Entrepreneurs and attractiveness to the other sex

Master Thesis Entrepreneurship

Entrepreneurs and attractiveness to the

other sex

Jana Saljic

Study: Joint Master Entrepreneurship program

University: University of Amsterdam and VU University

Student number: 11376163

3 The copyright rests with the author. The author is solely responsible for the content of the thesis, including mistakes. The university cannot be held liable for the content of the author’s thesis.

Abstract

The goal of this study was to generalize last year studies on whether attractiveness is influenced by entrepreneurial status by conducting a similar study in another country, namely Croatia. Models carrying one of five possible employment statuses (entrepreneur, starting entrepreneur, employee in public sector, employee in private sector, and unknown employment status) were rated in terms of general attractiveness, attractiveness as a dating partner, and attractiveness as a relationship partner. Our findings did not confirm that women or men preferred entrepreneurs, both in general and when judging as short-term or long-term partners. No significant difference was found between the ratings of the models and the employment statuses. In the discussion I speculate why the Dutch results were not produced in Croatia.

4 Table of contents 1. Introduction ... 6 1.1. Background ... 6 1.2. Research question ... 7 1.2. Relevance ... 8 1.3. Outline thesis ... 9 2. Theory ... 10 2.1. Evolutionary theory ... 10 2.2. Evolutionary psychology ... 11

2.3. Human sex and mating ... 12

2.4. Physical attractiveness ... 13

2.5. Non-physical attractiveness ... 14

2.6. Mate preferences ... 15

2.6.1. Short-term mating ... 16

2.6.2. Long-term mating ... 17

2.7. Perception by the public of work-related statuses ... 18

2.7.1. Perception of entrepreneurs ... 18

2.7.2. Entrepreneurship-based differences in Croatia and the Netherlands ... 19

2.7.3. Public perceptions of employees ... 21

2.8. Hypotheses ... 22

3. Method ... 24

3.1. Research design ... 24

3.2. Sampling and data collection ... 25

3.1. Experimental procedure ... 27

3.2. Stimuli ... 28

3.3. Measures ... 29

3.4. Data analysis ... 30

4. Results ... 31

4.1. Male ratings of female models ... 31

4.2. Female ratings of male models ... 33

4.3. Comparison between Croatia and the Netherlands ... 34

4.4. Control and explanatory variables ... 36

5. Discussion ... 39

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5.2. Limitations ... 41

5.3. Recommendations for future research ... 42

6. Conclusion ... 43

References ... 44

Appendix ... 53

Table 1. Distribution to age and gender within sample ... 26

Table 2. Control variables ... 27

Table 3. Means, standard deviations, and number of observations according to groups ... 31

Table 4. Descriptive statistics for general attractiveness of female models ... 32

Table 5. One-way ANOVA general attractiveness of female models ... 32

Table 6. Descriptive statistics for general attractiveness of male models ... 33

Table 7. One-way ANOVA general attractiveness of male models ... 34

Table 8. Independent samples test ‘ratings of male entrepreneurs - Croatian vs. Dutch women aged 20-29’ ... 35

Table 9. Independent samples test ‘ratings of male entrepreneurs – younger (20-29) Croatian women vs. older women (30-39)’ ... 36

Table 10. Paired Samples Test – Explanatory variables ... 37

Table 11. Regression analysis ‘effect of control variables on attractiveness ratings’ ... 38

Figure 1: Theoretical model ... 10

Figure 2. Research design ... 25

6 Figure 1: Theoretical model ... 10 Figure 2. Research design ... 25 Figure 3. Example stimuli and measures ... 29

1. Introduction

What makes a person attractive? A vast literature exists based on physical and non-physical characteristics that make a person attractive. One of the non-physical aspects that we are researching is entrepreneurial status to investigate whether the entrepreneurial status actually affects someone’s attractiveness. Entrepreneurial characteristics are positively viewed in the world. Being your own boss, having control, taking risks, having high social status, are all deemed as attractive characteristics. Perceptions of entrepreneurs are becoming more and more positive in the world, especially because it is considered to have influence on the economic development, in creating jobs, and supporting innovation (Van Praag & Versloot, 2007). Thus, it is likely that being an entrepreneur leads to enhanced attractictiveness to the other sex, although this may apply more to male entrepreneurs than to female ones.

Psychology literature states that women often prefer men’s socioeconomic status, willingness and ability of investing resources in a relationship than their physical attractiveness because one outweighs the other (Trivers, 1972). Males’ preferences, on the other hand, are mostly guided by physical attractiveness (Buss, 1989).

In this thesis, I conduct a replication study of master theses done in Netherlands by Borst (2016) and Wazir (2016). They found that male entrepreneurs were rated as more attractive than non-entrepreneurs. These results, however, may depend on local context, because the associations that people have with employment related statuses such as entrepreneur, starting entrepreneur and employee may vary from one culture or country to the next. I aim to confirm their findings in another country, Croatia and to compare the results. If the findings confirm male entrepreneurs get higher attractiveness ratings, then we can consider it as a new motivation to become entrepreneur.

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1.2. Research question

As we mentioned previously, attractiveness has been studied in fields of psychology for a long time. However, the impact of entrepreneurial status on someone’s attractiveness has not been researched almost at all. Thus, we investigated if individuals become more attractive if they become an entrepreneur because there are certain qualities linked to entrepreneurs which might increase their attractiveness. This in turn might increase the motivation to become entrepreneur.

Regarding the entrepreneurial motivation, identification of opportunities is ubiquitously in the center of entrepreneurial research. Individual’s personality traits, prior knowledge and social networks are recognized as antecedents to discovering opportunities, which might affect individual’s motivation to become an entrepreneur (Ardichvili et al., 2003). Highly associated personality dimensions with entrepreneurship are self-efficacy and need for achievement, amongst others (Frese & Gielnik, 2014). One of the motivations to become entrepreneur is that it provides autonomy which also might steer individuals into entrepreneurship (Van Gelderen, 2016). Furthermore, entrepreneurial motivation could also be non-pecuniary benefits, and preferences for control (Astebro et.al, 2014).

It is important to mention that entrepreneurial motivation and decision-making processes can greatly differ between men and women because they use different types and different amounts of heuristics or biases (Plous, 1993). As Tversky and Kahneman (1982) stated,

different individuals will see the same risk situation in quite different ways.

However, besides the differences in the decision-making, gender stereotypes have been a long-time issue in entrepreneurship. For example, one of the main issues is representation of entrepreneurship as a masculine activity with connotations of leadership and dominance, especially in modern cultures (Bruni et.al, 2004; Mirchandani, 1999; Thebaud, 2010). Yet, women who display these traits are often penalized for being insufficiently feminine. Therefore, women who become entrepreneurs violate stereotypes about feminine behaviour because they are expected to be kind, while men fulfill the stereotype that they should be risk-takers (Heilman, 2001; Rudman and Glick, 2001; Thebaud, 2010). Thus, the representation of men and women in entrepreneurial activities is not equal, and those stereotypes greatly affect men’s higher motivation to become entrepreneur, compared to women.

Two Dutch master theses established that there is a link between entrepreneurs and attractiveness of human beings. In order to ascertain whether these relations also hold in a

8 different culture, this research is based in Croatia, where we aim to answer the following research question and sub-questions:

1. How does the entrepreneurial status affect the attractiveness to the other sex?

1.a) How does the entrepreneurial status affect the attractiveness of an individual of opposite

sex as a short-term partner?

1.b) How does the entrepreneurial status affect the attractiveness of an individual of opposite

sex as a long-term partner?

Attractiveness to the same sex is beyond the scope of this research so we will investigate only attractiveness to the opposite sex.

1.2. Relevance

The scientific relevance of this thesis is both psychology and entrepreneurship. Many studies thus far have researched physical attractiveness and its factors. However, there has been few studies researching non-physical factors to attractiveness. No published journal article included entrepreneurial status. For example, Dunn and Searle (2010) used luxury cars to attain attractiveness ratings, while Dunn and Hill (2014) used luxury apartments. The only known research about the effect of entrepreneurial status on attractiveness was a master thesis by Borst (2016) and Wazir (2016) which I now replicate in another country. The power of replication is widely discussed in Davidsson’s book (2005). Replications are used to confirm or question someone else’s findings. Replications increase external validity and thus, we researched if we can make inferences of generalizations across populations (e.g. comparing Croatia to Netherlands). We will contribute to the literature of entrepreneurship by exploring possible motives for starting a business. There may be repercussions for economic performance depending on whether the attractiveness motive is dominant or supplementary (Van Gelderen et al., 2017). If dominant, some entrepreneurs may not be willing to put in the real work while simply enhancing their own attractiveness. If the attractiveness motive is more supplementary, it can stimulate entrepreneurship. Those individuals and their ambitions are fueled by a need for admiration. Also, this study will contribute to social psychology literature by exploring entrepreneurial status and employment status in general, as a non-physical characteristic to attractiveness.

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1.3. Outline thesis

This thesis consists of 6 sections. The first section presented the introduction of the thesis. In second section, relevant theory concerning the topic will be presented: evolutionary theory,

evolutionary psychology, human sex and mating, physical and non-physical attractiveness, mate preferences, perceptions of entrepreneurs, and main hypotheses respectively. Third

section describes the methodology used for testing the hypotheses. Section four will present the analysis and the results of the research followed by the discussion and conclusion.

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2. Theory

Before we introduce the relevant literature, we present our theoretical model of the study below. Entrepreneurial status is expected to influence non-physical characteristics to human attractiveness, such as one’s social status and personality characteristics. Human attractiveness can be further divided into three main categories: general attractiveness, attractiveness as a short-term partner, and attractiveness as a long-term partner.

Figure 1: Theoretical model

In order to understand how males and females assess work-related statuses in terms of their generic, short-term and long-term attractiveness, we employ theories of evolutionary psychology, an outgrowth of evolutionary theory.

2.1. Evolutionary theory

Darwin was the first to develop the theory of natural selection in his famous book On the Origin of Species (1859). In this book he defined three essential elements that allow natural selection to operate: inheritance, variation, and differential reproductive success. Differential reproductive success is defined as the reproductive success relative to others. All species have similar characteristics, but there is a slight variation in these characteristics within the species. Only the characteristics that are inherited play a role in evolution. The organisms that have the characteristics of adaptation, best fit to survive and reproduce in their current environment, have most reproductive success and thereby more success in passing on their characteristics. More importantly for this research, Darwin also introduced the theory of sexual selection besides the theory of natural selection. For this theory he proposed two essential elements that allow it to operate: intra-sexual competition and inter-sexual competition. In intra-sexual

11 competition, organisms from the same species compete with each other in order to mate with the other sex. The characteristics that lead to success in this competition are the characteristics likely to be passed on to the next generation. In inter-sexual competition, the characteristics that are most valued by the other sex are selected for as this allows easier mating and thus reproduction. Darwin noted that mostly females were picky in this matter.

Bateman's principle (1948) explains the conditions determining which sex becomes the more limited resource in intersexual selection. The principle states that the more investing sex in producing offspring becomes a limiting resource over which the other sex competes. For example, males could theoretically become a father every day whereas females can only give birth every ten months.

In order to understand why males and females perceive attractiveness in the way that they do, we proceed with the theories of evolutionary psychology.

2.2. Evolutionary psychology

Evolutionary psychology stems from evolutionary theory and is focused on how evolution has shaped the mind and behavior (Science daily, 2017). In evolutionary psychology theories, it is argued that much of human behaviour is the outcome of psychological adaptations that evolved to solve recurrent problems in human ancestral environments (Buss, 2005; Tooby & Cosmides, 2005; Gangestad & Simpson, 2016). Adaptations are considered to be systems or mechanisms of properties “designed” by natural selection to solve the specific problems in environments which have been encountered by ancestors during the course of evolution (Tooby & Cosmides, 1990). Many adaptive problems are complex thus they require complex adaptations to solve them. Furthermore, many genes are required to control the development of complex adaptations whereas sexual recombination also plays a big part to impose necessary genes together in the same individual.

Evolutionary psychology theories suggest that attractiveness is an assessment of fitness value, which includes health, strength, fecundity, mate quality, reproductive value, and the ability to invest in children (Buss, 2015; Honekopp et al., 2007; Singh, 2002). Markers of fitness value differ for males and females.

The field of evolutionary psychology includes human sex and mating which investigates how humans evolved psychological adaptations in the context of mating. For

12 example, mate selection, parental investment, and sexual strategies are particularly important for our research.

2.3. Human sex and mating

One of the basic theories for many ideas about sex and mating is the parental investment theory developed by Trivers (1972). He argued that parental investment affects sexual selection. The sex which invests the most in children will be more selective in their choice for a partner to avoid unnecessary costs, while others will compete between each other in order to mate with the selective sex. Parental investment can be split into two main categories: mating investment and rearing investment. The sexual act and the sex cells invested are components of the mating investment. The rearing investment is the time and energy expended to raise the offspring after conception. Women's parental investment substantially surpasses that of the male. Each intercourse may result in a nine-month commitment for the woman, while male can leave after the intercourse and focus their reproductive efforts elsewhere. In fact, males often compete for sexual access to women who invest more and are crucial for the reproductive success of their offspring because they are considered to be a valuable resource for men. However, if the male does invest in the child in the long-term scenario, there is a risk of investing resources in a child that is not biological offspring (Buss, 1996; Anderson, 2006; Gilding, 2009).

Two major evolutionary perspectives in this field are sexual strategies theory by Buss & Schmitt (1993) and strategic pluralism theory by Gangestad & Simpson (2000).

Drawing on Trivers' (1972) parental investment theory, Buss and Schmitt (1993) proposed sexual strategies theory in which humans use different strategies when it comes to mating. In sexual strategies theory, women may increase their options for long-term mates by being open to short-term relationships (Li & Kendrick, 2006; Buss & Schmitt, 1993). Li et al. (2002) have also pointed out that if women used short-term mating to evaluate potential long-term relationships, then it is expected of women to prioritize the same traits in short-long-term and long-term relationships such as social status, resources, and kindness. Besides these traits, it is expected that physical attractiveness will be treated as more of a luxury (Li & Kendrick, 2006). Physical attractiveness is a necessity to men, status and resources are necessities to women, while kindness and intelligence are necessities to both (Li et al., 2002). However, their study supported the good genes argument of strategic pluralism theory (Gangestad & Simpson, 2000). In good genes theory, females appear to select males whom they perceive to

13 have genetic advantages that would increase quality of their offspring. This means that male physical attractiveness is seen as a marker of ability to protect and provide (Buss & Shackelford, 2008).

The strategic pluralism theory was developed when researchers found a connection between men whom women are physically attracted to and men's masculinity and symmetry (Li & Kendrick, 2006; Thornhill & Gangestad, 1994). Furthermore, their results suggested that in short-term relationships women may be seeking good genes, which is in line with strategic pluralism theory. The theory proposed that the strategies differ according to the environmental conditions. Such variation accounts for a range of mate preferences and strategies which are employed by both sexes and leads to women competing for men as well as vice versa (Gangestad & Simpson, 2000).

Modern humans inherited the strategies of mating that affected our ancestor's success. Except long-term and short-term mating, some of those strategies include extra-pair mating (e.g., infidelity), mate poaching, and mate guarding (Buss, 2007). Through history, different adaptive problems in mating field were confronted by men and women, and thus the sexes differ tremendously in psychology of mating solutions.

In the next two chapters we will focus on physical and non-physical characteristics that influence attractiveness of the opposite sex. Since we do not study the effects of physical characteristics, the chapter of physical attractiveness will be briefly presented.

2.4. Physical attractiveness

Physical characteristics of men and women influence attractiveness and their selection in potential partners. Two most important dimensions of physical attributes are the human body and face. Evolutionary psychology theories suggest that facial traits that are commonly found to be appealing are cues of mate quality and good genes. Important facial features such as facial symmetry and facial averageness are considered to be related to an individual's attractiveness. Facial averageness and symmetry are considered to be features that indicate parasite resistance and those individuals are judged to be more attractive (Thornhill & Gangestad, 1993). Yet, Thornhill and Grammer (1999) pointed out the evidence that suggests that face and body collectively signal health and other associated variables which in the end determine sexual attractiveness.

14 Evolutionary psychology considers health and reproductive potential as a base for woman's sexual attractiveness. Reproductive value is associated with youth (Thornhill & Gangestad, 2006). Whereas, perceived female body attractiveness is connected with body fat distributions (Singh, 1993). One measure of body fat distribution called waist-to-hips ratio (WHR) correlates with youthfulness, reproductive potential, and long-term health risk in women. However, Tovée et al. (1999) show that the primary determinant of sexual attractiveness is body mass index (BMI) rather than WHR.

Previously underappreciated role in women's mate choices is male physical attractiveness. For example, women rated muscular men as sexier, more physically dominant, but less committed to their partners than non-muscular men (Frederick & Haselton, 2007). When men are healthy and possess higher testosterone levels, they develop more masculine faces (Symons, 1995). In good genes theory, women will select men whom they perceive to have genetic advantages that would increase their offspring quality, and male physical attractiveness is seen as a marker of ability to protect and provide (Buss & Shackelford, 2008).

Men find beautiful what is associated with fertility, without realizing the origin of their preferences, while women put higher emphasis on the non-physical characteristics which are presented below.

2.5. Non-physical attractiveness

From Trivers' parental investment model, Feingold (1992) derived evolutionary-related hypotheses about gender differences in mate selection preferences. Firstly, women are more likely to seek a mate of higher socioeconomic status who possesses non-physical characteristics that influence reproductive aspects. Secondly, most important cues to resource acquisition are ambitiousness, character and intelligence. Gender differences in preferences such as personality, or sense of humor, were not found.

Buss (1988) conducted studies based on Darwin's theory of sexual selection that suggests that individuals compete for opposite sex's relevant reproductive resources with individuals of their own sex. The research concluded that men and women have different reproductive strategies, by differing on which reproductively relevant resources they need from a potential partner. One male reproductive strategy is to ensure gene replication and therefore to attempt to mate with as many females as possible (Mealey et al., 1999; Buss, 1988; Buss & Schmitt, 1993; Townsend, 1989).

15 Women and men rate potential partners' physical attractiveness and socioeconomic status differently. In a study conducted by Townsend and Levy (1990), models' attire status had bigger effects on woman's willingness to enter a relationship than on men's. Men preferred physical attractiveness of the model more than socioeconomic status. This is consistent with the parental investment theory which says that men's socioeconomic status, willingness and ability of investing resources in a relationship could often outweigh the effects of their physical attractiveness in women's real selection of possible partners.

2.6. Mate preferences

Characteristics that influence mate choice may vary in short-term and long-term strategies. However, both will be included in this section. There are similarities in characteristics that both genders prefer although there are many differences as well (Buss et al., 1990). The shared mate preferences include finding a committed mate and identifying mates with good parenting skills (Buss and Schmitt, 1993). One study also found shared mate preferences such as love, kindness and pleasing disposition (Khallad, 2005).

Furthermore, effects of culture and sex on mate preferences have been researched in more than 30 countries. The most varied mate characteristic in cultures was found to be chastity, for both sexes. Some similarities among cultures were education, intelligence, and refinement. More importantly, effects of sex on mate preferences were small compared to the effects of culture (Buss et al., 1990). That means that the most relevant characteristics in mate selection are considered to be resource provision for women, and reproductive value for men. Women also preferred mates who were higher in income, education, intelligence and social status than themselves (Buunk et al., 2002).

Females were found to value the financial capacity and resource acquisition more than males do. However, males were found to value the signals of reproductive capacity, physical attractiveness and relative youth in potential mates (Buss, 1989). Women display greater preferences for attributes such as resources and commitment while being less concerned with physical appearance. Even though women did not prefer traits linked with mate's material wealth, wealthier women or with a higher social status do prefer mates with higher socioeconomic status (Todosijevic et al., 2003; Khallad 2005). Despite the fact women today are more educated and more independent, they still tend to prefer males with high social status and resources (Dunn & Hill, 2014; Dunn & Searle 2010).

16 When rating someone's attractiveness, men find females as more attractive when their physical appearance is high. However, drawing attention to physique produces overall enhancement of attractiveness when considering a mate as a sexual partner, but decreases for a marital partner (Hill et al., 1987). In the study, by manipulating physique display, researchers came to conclusions that men emphasized physical appearance more than status display while women emphasized higher status. The female attraction to the higher status than physique would be predicted in social systems where women depend upon men for financial and material security.

2.6.1. Short-term mating

Buss and Schmitt (1993) pointed out how men's and women's preferences in mate selection are highly sensitive to temporal contextual conditions. For example, in short-term mating as opposed to long-term mating, they approach different contextually sensitive adaptive problems which include sexual accessibility, fertility assessment, commitment seeking and avoidance, resource procurement, assessment of mate value, and parental investment. There are more similarities in preferences for short-term relationships between sexes. However, they do differ in whether they would enter such short-term sexual relationships.

Different involvement levels had to be considered when assessing criteria for mate selection. The lower the levels of relationship involvement, the lower were the preferences for a potential mate. Men preferred mates who were highly physically attractive, whereas women preferred mates who were higher in income, education, intelligence and social status than themselves. When the relationship involvement was lowered, the lower were the preferences for education, intelligence and physical attractiveness (Buunk et al., 2002). Also, they pointed out that older individuals have higher standards for mate's education. On the other hand, women prioritized short-term physical attractiveness as a necessity and not as a luxury, which is in line with the good-genes account of strategic pluralism theory (Li & Kendrick, 2006).

According to proponents of evolutionary psychology theories, men value physical attractiveness of women with the focus in particular on the body for the short-term relationships (Buss, 2015; Confer et al., 2010). Good genes were mostly favored when entering a short-term relationship (Li & Kendrick, 2006). One male reproductive strategy is to ensure gene replication and therefore to attempt to mate with as many females as possible (Mealey et al., 1999; Buss, 1988; Buss & Schmitt, 1993; Townsend, 1989). The researchers

17 suggested the devaluing mechanism which is a mechanism that would allow men to be less picky about potential partners, but only when considering short-term relationships.

Recent research suggests that men with genetically beneficial features for their offspring are preferred by women as short-term partners however, there are tradeoffs between a mate's genetic physique and his willingness to help raise a child (Gangestad & Simpson, 2000).

2.6.2. Long-term mating

Evolutionary psychology theories suggest that women have a huge obligatory parental investment to produce children as they are the bearers of babies, thus they have inherited the evolutionary trait to select long-term partners who can give them material benefits and to exclude those who make her incur costs. The selection tends to males with resources and the potential to acquire resources in order to share them with her and their children (Buss 2008; 2015).

The tradeoffs between a mate's genetic physique and his willingness to help raise a child means that if the local environment was difficult and demanded biparental care, women accentuated investment potential of their future mates more than their genetic fitness. Because of this demand, larger proportion of women adopts long-term mating strategy almost immediately (Gangestad & Simpson, 2000).

In long-term mates, women prioritized status, whereas men prioritized physical attractiveness (Li & Kendrick, 2006). However, with enough freedom of choice, both sexes tend to go for well-rounded mates at some point.

Personality factors become critical if a male-female pairing leads to long-term relationships such as marriage (Singh, 1993). Those are usually culturally biased, for example religious affiliation, sense of humor, compatibility etc. Yet, men's and women's choice for long-term mates have been noted as very similar, in contrast to their differences in short-term mating. Long-term partners put much more emphasis on obtaining a partner who is similar to themselves (Kenrick et al., 1990; 1993).

The preferences and priorities of both sexes in short and long-term partners have been put forward. We are interested if entrepreneurs fit these characteristics which would make him or her more attractive than the average person. In order to examine if employment status

18 affects attractiveness, the next section will elaborate on the employment status’ characteristics.

2.7. Perception by the public of work-related statuses

When asking people to rate the attractiveness of models who carry different work-related statuses, it is important to know what associations they may have with statuses such as entrepreneur, starting entrepreneur and employee. This section will focus on perceptions of entrepreneurs and employees in general, and on Croatia in particular. Apart from the public perception of entrepreneurs, perceptions of employees will be discussed as well since there is a bigger difference between public and private sector in Croatia than in the Netherlands (Eurostat, 2016). It is important to note that according to Eurobarometer (2014), 46% of respondents believed that employment situation in Croatia will be even worse in the next few months.

2.7.1. Perception of entrepreneurs

Entrepreneurs are thought to have a unique presence in society which is shaped by cultural norms and expectations (Anderson & Warren, 2011). Entrepreneurs are repeatedly perceived as risk-takers, achievers, dominant, and confident (Baron et al., 2001).

Long-time issue in entrepreneurship is its representation as a masculine activity with connotations of leadership and dominance, especially in modern capitalist cultures (Gupta & Fernandez, 2009; Bruni et al., 2004; Mirchandani, 1999; Thebaud, 2010). Due to gender stereotypes, such as men being more dominant and risk-taking, women who display these traits are often penalized for being insufficiently feminine. Therefore, women who become entrepreneurs violate stereotypes about feminine behaviour because they are expected to be kind, while men fulfill the stereotype that they should be risk-takers (Heilman, 2001; Rudman and Glick, 2001; Thebaud, 2010). Being an entrepreneur is viewed as a more exciting or adventurous occupation than for example being a manager, and thus describing strangers as entrepreneurs generates higher positive effect. On the other hand, when women are described as entrepreneurs, it simultaneously raises their attractiveness while decreasing their perceived femininity (Baron et al., 2001).

Different individuals have different motivations to enter the entrepreneurial field. According to Alstete (2002), several reasons why individuals would consider

19 founding a business. Entrepreneurs also tend to be less risk averse, benefit from

non-pecuniary benefits, and have preferences for control (Astebro et.al, 2014). Entrepreneurs are seen as risk-takers, as more independent and driven, with a higher need for achievement and control. Those motivations are considered to influence opportunity recognition, idea

development, and execution (Shane et al., 2003).

Autonomy is one of the most common reasons for people to start their own business (Van Gelderen, 2016). Having autonomy usually means having decisional freedom in a venture. Entrepreneurship can provide autonomy and this could be a motivation for people to become an entrepreneur (Van Gelderen, 2016).

2.7.2. Entrepreneurship-based differences in Croatia and the Netherlands The study was performed in Croatia partly due to convenience as the author of the thesis is from Croatia. Secondly, it is assumed that Croatia’s history and culture are distinct, particularly the history of socialism followed by war, and newly introduced capitalism with weaknesses and issues in economic development. All of these conditions make it likely that public perceptions of entrepreneur and employee status differ from the Netherlands.

The meaning of autonomy may differ in developed and developing countries given that Croatia and the Netherlands have differences in history, culture, institutions, and economic and business development (GEM, 2016; GCR, 2016-2017). This could be a complication when comparing different countries in terms of entrepreneurship related parameters. In Western economies, entrepreneurship is facilitated by laws that apply to all and are enforced by an independent judiciary (Van Gelderen et al., 2017). By contrast, Croatia has inefficient government bureaucracy, burden of government regulation, poor protection of property rights, weak capital market institutions, corrupt law enforcement and judicial systems, policy instability, and low protection of minority shareholders’ interests (Global Competitiveness Report 2016-2017). According to the report, Croatia is ranked 89th out of 138 countries in terms of the level of institutional development, while Netherlands is ranked 11th. The level of institutional development influences the way companies operate and thus a well-developed system of intellectual property rights protection is important for firms to participate in innovative activities (Van Gelderen et al., 2017).

Government policies and programs greatly affect Croatia's entrepreneurial environment (Singer, 2007). As a result, entrepreneurial environment in Croatia is more

20 constraining than stimulating (GEM, 2016). Regarding the speed and ease of regulatory functioning of government policies, Croatia is the lowest ranking country in the EU (GEM, 2016).

After few years of decrease in perceived opportunities, there was 24.6% of individuals who perceived business opportunities in 2016, according to GEM. However, it is still not good enough to move upward from the back of the list, suggesting a very slow return to business optimism. At the same time, Croatia is at the top of the EU on its stated entrepreneurial intentions (18.2%), suggesting greater participation in the emergence of business ventures out of necessity, not due to the observed opportunity.

According to GEM (2016), the opinion of most respondents in Croatia is that successful entrepreneurs do not have a high social status (less than 45.6%) - as such, Croatia is at the last place in the EU in the last analyzed period, and at the back of the list by the media attention given to entrepreneurship. In comparison, 60.2% of respondents in Netherlands agree that entrepreneurs have high social status. The largest number of respondents who consider entrepreneurship a good career choice is in the Netherlands (about 79%).

It should be noted that nearly two thirds (62.2% in 2016) of respondents have a positive attitude on entrepreneurial careers (and therefore Croatia is above the EU average) and that one fifth of the respondents indicate intent to launch a business venture (again above the EU average) but this has not been followed by opinions about social status, as well by media attention to entrepreneurship, which endangers the capacity of entrepreneurial activity.

Most entrepreneurially active age groups is 25-34, followed by 35-44, while there is significantly less entrepreneurially active people in age groups 18-24 and 55-64 , Which is similar to the distribution of early entrepreneurial activity by age groups in the EU. Between 2014 and 2016, the participation of the young population (aged 18-34 years) in entrepreneurial activities is stable at around 45% after a steady decline in the previous years, and in 2016 was somewhat above average for EU countries covered by GEM research.

There is still a lot more men than women participating in entrepreneurial activities in 2016, measured by TEA index which was 11.2% for men, and 5.6% for women. However, the results of research change immensely over the years. The TEA indexes in 2015 implied extremely low participation of women aged 25-34 compared to women aged 35-44. Yet, in

21 2016 participation of women aged 25-34 came very close to the participation of women aged 35-44.

In contrast to Croatia, the Netherlands is in the top five countries that support female high-growth entrepreneurs. According to Female Entrepreneurship Index (2015), the Netherlands scored 69.3, whereas Croatia scored 49.9, which means that the conditions are much better in Netherlands for women who want to become entrepreneurs. Furthermore, according to Hofstede cultural dimensions, Croatia scores higher than Netherlands on power distance (73 vs. 38), masculinity (40 vs. 14), and uncertainty avoidance (80 vs. 53), and lower on individualism (33 vs. 80), indulgence (33 vs. 68), and long-term orientation (58 vs. 67).

After a long period of global crisis, the conflicting results and differing perceptions over the years in Croatia might add to the point that under difficult circumstances such as poverty or social crisis, entrepreneurship is faced with envy, suspicion and mistrust among entrepreneurs (Glas et al., 2000). All these differences make it hard to assess if entrepreneurial status will have an effect on perceived male attractiveness in Croatia, and thus hypothesis will be based off of the results in Netherlands, and previous literature.

2.7.3. Public perceptions of employees

As previously mentioned, distinction between employees in private and public sector was made because we presume that there might be bigger differences between the sectors in Croatia than in Netherlands. However, there was no research found on the public perceptions of employees in private and public sector in Croatia or Netherlands.

Usually considered advantages of working in public sector are job security, benefits, and it is often harder to be fired from a public job than one in the private sector. Disadvantages to working in public sector are the lower salaries. On average, the salaries offered in the public sector are not as high as those offered in the private sector. Also, there are many entry-level positions available, but it can be more difficult to work your way up the corporate ladder (Employment Crossing, 2017).

On the other hand, there are more opportunities in the private sector, and the quality of life in Croatia is presumed to be higher in private sector than in the public sector (Employment Crossing, 2017; Džeba, 2011).

22 Research by Budak (2007) claimed that the number of public administration employees was increasing because of an attractive opportunity to make an additional earning from corruption activities. Nepotism in employment additionally reduces the efficiency of the public administration since the competence of its employees declines. Croatian citizens rated the level of the presence of corruption in Croatia as high, and the perception of corruption prevalence had increased. This is important for our research because Croatia was recently named as the most corrupted country in Southeast Europe (Slobodna Dalmacija, 2017). Thus, the prevalence of corruption might increase the favoritism towards employment in the public sector, and possibly increase perceptions of attractiveness towards employees in the public sector.

Apart from corruption, perceptions of self-employment might add to the possibility of preferring employees rather than entrepreneurs. Eurobarometer (2012) shows that Croatians are afraid of the red tape that self-employment entails, and 13% of respondents say that they lack the skills to be employed. Even though the most respondents in Croatia favor self-employment, they believe self-employment is not feasible, and that the current economic climate is not conducive to becoming self-employed.

2.8. Hypotheses

I now form the hypotheses based on the literature on physical and non-physical attractiveness, short-term and long-term preferences, and on the perceptions by the public of entrepreneurs and employees. Both sexes differ in characteristics they prefer based on attractiveness factor and the relationship duration factor. Men judge women's attractiveness more on physical characteristics, such as the face and body shape. However, in certain instances when thinking about long-term relationships, men also pay attention to other personality characteristics. Therefore, it is not expected that the entrepreneurial status will affect the general attractiveness of women. Men prefer physical attractiveness, reproductive potential, and youth in potential mates more than their status (Buss 1989). Thus, the first hypothesis is formulated:

H1a: The entrepreneurial status will have no effect on the general attractiveness of females.

Women place more emphasis on higher socioeconomic status, higher financial capacity, risk-taking, and commitment, but they place less emphasis on the physical appearance of men (Todosijevic et al., 2003). These features are as well connected to the perception of entrepreneurs. Conflicting and changing perceptions in Croatia hinders the

23 ability to presume if the results will differ from the Dutch data. Therefore, it is expected that the entrepreneurial status will affect the general attractiveness of men. Thus, the second hypothesis is formulated:

H1b: The entrepreneurial status will positively affect the general attractiveness of males. Due to larger differences between public and private sector in Croatia, perceived attractiveness of male employees might differ. Benefits of public sector could outweigh the benefits in private sector in Croatia, mostly due to corruption. Because of these benefits of public sector in Croatia, and considering the perception of entrepreneurs, the hypothesis 2.a is formulated:

H2a: Attractiveness of male employees in public sector will be higher than the attractiveness of male employees in private sector.

We also predict the ratings of the attractiveness to be in the following order:

Generic/to date: 1. Entrepreneur, 2. Employee public sector, 3. Employee private sector/Starting entrepreneur, 4. Unknown employment status.

For a relationship: 1. Entrepreneur/Employee public sector, 2. Employee private sector/Starting entrepreneur, 3. Unknown employment status.

Entrepreneurial environment in Croatia is more constraining than stimulating, with a lower degree of young women (18-34) participating in entrepreneurial activities, compared to older women (35-44) and men. On the other hand, in the Netherlands entrepreneurship is seen as a positive force in society and thus may appear as more attractive. Therefore, the third hypothesis is formulated:

H3: General attractiveness of male entrepreneurs will be lower in Croatia in comparison to Netherlands, when rated by younger women.

Considering the results of research in Netherlands, where entrepreneurship is highly supported among men and women, we expect the overall attractiveness of male entrepreneurs to be higher than in Croatia, when rated by younger women (20-29).

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3. Method

3.1. Research design

To determine whether entrepreneurial status influences the attractiveness of an individual we combined the disciplines of psychology and entrepreneurship. As mentioned previously, the subject of attractiveness has been researched for quite some time. Although associating entrepreneurial status with attractiveness is a relatively new endeavor, comparable studies have regularly been conducted in evolutionary psychology. For this research, quantitative approach is more appropriate according to Edmondson and McManus (2007).

We conducted an experiment in order to answer our research question. Experiments have many advantages such as ability to establish causality, cost effectiveness and convenience, but most importantly for this thesis is that it allows replication (Blumberg, Cooper & Schindler, 2011). Replications should be focused on poorly understood phenomena, such as perceived attractiveness of entrepreneurs. Replications should make sure the studies are as similar as possible however, this study is conducted in Croatia and one status was additionally added. Therefore we classified it as a generalization and extension study (Tsang & Kwan, 1999). Such studies in social sciences are important as a result of increased pressure to show the reliability and contextual nature of its findings (Welter, 2011; Miller & Bamberger, 2016).

Participants of the experiment were asked to rate the attractiveness of the faces of the opposite sex in their own age group (20-29 or 30-39). This range was chosen because the need to find a partner and mating are most pronounced around this age. Furthermore, people in these age groups start the most ventures (Van Gelderen et al., 2005). Also, it allows people to rate models near their own age, with a maximum accepted difference of 9 years. Thus, using two age groups increases validity, reliability and generalizability.

The experiment has 2 x 5 factorial design in which one independent variable is gender (male or female), and the second one is the employment status (entrepreneur, starting entrepreneur, employee in public sector, employee in private sector, or unknown employment status). We made a distinction by including employees in public and employees in private sector, in comparison to the study we are replicating. It is believed that there are no distinct differences between the sectors in the Netherlands however, it is believed that in Croatia are recognizable. Unknown employment status was chosen as a neutral variable because it was

25 presumed to have no positive or negative connotations. These employment statuses were systematically varied over respondents, so that each picture of a model received separate ratings for all five work statuses.

The dependent variables are attractiveness, attractiveness as dating partner, and attractiveness as relationship partner. Those three measures were chosen because it has been noted that men and women's preferences differ depending on the level of involvement. This distinction is considered important as minimal requirements for a partner might differ between the three measures (Kenrick et al., 1990).

Figure 2. Research design

The survey was administered in Croatian, using Qualtrics online survey software. Real purpose was not given but instead a cover story was provided to participants, stating that the study was about speed dating and first impressions.

3.2. Sampling and data collection

To draw a representative sample, it is important to define the target population (Eisenhardt, 1989). The target population was Croatians living in Croatia aged 20 to 39. As the author of the thesis was unable to go to Croatia, respondents were recruited mostly by anonymous survey link through family, friends, and other contacts all over Croatia, ensuring representativeness by recruiting respondents within different age groups, different regions and with different educational backgrounds. The participants were tasked with rating five pictures of five models from a scale of 1 to 10, and with answering six control questions. From May 1st to May 16th, 2017, 347 responses were recorded in total. The minimum accepted age was

Enterepreneur Starting entrepreneur Employee in public sector Employee in private sector Unknown employment Male Female

entrepreneur Female Starting

Female employee public Female employee private Male unknown Female Male

entrepreneur Male Starting

Male employee public Male employee private Female unknown (IV) Employment status

(DV) General Attractiveness (DV) Attractiveness for dating (DV) Attractiveness for relationship (IV)

26 18 and the maximum 39. Unfinished responses, respondents older than 40, and non-Croatians were deleted. After taking into account the expected variance of the variables of interest, a desired sample of 237 was chosen.

The sample of 237 that was used for analysis resulted in 1185 observations because they rated 5 pictures of models. 106 (44,8%) were male and 131 (55,3%) were female. Mean age was 26.9 which indicates that, within the age range of 20 to 39, there were relatively more young people in the sample. This is shown in table 1.

Male Female Total

Between age 20-29 80 (33.8%) 91 (38.4%) 101 (72,2%) Between age 30-39 26 (11.0%) 40 (16.9%) 66 (27,9%)

Table 1. Distribution to age and gender within sample

Control variables were also collected from respondents. We include them to make sure we account for all variability among respondents. Firstly, they were asked which one of the following statements best fits them: I am an entrepreneur, I have the intention to become entrepreneur, I study entrepreneurship, None of the above. Secondly, they were asked who in their opinion earns more money, entrepreneurs, employees in public sector, or employees in private sector. Thirdly, they were asked who in their opinion has a higher social status, entrepreneurs, employees in public sector, or employees in private sector. Then, they were asked if they are currently in a serious relationship. Finally, they were asked about their educational level and ethnicity respectively. An overview of this data is provided in table 2 in which the information is split between males, females, and total.

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Variables Categories Males (106) Females (131) Total (237)

N % N % N % Entrepreneurial affinity Entrepreneur 11 10.4% 13 9.9% 24 10.1% Intention to become entrepreneur 21 19.8% 11 8.4% 32 13.5% Studied entrepreneurship 6 5.7% 13 9.9% 19 8.0% None of the above 68 64.2% 94 71.8% 162 68.4% Highest income Entrepreneur 74 31.2% 87 36.7% 161 67.9% Employee public 11 4.6% 24 10.1% 35 14.8% Employee private 21 8.9% 20 8.4% 41 17.3% Highest social status Entrepreneur 69 29.1% 83 35.0% 152 64.1% Employee public 17 7.2% 27 11.4% 44 18.6% Employee private 20 8.4% 21 8.9% 41 17.3% Serious relationship Yes 60 56.6% 95 72.5% 155 65.4% No 46 43.4% 36 27.5% 82 34.6% Education level No finished education 1 0.9% - - 1 0.4% High school gymnasium 18 17.0% 18 13.7% 36 15.2% High school vocational 23 21.7/ 13 9.9% 36 15.2% University degree 53 50.0% 90 68.7% 143 60.3% University professional 11 10.4% 10 7.6% 21 8.9%

Table 2. Control variables

3.1. Experimental procedure

The experiment was done using an online questionnaire created in Qualtrics. The questionnaire starts with an introduction in which the research is placed in the context of a master thesis at the VU. It is stated the questionnaire is anonymous and voluntary. A cover story is provided that the questionnaire is about first impressions and speed-dating. This cover is used to avoid bias from knowing the real purpose of the research.

Respondents were first asked about their gender and age, and then rated models of the opposite sex, within their age group. They were directed to the female models between ages 20-29, the female models between ages 30-39, the male models between ages 20-29, or the male models between ages 30-39. Every group contained six pictures of models because the

28 first one was used as an example. The respondents were randomly placed in one of five sets, within their age group. The sets contained the same pictures of models but the employment status was systematically varied so that every model had a different employment status in each set. This allows comparison of stimuli with employment status being the only difference. Respondents were asked to rate the models on their general attractiveness, attractiveness for a date, and attractiveness for a relationship.

Furthermore, all respondents were asked to answer six control questions, which were presented above. Finally, the survey ended by thanking the respondent and providing the e-mail address of the thesis mentor for further information.

3.2. Stimuli

Pictures of faces that were rated were used from the Chicago Faces Database which is developed and provided by Ma, Correll and Wittenbrink (2015). This data base was used because it contained pre-rated pictures of different models in the same pose, clothes, and with the same neutral expressions, resulting in standardized models and minimal bias between the pictures. Only Caucasian models were used because people in Croatia are mostly Caucasian. Rating other ethnicities on attractiveness may cause other impacts that are not desirable for the scope of this research. Selection of the pictures was divided by age groups and gender, therefore female models aged 20-29, female models aged 30-39, male models aged 20-29, and male models aged 30-39.

Figure 3 is an example of one of the stimuli in the female model 20-29 group. All of the pictures of the models used in the experiment can be found in Appendix 1.

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Figure 3. Example stimuli and measures

3.3. Measures

Measures used for two independent variables were gender and employment status. Gender had two levels: male and female. The five employments statuses were: entrepreneur, starting entrepreneur, employee in public sector, employee in private sector, and unknown employment status. This measure is the biggest difference from Borst (2016) and Wazir’s (2016) measurements. It is presumed that there is a wider gap between public and private sector in Croatia than it is in the Netherlands. That is why we chose to separate them. General attractiveness, attractiveness for a date, and attractiveness for a relationship were the measures used for the dependent variables. They were measured on a sliding scale from 0 to 10 with 1 decimal precision. See figure 2 for an example.

Several studies used pictures and asked respondents to rate attractiveness and used somewhat different measures of attractiveness. For example, Olson and Marshuetz (2005), Dunn and Hill (2014), and Dunn and Searle (2010). They all used a 1-10 scale to measure the ratings of attractiveness.

30 General attractiveness was chosen as the first measure. Physical attractiveness was not chosen because it is thought that attractiveness as whole is more captured by general attractiveness.

In some of the mentioned studies, participants were rating the attractiveness of models for a short-term relationship and as sexual partners. This might be offensive or controversial to some people and thus result in bias, so in order to avoid this issue participants were instead asked to rate the attractiveness of a model as a dating partner.

On the other hand, for a long-term partner, some studies chose to operationalize it as marital partners. However, the European marriage and divorce statistics show that there has been simultaneously a steady decline in marriage rates and increase in divorce rates for decades (Eurostat, 2017). Because of this, choosing to operationalize the attractiveness of a model as a relationship partner seemed as a better option.

All control variables appeared in the survey after rating the models except from the age variable, so that the control questions would not affect the ratings of the dependent variables. Control variables were: age, entrepreneurial association, opinion on highest income, opinion on highest social status, relationship status, education level, and ethnicity.

3.4. Data analysis

All data were analyzed using Microsoft Excel and IBM SPSS Statistics. In IBM SPSS Statistics, all three dependent variables were measured on 'scale'. In order to test the hypotheses, a series of variance analyses were performed, relying on ANOVA without controls. Additionally, t-tests and hierarchical regression analysis were performed. Both genders were analyzed separately as there were no formulated hypotheses concerning both genders together. Variable 'respondent gender' was assigned values of 1 and 2 for 'male' and 'female' respectively. Similarly, the independent variable 'employment status' was converted into a nominal variable, with values of 1 to 5 for 'entrepreneur', 'starting entrepreneur', 'employee in public sector', 'employee in private sector', and 'unknown employment status' respectively.

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4. Results

The number of observations, mean, standard deviation, minimum and maximum for each of the dependent variables are presented separately for both genders and in total in table 3. We can also see, when moving from general, to date, to relationship attractiveness, the mean ratings decrease as expected because the level of involvement with a potential partner increases. This is expected and also found by Borst (2016) and Wazir (2016) and confirms the validity of the data. Although there were some extremely low ratings (e.g. below 1), removing them did not change the results. Participants who gave such low ratings probably did not take this research seriously, or they thought the models were extremely unattractive or that every woman should look like a supermodel to date them or to be in a relationship with.

Respondent

gender N M SD Min Max

General

attractiveness Male 106 4,15 2,31 0,0 9,2

Date attractiveness Male 106 3,90 2,53 0,0 10,0

Relation

attractiveness Male 106 3,46 2,55 0,0 10,0

General

attractiveness Female 131 2,94 2,29 0,0 9,3

Date attractiveness Female 131 2,54 2,26 0,0 10,0 Relation

attractiveness Female 131 2,23 2,16 0,0 10,0

General

attractiveness Total 237 3,48 2,37 0,0 9,3

Date attractiveness Total 237 3,14 2,48 0,0 10,0

Relation

attractiveness Total 237 2,78 2,42 0,0 10,0

Table 3. Means, standard deviations, and number of observations according to groups

4.1. Male ratings of female models

Descriptive statistics with means and standard deviations for the general attractiveness of female models is shown in Table 4.

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Status N M SD Min Max

Entrepreneurs 106 4,27 2,24 0,0 8,2 Starting entrepreneurs 106 4,20 2,21 0,0 8,9 General attractiveness Employees in public sector 106 4,17 2,47 0,0 8,7 Employees in private sector 106 4,17 2,33 0,0 8,9 Unknown employment status 106 3,95 2,34 0,0 9,2 Total 530 4,15 2,31 0,0 9,2

Table 4. Descriptive statistics for general attractiveness of female models

The first hypothesis which states that entrepreneurial status will not have an impact on the general assessment of the attractiveness of women was confirmed. The hypothesis test used a one-way variance analysis that compared the effect of five different categories of employment status on perceived attractiveness of women. Since there was no statistically significant difference between the employment status and attractiveness (F = 0.285, p > 0.05), it can be concluded that the effect of the status does not significantly affect the estimate of the general attractiveness of women when evaluated by men. This is presented in table 5 for general attractiveness, with date and relation attractiveness shown in Appendix 2. This result means that women will be equally attractive to men regardless of whether they are entrepreneurs, starting entrepreneurs, public sector employees, private sector employees or whether their status is unknown. The implication of these findings is that the entrepreneurial status of women is not related to the assessment of woman's attractiveness.

M df F p

Between

Groups 1,53 4 0,28 ,888

General

attractiveness Within Groups 5,37 525

Total 529

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4.2. Female ratings of male models

Descriptive statistics for the general attractiveness, date and relationship attractiveness of male models are presented in table 6.

Status N M SD Min Max

Entrepreneurs 131 2,96 2,34 0,0 9,3 Starting entrepreneurs 131 2,83 2,23 0,0 9,0 General attractiveness Employees in public sector 131 2,79 2,27 0,0 8,4 Employees in private sector 131 3,09 2,29 0,0 8,3 Unknown employment status 131 3,02 2,33 0,0 8,9 Total 655 2,94 2,29 0,0 9,3 Entrepreneurs 131 2,54 2,26 0,0 8,2 Starting entrepreneurs 131 2,54 2,30 0,0 9,0 Date attractiveness Employees in public sector 131 2,44 2,26 0,0 8,4 Employees in private sector 131 2,56 2,21 0,0 8,9 Unknown employment status 131 2,60 2,33 0,0 10,0 Total 655 2,54 2,26 0,0 10,0 Entrepreneurs 131 2,29 2,22 0,0 10,0 Starting entrepreneurs 131 2,22 2,24 0,0 9,0 Relation attractiveness Employees in public sector 131 2,10 2,14 0,0 8,4 Employees in private sector 131 2,28 2,06 0,0 8,4 Unknown employment status 131 2,27 2,17 0,0 8,8 Total 655 2,23 2,16 0,0 10,0

Table 6. Descriptive statistics for general attractiveness of male models

Hypothesis 1b which states that entrepreneurial status will have a positive effect on assessing the attractiveness of male individuals was not confirmed. Participants indicated the degree of attractiveness of men on the Likert type scale. In the hypothesis testing a one-way variance analysis was used to compare the effect of five different categories of employment

34 status on perceived attractiveness of men. Since there was no statistically significant difference between the employment status and attractiveness (F = 0.368, p > 0.05), it can be concluded that entrepreneurial status does not significantly affect the estimate of the general attractiveness of men when evaluated by women. This means that men will be equally attractive to women regardless of whether they are entrepreneurs, starting entrepreneurs, employees in the public sector, private sector employees or whether their status is unknown. This is presented in table 7 for general attractiveness, date and relationship attractiveness. The implication of these findings is that the entrepreneurial status of a man is not related to the assessment of the attractiveness of men.

M df F p

Between Groups 2,01 4 ,38 ,821

General

attractiveness Within Groups 5,25 650

Total 654

Between Groups ,43 4 ,08 ,988

Date

attractiveness Within Groups 5,15 650

Total 654

Between Groups ,80 4 ,17 ,953

Relation

attractiveness Within Groups 4,70 650

Total 654

Table 7. One-way ANOVA general attractiveness of male models

The hypothesis that men's employment in the public sector will appeal more to women than men's employment in the private sector was not confirmed and is shown in Table 7. The analysis of the results found that there was no statistically significant difference between employments statuses and the ratings of general attractiveness, when women were evaluating (F=.38, p > 0.05). The same results appear for both date and relationship attractiveness. Women evaluated men equally attractive regardless of whether they are employees of the public or private sector, therefore it is obvious that neither the status nor the sector in which a person works does not significantly affect the assessment of men's attractiveness.

4.3. Comparison between Croatia and the Netherlands

The last hypothesis states that younger women will give lower attractiveness ratings of male entrepreneurs in Croatia compared to the Netherlands. When women aged 20-29 evaluated

35 entrepreneurs in Croatia and in the Netherlands, the results confirmed that there was a statistically significant difference in estimating the general attractiveness of male entrepreneurs between young Croatian women and young Dutch women. Dutch women, up to the age of 29, estimated male entrepreneurs as significantly more attractive than Croatian women estimated (t = 8,65, p < 0.001), as shown in table 8.

Table 8. Independent samples test ‘ratings of male entrepreneurs - Croatian vs. Dutch women

aged 20-29’

Dutch women also gave significantly higher ratings to entrepreneurs than the participants in Croatia when they investigated how much a certain male entrepreneur would be attractive to go on a date (t = 8,50, p < 0.001) and how much would entrepreneur be an attractive choice for the long-term relationship (t = 8.91, p < 0.001). These results can be interpreted in a way that there is a cultural difference in assessing the attractiveness of entrepreneurs for shorter and longer-term relationships, with status having a significantly greater impact on women in the Netherlands. We also compared ratings of older women (30-39) given to male entrepreneurs, between Croatia and Netherlands. The results suggested that again, women in Croatia gave significantly lower ratings to male entrepreneurs than Dutch women did. This was expected, as Croatians gave significantly lower ratings, for all models, on all counts of attractiveness compared to the Dutch. Therefore, we conducted an independent samples test in order to compare ratings of attractiveness between younger and older women in Croatia given to male entrepreneurs. The results are presented in table 9 and suggest that there was not a

36 significant difference in the ratings for general (t=1.66, p > 0.05) and relationship attractiveness (t=1.10, p > 0.05). However, there was a significant difference in the ratings for date attractiveness (t=2.05, p < 0.05).

Table 9. Independent samples test ‘ratings of male entrepreneurs – younger (20-29) Croatian

women vs. older women (30-39)’

These results suggest that there was no significant difference in ratings between younger and older Croatian women given to male entrepreneurs, except for date attractiveness. This means that younger women on average gave higher ratings to male entrepreneurs compared to older women when assessing date attractiveness. Perhaps, younger women considered dating entrepreneurs as more interesting or exciting.

Next section will describe important control and explanatory results.

4.4. Control and explanatory variables

As anticipated, ratings of attractiveness decrease with higher involvement with a potential partner. There was a significant difference in the ratings for general attractiveness compared to date attractiveness (t=10.38, p < 0.05), and compared to relationship attractiveness (t=17.24, p < 0.05). There was also a significant difference in the ratings for date attractiveness compared to relationship attractiveness (t=12.89, p < 0.05). This is presented in table 10.

37 M SD t df p (2-tailed) General attractiveness - Date attractiveness ,34 1,11 10,38 1184 ,000* General attractiveness - Relation attractiveness ,70 1,40 17,24 1184 ,000* Date attractiveness - Relation attractiveness ,36 ,97 12,89 1184 ,000*

Table 10. Paired Samples Test – Explanatory variables

Participants were asked who in their opinion has a higher income and higher social status. The results show that they in fact rated entrepreneurs more highly than employees in both sectors. This was already presented in table 2. The results are somewhat contradictory as GEM research showed that most Croatians do not believe entrepreneurs have a high social status. On the other hand, the results are in line with the last year’s research that states that most people in general believe entrepreneurs have a higher income than employees.

We performed a hierarchical regression analysis in order to test if any of the 5 predictors significantly explain attractiveness ratings. 5 predictors were: I am an entrepreneur, I am studying entrepreneurship, I intend to become entrepreneur, What is your level of education, and Are you in a serious relationship. This is presented in the table 11.

38 General attractiveness Date attractiveness Relation attractiveness

B SE B β B SE B β B SE B β Entrepreneur -0,36 0,23 -0,05 -0,49 0,24 -0,06 -0,34 0,23 -0,04 Entr. Intention -0,29 0,20 -0,04 0,09 0,21 0,01 -0,08 0,20 -0,01 Entr. Student -0,09 0,25 -0,01 -0,06 0,26 -0,01 -0,19 0,25 -0,02 In Relationship -1,27 0,14 -0,25* -1,29 0,15 -0,25* -1,27 0,15 -0,25* Education level -0,04 0,08 -0,01 -0,02 0,08 -0,01 0,03 0,08 0,01

Table 11. Regression analysis ‘effect of control variables on attractiveness ratings’

The model explained 19% (F=18.56, p < 0.05) of the variance in general attractiveness ratings with a R2 of 0.07. ANOVA indicates that predictors of the model significantly affect the ratings of general attractiveness, as shown in Appendix 3. The results show that only one predictor was significant (β = -.25, p < 0.05) and that was question ‘Are you in a serious relationship?’. None of the other control questions affected the ratings of general attractiveness. The same is true for the estimates of date and relationship attractiveness. The effect of question ‘Are you in a serious relationship?’ decreased the ratings of models for date and relationship attractiveness (β = -.25, p < 0.05). This means that participants who are in a serious relationship gave significantly lower ratings than participants who are not in a serious relationship.