually have financial stakes in the company. Being stress resistant is thus helpful for bearing uncertainty during later stages of entrepreneurial activities such as entering new markets, developing new products, and expanding the business portfolio. According to RFT, it would be most likely that innovative entrepreneurs with a promotion orientation tend to feel more comfortable in a relatively unstructured environment with uncertain outcomes due their explorative character and desire for growth and achievements (Higgings, 1997; Kammerlander et al. 2015). In contrary, non-innovative entrepreneurs with a prevention orientation and with an exploitative character tend to seek more security and stability due their desire to avoid failure (Brockner et al. 2004; Gorman et al. 2012). So, undertaking innovative entrepreneurial activities, as for instance, searching for new viable business opportunities or targeting new customer segments, bears risk and can produce physical and psychological stress. This suggest that emotional stability is more appropriate when having a promotion orientation. Thus, being emotionally stable and having self-confidence and resilience in the appearance of stress, appears to be more important for innovative entrepreneurs, as for non-innovative entrepreneurs. Therefore, the expectation is that innovative entrepreneurs will score lower on this personality dimension.
H1. Innovative entrepreneurs will score lower than non-innovative entrepreneurs on Neuroticism.
Extraversion. Extraversion describes the extent to which people are assertive, dominant, energetic, active,
talkative, and enthusiastic. People who score high on extraversion tend to be cheerful, like people and groups, seek excitement and stimulation. A low score on this dimension means that people prefer to spend more time alone and are characterized as quieter, and independent. This dimension is positively related to interests in enterprising occupations (Costa and McCrae, 1992). Extraverted individuals tend to be sociable, which enables entrepreneurs to develop social networks more easily, and as a result, may result in stronger partnerships with clients and suppliers. All elements of this dimension—being assertive, seeking leadership, and developing networks—are positively related to entrepreneurial development regarding the entry decision and in terms of entrepreneurial
2 As a recapitulation, personality traits refer to a coherent and constant structure of feelings, thoughts, and forms of behavior
survival (see Ciavarella et al. 2004). With respect to RFT, it seems that innovative entrepreneurs having a promotion orientation, focus more on exploratory activities such as searching for viable business opportunities and the willingness to act upon such oppertunities. Subsequently, it is most likely that they will have intensified interaction with a diverse range of constituents (e.g., venture capitalists, partners, suppliers, employees etc.) as opposed to non-innovative entrepreneurs who are more focused on exploitation activities—enhancement of productivity and efficiency of existing business processes (Kammerlander et al. 2015). Furthermore, Gorman et al. (2012) suggests that entrepreneurs high on extraversion have greater orientation to explore opportunities and appropriate potential rewards, which is equivalent to innovative entrepreneurs with a promotion orientation. In contrast, entrepreneurs low on extraversion are more attuned to potential for failure, which is equivalent to non-innovative entrepreneurs having a prevention orientation. Thus, it appears that non-innovative entrepreneurs benefit more from extraverted personality traits due to intensified and direct social interaction with external and internal constituents, as well as the potential for exploring novel opportunities as compared to non-innovative entrepreneurs. Therefore, the expectation is that innovative entrepreneurs will score higher on this dimension.
H2. Innovative entrepreneurs will score higher than non-innovative entrepreneurs on Extraversion.
Openness to Experience. This is a personality dimension that characterizes someone who is intellectually curious
and tends to seek new experiences and explore novel ideas. A high score on this dimension means that someone is creative, innovative, imaginative, reflective and untraditional. A low score on this dimension characterizes someone who is conventional, narrow in interests, and unanalytical (Costa and McCrae, 1992). The attributes of exploring new ideas, being creative, and trying out novel approaches are in particular suited for undertaking exploratory entrepreneurial activities such as, new product development, exploring new technologies, entering new markets, expand the business portfolio or targeting new customer segments. Moreover, the attributes as mentioned should also have a positive influence on entrepreneurial activities such as, starting a new venture or the further development of a venture (see Sarasvathy, 2004). On the other hand, considering “entrepreneurial survival” for instance, it can be argued that, in the entry period, calmness is more necessary than the creativity of an entrepreneur due to environmental dynamics and uncertainty. From the perspective of RFT, innovative entrepreneurs with a promotion orientation, are inclined to conduct more exploratory entrepreneurial activities due to their desire to seek growth and advancements, as well as their need for achieving “hits”.3 This indicate pursuing
more future-orientated activities to search for new business opportunities and to explore novel ideas in order to accommodate their needs (Wiklund and Sheperd, 2011). Exploratory activities require creativity while being innovative—undertaking novel approaches and developing new products or services, designing new business methods or strategies. However, creativity is also an advantage in problem-solving endeavors as entrepreneurs in general face a lot of challenges they have to cope with. With respect to non-innovative entrepreneurs with a prevention orientation, they are inclined to follow a more exploitative direction and undertake more exploitative entrepreneurial activities due their narrow interests (i.e. increasing or maintaining productivity, security, stability and are inclined to follow established routines) (Higgins, 1997; Kammerlander et al. 2015). This suggests that non-innovative entrepreneurs prefer predictable and familiar experiences and are distrustful of change, echoing
3 A recapitulation, a “hit” refers to a positive outcome provoked by an entrepreneur’s decisions and actions” (Brockner et al.
the caution conveyed in prevention focus. Equivalent to findings of Vaughn et al. (2008), which demonstrated that higher O was related to increased pursuit of promotion-related goals, the expectation is that innovative entrepreneurs will score higher on this dimension.
H3. Innovative entrepreneurs will score higher than non-innovative entrepreneurs on Openness to Experience.
Agreeableness. This dimension assesses one interpersonal orientation. Individuals who score high on this
dimension can be characterized as trusting, forgiving, caring, altruistic, and gullible. It represents someone who has cooperative values and a preference for interpersonal relationships. A low score characterizes someone as manipulative, self-centered, suspicious and ruthless (Costa and McCrae, 1992). Diving deeper into this dimension suggests that individuals with high levels of agreeableness, are cooperative, while low levels indicate self-centered and hard-bargaining individuals. From an entrepreneurial perspective combined with RFT, high levels of agreeableness may inhibit one’s willingness to drive hard bargains, look out for one’s self interest, and influence or manipulate others for one’s own advantage. As RFT suggests that entrepreneurs with a promotion focus poses an explorative nature with the desire for growth, advancement and achievement of “hits” (e.g., explore new business opportunities, explore new market segments, developing new products or services), they are less inclined to score high on this dimension due the fact that they often operate with less legal protection within a thin margin of error and limited availability of resources as compared to non-innovative entrepreneurs (Zhao and Seibert, 2005). As a result, innovative entrepreneurs can suffer serious consequences from even small bargaining disadvantages, as for instance, during entry or latter entrepreneurial stages (e.g., starting a new venture, expanding the business portfolio or network alliances). In addition, RFT suggests that innovative entrepreneurs with a promotion orientation tend to follow their desire for achievements and combine this with their preference to undertake exploratory entrepreneurial activities. Therefore, it is most likely that innovative entrepreneurs are inclined to pursuit their own interests and can be ruthless towards achieving their desired end-state. This would indicate that innovative entrepreneurs would be less cooperative and self-centered. In contrary, non-innovative entrepreneurs with a prevention orientation pursuit more exploitative entrepreneurial activities and favor working within established routines. Their orientation is directed towards activities associated with factors such as, stability, security and safety (Higgins, 1997; Kammerlander et al. 2015). Due their desire for safety and stability, non-innovative entrepreneurs are more inclined to be cooperative and to avoid discrepancies. Therefore, the expectation is that innovative entrepreneurs will score lower on this dimension.
H4. Innovative entrepreneurs will score lower than non-innovative entrepreneurs on Agreeableness.
Conscientiousness. This dimension indicates an individual’s degree of organization, persistence, hard work and
their explorative character (Kammerlander et al. 2015). RFT suggests that individuals with high levels of promotion focus are strongly motivated by the need for growth and profit maximization (Crowe and Higgins, 1997). As a consequence, such individuals will most likely aim for innovative activities due their explorative nature and as a result, will have a higher achievement motivation as opposed to their counterparts. As innovative entrepreneurs’ desire achieving positive feelings and outcomes, their motivation to maximize rewards for their own efforts should be elevated (Brockner et al. 2004). In other words, innovative entrepreneurs are especially motivated by acquiring achievements due their own efforts, and due their explorative character they focus on innovative activities. As a result, they are more persistent and motivated to achieve growth and desired goal accomplishments. On the other hand, McClelland (1961), argues that non-innovative entrepreneurs would not be characterized by a high need for achievement and a high score on this dimension because – according to RFT – they are more prevention orientated. This fact suggests that, for instance, in an organizational environment with a focus on enhancing efficiency and productivity, entrepreneurs must work with and through others. Moreover, entrepreneurship literature suggests that non-innovative entrepreneurs working within an established organization, with established routines, are likely to have their responsibilities, goals, and work performance more closely structured and monitored by existing organizational systems and day-to-day interactions (see Zhao and Seibert, 2006). This fact suggests a more secure and safely environment for non-innovative entrepreneurs. Since innovative entrepreneurial activities involve a higher level of uncertainty and environmental turbulence, which demands a high level of perseverance and determination, the expectation is that innovative entrepreneurs will score higher on this dimension.
H5. Innovative entrepreneurs will score higher than non-innovative entrepreneurs on Conscientiousness. Table 2 - overview of presented hypotheses
Neuroticism Extraversion Openness Agreeableness Conscientiousness Innovative
entrepreneurs - + + - +
Non-innovative
entrepreneurs + - - + -
Note. A plus/minus sign indicates that, from theoretical considerations, a positive/negative correlation is expected on the stated personality dimension.
3 METHODOLOGY
3.1 DATA DESCRIPTIONIn the following analysis, the database used is the German Socio-Economic Panel (SOEP). The SOEP is an annual representative panel survey covering detailed information about the socio-economic situation of household members living in more than 10,000 households across Germany.4 The database started in 1984, and in 1990—
shortly after German reunification—it was enlarged to include a representative sample from East Germany. This feature makes the SOEP unique among household panel surveys worldwide. Every year since 1984, around 15,000
4 The SOEP is similar to the PSID (Panel Study of Income Dynamics) in the US and the BHPS (British Household Panel
households and 30,000 individuals have been surveyed. The data in SOEP provide information on every member of every household that participated in the survey. Respondents include Germans living in both the former East- and West Germany, foreign citizens residing in Germany, recent immigrants, and a new sample of refugees added in 2016. The SOEP database contains ten focus topics all related to aspects of life (e.g., demography and population, health and care, education and qualification, personality etc.). As this study focuses on gaining deeper understanding of potential differences in personality traits between innovative and non-innovative entrepreneurs, the area of “personality” will be used in SOEP. In particular, the Big Five concept will be used, which was treated as a separate topic in the SOEP database.
A short recapitulation, the Big Five personality traits concept also referred to as the Five-Factor Model (FFM), makes it possible to describe human personality traits in terms of individually differing behaviors and experiences. At the heart of this approach lies the assumption that there exist five broad, non-overlapping dimensions of personality that can be used to describe human personality: neuroticism, extraversion, openness to experience, agreeableness and conscientiousness. An additional recapitulation, “personality traits” are coherent and constant structures of feelings, thoughts, and forms of behavior that influence psychological conditions and individual actions (Costa and McCrae, 1985).
The sample that is being used for this study was established in 2005, 2009, and 2013. In 2009, and 2013 the scale is extended by one additional item measuring openness to experience. The total sample in the SOEP database is N = 60,168. However, this sample will be reduced due to corrections for selecting only self-employed individuals and an additional emphasis on adults varying between the ages 20 and 65.
3.2 MEASUREMENT OF PERSONALITY CONSTRCUTS
Personality constructs. In several survey waves, the SOEP included short versions of established psychological
personality inventories. This allows—for the focus of this study—to explicitly study personality traits and their consequences on a large representative sample of the population in order to make a comparison between innovative and non-innovative entrepreneurs and analyze if, and on which personality traits they differentiate from one another. Specifically, in 2005, 2009, and 2013, the SOEP included special personality questionnaires that measured respondents’ Big Five personality factors.
The scale development of the personality constructs needed to be short and efficient, due to space and time reasons (source: SOEP database manual) but is nevertheless more than capable of reflecting the structure of the FFM in a robust and reliable way. The development and validation of the scales took place in the framework of a SOEP pretest, which represents an independent representative survey of the resident population of Germany.5
The establishment of measurements constructs in the SOEP database, were derived from the Ten-Item Personality inventory (TIPI; Gosling et al. 2003) and the BFI-25. The BFI was developed based on a principal component analysis carried out with the entire inventory by John et al. (1991): the five items for each personality dimension with the highest factor loadings were eventually included in the multiple survey waves of the SOEP questionnaire. The Big Five personality scale in the SOEP database consisted of a total of 15 items measuring the “five personality
5 The eventual choice of items was made based on five criteria: (1) the conditions and limitations that result from the SOEP
traits” and was used in the SOEP in 2005, 2009, and 2013. Each personality construct consisted out of three items (see Appendix – Table 14 for an overview). All items are measured on a seven-point Likert-type scale ranging from 1 (“does not apply to me at all”) to 7 (“applies to me perfectly”). Respondents’ scores were obtained for a personality trait by averaging the scores from the different statements referring to the construct; for some items the scale is inverted (see Appendix – Table 14).
Apart from the personality constructs, this study included well-known determinants of entrepreneurship (e.g., Parker, 2009) as additional control variables listed in Table 15 (see Appendix). The control variables that were included are; age, gender and amount of education or training in years.6 These control variables provided
additional perspectives for implications into discovering differences between innovative and non-innovative entrepreneurs. For instance, is there a difference in age (e.g., are innovative entrepreneurs younger as compared to non-innovative entrepreneurs), and is there a difference in gender (e.g., are most non-innovative entrepreneurs female), and finally, is there a difference in the amount of education or training in years (e.g., do innovative entrepreneurs experienced a higher amount of education or training).
Lastly, since the database does not originally separate innovative and non-innovative entrepreneurs, this study follows the Eurostat definition and categorization of high-technology industries and knowledge-intensive services in order to label innovative and non-innovative entrepreneurs in the database (see Appendix – Table 16). Statistics on high-tech industries and knowledge-intensive services comprise economic, employment and science, technology and innovation data describing manufacturing and services industries, or products traded broken down by technological intensity. The domain uses various other Eurostat’s official statistics descriptions, but coverage and usage of data is dependent on the primary sources of data. Two main approaches are used in the domain in order to identify innovative sectors; (1) sectoral approach and (2) product approach. This study focuses on the sectoral approach which is an aggregation of the manufacturing industries according to technological intensity (R&D expenditure/value added) and based on the statistical classification of economic activities in the European Community (NACE) at digit level. The data used for this study comprises sector description based on NACE 2-digit level. The level of R&D intensity served as a criterion of classification of economic sectors into high-technology, medium high-high-technology, medium low-technology and low-technology industries. This study emphasized on manufacturing industries with high-technology and medium-high technology in order to categorize innovative sectors. As a consequence, medium low-technology and low-technology industries are excluded. Services are mainly aggregated into knowledge-intensive services (KIS) and less knowledge-intensive services (LKIS) based on the share of tertiary educated persons at NACE 2-digit level. Subsequently, only knowledge intensive services (KIS) are used to mark innovative sectors. Hence, the sectoral approach does not include data on high-tech trade and patents.
In summary, classification of innovative entrepreneurs in innovative sectors, as opposed to non-innovative entrepreneurs and sectors are made according to the Eurostat NACE 2-digit classification. Targeted manufacturing industries comprising innovative entrepreneurs consist of; technology and medium high-technology industries, and knowledge-based services labeled as knowledge intensive services (KIS). All the remaining sectors are labelled as “non-innovative entrepreneurs” (source: Eurostat manual description of sectors).
3.3 METHOD OF ANALYSIS
First of all, a descriptive statistics analyses of the sample and variables that have been used, are conducted. This part analyzed distributions of the two populations; innovative and non-innovative entrepreneurs, and analyzed differences between the populations in age, gender, and amount of training or education in years.7 Second, a mean
comparison test (independent sample t-test) is conducted, where innovative and non-innovative entrepreneurs are compared with respect to the Big Five personality traits. Third, in order to test hypotheses, regression analyses have been conducted for each personality trait where each trait serves as the dependent variable. The regression analysis is restricted to innovative and non-innovative entrepreneurs. The main independent variable was “being an innovative entrepreneur”. The main regression analysis consisted of single- and multiple regression analyses.8
To finalize, additional probit regression analyses have been conducted in order to test if certain personality traits determine if an entrepreneur is being innovative or not (i.e. personality traits affecting occupational choice). This is a slightly different perspective in contrast to the hypotheses testing part, where tests consisted of, if being an innovative entrepreneur has certain personality traits or not. With this two-sided testing approach, further insights are being gathered about the mechanisms at play. However, to conduct the probit regression analyses the model was redesigned. The original dependent variable (each personality trait) was switched with the independent variable (being an innovative entrepreneur).9 As explained, the intention was to check if a certain personality traits
might affect entrepreneurs into pursuing an innovative entrepreneurial career (i.e. have a positive effect on being or becoming an innovative entrepreneur) and subsequently, compare results with the hypotheses testing results. Overall, the significance level that was used in all theory testing analyses is 5% (a = 0.05).
3.4 CORRELATION AND VALIDITY CHECKS
First of all, a factor analysis was conducted as an ex-post validation of the personality constructs which confirmed that items used in the analysis load on distinct factors, which generally correspond very well to the Big Five traits and personality constructs. This is noteworthy because it shows that personality constructs used to measure the Big Five personality traits are independent. As this study only observes personality traits in selected survey waves, the assumption is that traits were stable for adults within a few years and also used them for the same respondents in the other survey years.10 All items scored greater than 0.5 and all items loaded into the correct factor.
Furthermore, the results indicate that all multiple item constructs have good reliabilities coefficient as between 0.53 and 0.66. This also indicates that almost all relevant correlations between the constructs are confirmed, thus increasing the confidence that measures of all personality constructs available in the dataset are closely related to theoretical concepts. These ex-ante correlation checks indicated that all personality constructs used in this study measure concepts are correlated but clearly distinct, allowing for the conclusion that, a priori, all variables should
7 First the focus was on the control variables; age, gender and amount of education or training in years. In addition, for
differences in gender a Pearson Chi-Squared test has been conducted. Regarding age and amount of education or training in years an independent sample t-test was conducted.
8 The main regression analyses consisted of a single regression (referred to as model one in the result section) and multiple
regression (referred to as model two in the results section) when adding the control variables.
9 In the design for the probit regression analyses, the new dependent variable is ‘being an innovative entrepreneur’ and the
new independent variable is ‘each of the five personality traits’.
10 The correlation coefficients of the Big Five personality variables in the sample, as measured in 2005, 2009, and 2013 are;
be included in the analysis related to this study. Furthermore, variance inflation factors were calculated after conducting linear regression analyses for all personality constructs with respect to innovative entrepreneurs and find that all outcomes are satisfied, meaning that all results were smaller than 10 percent.
4 EMPRICAL RESULTS
4.1 DESCRIPTIVE STATISTICS AND SAMPLE DESCRIPTIVESConducting a descriptive statistics analysis, resulted in a valid sample of N = 20,405 when correcting for self-employment and targeting specific people varying between the ages 20 - 65 (M = 43.9 age). Within the valid sample, distributions between men and woman are 47.5% male, and 52.5% female. Subsequently, descriptive statistics reveal that distributions are 36.6% innovative entrepreneurs and 63.4% non-innovative entrepreneurs. Furthermore, results indicate that amount of education or training in years variates between 7 – 18 years. The assumption was that the lower the amount of education or training an entrepreneur has experienced, the lower the level of education is. Later on, an analysis was conducted to see if innovative entrepreneurs have experienced more years of education or training.
Secondly, descriptive statistics crosstabulations and accordingly, a Pearson Chi-Square test is conducted to check for differences in gender between innovative and non-innovative entrepreneurs (see Table 3). In other words, is there a significant difference in gender between innovative and non-innovative entrepreneurs. Results of the Pearson Chi-Square test indicate that outcomes are significant and positive (c2 = 36.291; p < .001), but with a
small size of effect (V = .280).11 This result suggests a difference in gender between the two populations. Further
interpretation of results indicates that there are more innovative entrepreneurial women as compared to their adversaries (female = 54.5%; male = 45.6%).
Table 3 - descriptive statistics and crosstabulations (N = 20,405)
Crosstabulations Female Male N Pearson
Chi-square (c2) Cramer’s V Innovative entrepreneurs 54.4% 45.6% 8,377 36.291 *** .280*** Non-innovative entrepreneurs 51.5% 48.5% 12,028
Note. Distribution of gender between innovative and non-innovative entrepreneurs.
* p < .05. Results are significant at the 0.05 level (2-tailed). ** p < .01. Results are significant at the 0.01 level (2-tailed). *** p < .001. Results are significant at the 0.001 level (2-tailed).
Third, comparing age and amount of education or training in years between innovative and non-innovative entrepreneurs 12, results reveal significant outcomes, which indicate differences in age and amount of
education or training in years between populations. On the one hand, results concerning age, show significant and
11 In this study, analyses were conducted related to the relevance of significant results. In this situation, tests were applied to
determine the level of correlation between variables in terms of ‘effect size’ by calculating the Cramer’s V—measure for correlations on a nominal level. Results vary between 0 and 1. Close to 0 means low correlation and close to 1 means high correlation.
12 In order to compare potential differences of age and amount of education or training in years between the two populations
positive outcomes (F = 762.344, t = 6.076; p < 0.05), with a small-medium correlation effect (d = .50)13, indicating
that innovative and non-innovative entrepreneurs differ in age. This preliminary result suggest that innovative entrepreneurs are younger in comparison to non-innovative entrepreneurs (M = 43.5 vs. M = 44.2 both in age). Additional results regarding the amount of education or training in years, show significant outcomes (F = 2796.542, t = -59.096; p > 0.05), with a high and positive correlation effect (d = .60), indicating that innovative and non-innovative entrepreneurs differ in experienced amount of education or training in years. Results suggest that innovative entrepreneurs have experienced more years of education or training as compared to their adversaries (M = 13.5 vs. M = 11.9).
Fourth, comparing preliminary results of descriptive statistics concerning the five personality constructs of innovative and non-innovative entrepreneurs with only a focus on average scores of both populations (see Table 4), show that first, on neuroticism innovative entrepreneurs score lower as compared to non-innovative entrepreneurs. Second, innovative and non-innovative entrepreneurs have equivalent scores on extraversion. Third, regarding openness to experience, innovative entrepreneurs score higher as compared to their counterparts. Fourth, concerning the personality construct agreeableness, both entrepreneurial populations have equal scores. Last, results reveal that innovative entrepreneurs score higher on conscientiousness.
Table 4 – exploration of mean comparison of the two populations on the personality constructs
N = 20,405 Mean SD Neuroticism (M = 4.19) Non-innovative entrepreneurs 4.24 .87 Innovative entrepreneurs 4.11 .83 Extraversion (M = 4.87) Non-innovative entrepreneurs 4.87 .79 Innovative entrepreneurs 4.88 .75 Openness to experience (M = 4.52) Non-innovative entrepreneurs 4.44 1.19 Innovative entrepreneurs 4.63 1.16 Agreeableness (M = 4.75) Non-innovative entrepreneurs 4.75 .73 Innovative entrepreneurs 4.75 .71 Conscientiousness (M = 4.81) Non-innovative entrepreneurs 4.79 .64 Innovative entrepreneurs 4.85 .61
Note. Descriptive statistics of the average scores for both populations with a focus on average scores. 4.2 MEAN COMPARISON ANALYSES OF PERSONALITY CONSTRUCTS
Results derived from the mean comparison analysis of the five personality constructs show significant results for the personality dimensions; neuroticism (t = 15.664; p < .001), openness to experience (t = -12.647; p < .001) and conscientiousness (t = -10.742; p < .001) (see Table 5).14 These findings suggest that there are differences in these
personality constructs between innovative and non-innovative entrepreneurs. More specifically, innovative entrepreneurs score higher on the constructs openness to experience and conscientiousness, but lower on
13 To make statements about the relevance of results, calculations for correlation effect sizes were conducted to expand the
interpretation of my findings. The analysis used to calculate the effect size is Cohens’ d. If Cohens’ d is close to 0 then there is a small correlation effect and the opposite for a large effect. A negative Cohens’ d indicates a negative correlation effect size. The formula for calculating Cohens’ d is as follows; (M2-M1)⁄ SDpooled
14 A mean comparison analysis is conducted in order to check if there are significant differences in means (M) of personality
neuroticism (see Table 4 for mean differences). However, correlation effect sizes were small; neuroticism (d = .15), openness to experience (d = .16), and conscientiousness (d = .11). With respect to the personality constructs extraversion and agreeableness, results were insignificant (see Table 5). These findings suggest that there is not enough evidence to assume that populations differ on these personality constructs.
Table 5 - mean comparison analyses of the personality constructs (N = 20,405).
F t M difference SE Neuroticism 24.170*** 15.664*** .12965 .00837 Extraversion 42.147*** -.229 -.00174 .00757 Openness to experience 11.805*** -12.647*** -.14590 .01154 Agreeableness 15.927*** .042 .00030 .00703 Conscientiousness 25.834*** -10.742*** -.06574 .00612
Note. Mean comparison analyses of innovative and non-innovative entrepreneurs with respect to the five personality constructs.
* p < .05. Results are significant at the 0.05 level (2-tailed). ** p < .01. Results are significant at the 0.01 level (2-tailed). *** p < .001. Results are significant at the 0.001 level (2-tailed).
4.3 MAIN REGRESSION ANALYSES RESULTS
In order to test the hypotheses associated with this study, single and multiple regression analyses were conducted. For each personality construct a regression analysis is conducted in two models; in model one, a single regression analysis was performed where each personality trait served as dependent variable and being an innovative entrepreneur served as independent variable. In model two, a multiple regression analysis was conducted with the same variables as in model one but in model two the control variables were added.15 For each personality construct,
results of the regression analyses are presented (see Table 6 for an overview).
Neuroticism (H1) (see Appendix - Table 17). Results of model one show that the regression model is highly significant (F = 244.391; p < .001), and that around 6% of the variance can explain being an innovative entrepreneurs’ score on neuroticism (R2 = .06). Subsequently, results show a significant but negative effect (b =
-.133, t =-15.633; p < .001), indicating that innovative entrepreneurs score lower as compared to non-innovative entrepreneurs on this personality construct. Therefore, enough evidence was found to confirm hypothesis 1. Results regarding model two show that the regression model is highly significant (F = 453.166; p < .001), and accordingly, around 10% of the variance explains the score of being an innovative entrepreneur on neuroticism (adjusted R2 = .10). Second, results are equivalent to model one, both presenting a significant but negative effect
(b = -.80, t = -9.155; p < .001), meaning that innovative entrepreneurs score lower as compared to their counterparts. Thus, hypothesis 1 can be confirmed in both models. Assessing the remaining results (Appendix - Table 17 model two), findings suggest that older entrepreneurs score higher and men score lower on neuroticism. At last, regarding the amount of education or training in years results suggest that the more education or training an innovative entrepreneur has experienced, the lower the score on neuroticism.
Extraversion (H2) (see Appendix – Table 18). Results of model one show that the regression model is insignificant (F = .048; p = .827 > .05), meaning that not enough evidence was found to confirm hypothesis 2. Comparing results from model one with model two, the conclusion is that all results were insignificant. First, compared to model one, this regression model is highly significant (F = 169.029; p < .001). However, just 1.5%
of the variance explains the score of being an innovative entrepreneur on extraversion (adjusted R2 = .015). Second,
results show an insignificant but positive effect (b = .011, t = 1.394; p > .05), meaning that in both models, no evidence was found to support hypothesis 2. Assessing the remaining significant results in model two (Appendix - Table 18 model two), findings indicate that younger entrepreneurs are more extravert and entrepreneurial men are less extravert as compared to their counterparts. Furthermore, results imply that the more years of education or training an entrepreneur has experienced, the more extravert they are.
Openness to Experience (H3) (see Appendix – Table 19). Results of model one reveal that model is highly significant (F = 167.158; p < .001), but that just 4% of the variance can explain the score of being an innovative entrepreneur on openness to experience (R2 = .04). Second, results show a significant and positive effect (b = .153,
t = 12.929; p < .001), indicating that innovative entrepreneurs score higher as compared to non-innovative
entrepreneurs on this personality trait. Therefore, results in model one suggests that there is enough evidence to confirm hypothesis 3. Assessing the results of model two, it shows that the regression model is highly significant (F = 381.080; p < .001), and if adding the control variables, 15% of the variance can explain an entrepreneurs’ score on openness to experience (adjusted R2 = .15). Furthermore, results show a significant and positive effect (b
= .31, t = 2.529; p < 0.05), indicating that similar to model one, innovative entrepreneurs score higher on this construct. Thus, in both models’, enough evidence was found to support hypothesis 3. The remaining results (Appendix - Table 19 model two), suggest that older entrepreneurs are less open to experience which is equivalent for men. Subsequently, it appears that more years of education or training an entrepreneur has experienced, the more open to experience entrepreneurs are.
Agreeableness (H4) (see Appendix - Table 20). Results of model one are insignificant (F = .235; p = .682 > .05), indicating that no evidence was found to confirm hypothesis 4. Assessing the results of model two, the regression model seems highly significant (F = 6.452; p < .001), but only 1% of the variance explains an innovative entrepreneurs’ score on this trait when adding the control variables (adjusted R2 = .01). However, model two shows
an insignificant but positive effect (b = .004, t = .490; p > .05), meaning that both models lack the evidence to support hypothesis 4. Assessing the remaining results (Appendix - Table 20 model two), findings suggest that older entrepreneurs are less agreeable, and results for gender were insignificant indicating that no effect was found. Interpreting results related to the amount of education or training in years, findings suggest that the more years entrepreneurs have experienced education or training, the less agreeable entrepreneurs are.
Conscientiousness (H5) (see Appendix - Table 21). Results of model one show that the regression model is highly significant (F = 108.800; p < .001), but that only 9% of the variance can explain an entrepreneurs’ score on conscientiousness (R2 = .09). Subsequently, results reveal a significant and positive effect (b = .066, t = 10.431;
p < .001), indicating that innovative entrepreneurs score higher on conscientiousness as compared to non-innovative entrepreneurs. Thus, enough evidence was found to confirm hypothesis 5. Comparing results of model two with model one, findings indicate that the regression model is highly significant (F = 154.115; p < .001) and adding the control variables results in that 17% of the variance can explain an entrepreneurs’ score on conscientiousness (adjusted R2 = .17). Second, model two notes a significant and positive effect (b = .049, t =
result of men (i.e. are less conscientiousness) in contrary to their adversaries. Concluding, results imply that the more years of education or training an entrepreneur has experienced the more conscientiousness entrepreneurs are. Table 6 – regression analyses results of coefficients for the personality constructs (N = 20,405)
Neuroticism Extraversion Openness Agreeableness Conscientiousness
b b b b b Model 1 Constant 4.25*** 4.88*** 4,47*** 4.75*** 4.79*** Innovative entrepreneurs -.133*** .002 .153*** -.003 .066*** Model 2 Constant 4.65*** 4.97*** 3.77*** 4.85*** 4.89*** Innovative entrepreneurs -.080*** .011 .031* .004 .049*** Age .003*** .002*** -.001** -.001** -.005*** Gender -.244*** -.182*** -.189** .001 .059*** Amount of training or education -.036*** -.008*** 0.72*** -.005*** .009***
Note. Model 1 consist of a single regression analysis with the personality traits as dependent variable and being an innovative
entrepreneur as independent variable.
Model 2 consist of a multiple regression analyses with the same design as model 1, but in this model control variables were
added.
* p < .05. Results are significant at the 0.05 level (2-tailed). ** p < .01. Results are significant at the 0.01 level (2-tailed). *** p < .001. Results are significant at the 0.001 level (2-tailed).
4.4 ADDITIONAL REGRESSION ANALYSES RESULTS
The main objective for this additional probit regression analyses was to test if certain personality traits determine whether a person, or entrepreneur in this case, is innovative or not. It was the intention to not only check for differences in personality traits between innovative and non-innovative entrepreneurs based on a single relationship (i.e. if an innovative entrepreneur has certain personality traits or not), but it is my belief that a reversed perspective would be wise to consider, as it would be very interesting to check if certain personality traits affect occupational choice (i.e. determine if certain personality traits have an positive effect on being or becoming an innovative entrepreneur). An important note, in the previous regression analyses tests consisted of, if an innovative entrepreneur has certain personality traits or not. In these analyses, tests consisted of, if certain personality traits determine whether a person is/becomes innovative or not. For the following analyses the model has been redesigned by replacing the original independent variable with the dependent variable.16 The results of the analyses
have been compared with the regression results in section 4.3.17 For each of the five personality traits the most
important results are being discussed. The results of the control variables have been presented as last.
Neuroticism (H1). Results in Table 7 show that neuroticism has a significant and negative effect on being an innovative entrepreneur (b = -.071, Wald c2 = 85.054; p < .001), indicating that neuroticism does not contribute
to innovativeness. This finding suggest that this personality trait has a negative effect on being an innovative entrepreneur. Subsequently, comparing this result prior to the hypothesis—where is proposed that innovative entrepreneurs score lower on this personality trait, results showed a negative but significant effect for this
16 The dependent variable (each of the five personality traits) was switched with the independent variable (being an innovative
entrepreneur). For the following analyses, the DV is ‘being an innovative entrepreneur’ and the IV is ‘each of the five personality traits + control variables’. The control variables are; age, gender and amount of education or training in years.
hypothesis. Comparing results of this analysis with findings in section 4.3, the conclusion is that all results show a negative effect for neuroticism on being or becoming an innovative entrepreneur. These findings suggest that innovative entrepreneurs are, for instance, emotionally more stable as compared to non-innovative entrepreneur. Table 7 - probit regression analysis results of neuroticism (N = 18,947)
95% Wald Confidence interval
Parameter b SE Lower Upper Wald Chi-Square
(Intercept) -1.545*** .0522 -1.648 -1.443 877.852*** Neuroticism -.071*** .0076 -.086 -.056 85.054*** Age -.004*** .0005 -.005 -.003 57.433*** Gender -.112*** .0129 -.137 -.087 76.002*** Amount of education or training in years .137*** .0024 .133 .142 3275.764***
Note. This probit regression analysis consist of being an innovative entrepreneur as dependent variable and the personality trait combined with the control variables as independent variable.
* p < .05. Results are significant at the 0.05 level (2-tailed). ** p < .01. Results are significant at the 0.01 level (2-tailed). *** p < .001. Results are significant at the 0.001 level (2-tailed).
Extraversion (H2). Results in Table 8 reveal that extraversion has a positive but insignificant effect on being an innovative entrepreneur (b = .013, Wald c2 = 2.541; p = .111 > .05), meaning that extraversion has no effect on
being an innovative entrepreneur. Comparing this result prior to the hypothesis—where is proposed that innovative entrepreneurs score higher as opposed to their counterparts on this personality trait, all results were insignificant. Comparing this result with results in section 4.3, the conclusion is that extraversion has no effect on being or becoming an innovative entrepreneur and further implications cannot be provided at this point.
Table 8 - probit regression analysis results of extraversion (N = 18,975)
95% Wald Confidence interval
Parameter b SE Lower Upper Wald Chi-Square
(Intercept) -1.936*** .0563 -2.047 -1.826 1183.380*** Extraversion .013 .0082 -.003 .029 2.541 Age -.004*** .0005 -.005 -.003 64.735*** Gender -.092*** .0128 -.118 -.067 52.118*** Amount of education or training in years .140*** .0024 .135 .145 3449.607***
Note. This probit regression analysis consist of being an innovative entrepreneur as dependent variable and the personality trait combined with the control variables as independent variable.
* p < .05. Results are significant at the 0.05 level (2-tailed). ** p < .01. Results are significant at the 0.01 level (2-tailed). *** p < .001. Results are significant at the 0.001 level (2-tailed).
Openness to Experience (H3). Table 9 shows that openness to experience has a positive and significant effect (b = .015, Wald c2 = 7.663; p < .01), which indicates that this personality trait has a positive effect on being an
