WHO IS THE FAIREST OF THEM ALL? ON THE PUNISHMENT OF UNETHICAL BEHAVIOR. Laura PEETERS

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1 WHO IS THE FAIREST OF THEM ALL? ON THE PUNISHMENT OF UNETHICAL BEHAVIOR Laura PEETERS Abstract The present study investigated the role of attractiveness in a corporate context of assigning bonuses as a function of fraud. We predicted that highly (vs. lowly) attractive women would benefit from their looks and would face softer punishments when committing fraud. In addition to attractiveness, we predicted evaluator gender would be another moderating variable of the effect of fraud on bonus allocation, as prior research suggests men treat women more leniently than female evaluators. First, we conducted a within-subjects stimuli-selection pre-test to select two pictures that differed on perceived facial attractiveness, but not on other trait perceptions like intelligence, sociability, and trustworthiness. Afterwards, 112 respondents within Flanders participated in a scenario-experiment with a 2 (high vs. low attractive) x 2 (fraud vs. no fraud) x 2 (evaluator gender) between-subjects factorial design. The results indicated a main effect of unethical behavior on the assigned bonus. Evaluators punished a team member that committed fraud by withholding the bonus (almost) completely. In contrast to prior research, evaluator gender and attractiveness did not moderate this effect. Findings, however, do suggest the opposite pattern that very (vs. less) attractive female employees were punished somewhat more severely. Furthermore, we looked at indicators of the decision-making process. Respondents reported significantly more certainty regarding their bonus decision in the fraud (vs. control) condition. Lastly, decision-makers also punished themselves in the fraud (vs. control) condition by allocating a lower bonus to themselves. We discuss these findings with respect to their implications for future research in examining the attractiveness-leniency effect. Introduction The extensive attention to favoritism and discrimination in the corporate context puts leaders in a delicate position when making decisions that involve other individuals, a group or a whole organization. They are pressured to find a balance between empathy and rationality, while they are expected to act ethically. Unethical behavior of subordinates creates challenges to leaders, who are supposed to treat every individual the same. Employees are organization s main asset and greatest resource, and their performance is directly related to a firm s performance (Knowling, 2003, p. 88). Leaders have the responsibility to manage and develop this human capital. By doing this, leaders will face many difficulties and challenges. Adams (1965) suggested that employees compare their own inputs and outcomes of the job to their colleagues input-outcome ratio. Adams (1965, p. 280) states: when the normative expectations of the person making social comparisons are violated, when he finds that his outcomes and inputs are not in balance in relation to those of others, feelings of inequity result. Feelings of inequity will demotivate employees and constrain their work performance. As employees performance is crucial for a firm s performance, fair treatment among all employees is a crucial tool to keep up motivation and lead a successful company. However, an obvious case as the glass ceiling demonstrates that unequal treatment in business still exists. 1

2 In the present study we will investigate how (ethical) leaders handle reward and punishment in the form of bonus decisions regarding a female employee. We present a situation where only employees performance data are given, next to a context portraying the same performance data, but where participants in the experiment are told the employee boosted her performances unfairly and thus committed fraud. In addition, we investigate the influence of the employee s attractiveness on the leader s decision. In order to be perceived as fair-treated, an employee s appearance is not supposed to influence a leader s decisions regarding this employee or a whole group. On the other hand, an extensive body of research focuses on the role of beauty in criminal and corporate contexts and proclaims a beauty benefit for attractive people. The first part of the state of the art will discuss ethical leadership and the importance of rewarding and punishing behavior of employees. For the present study, allocating or withholding bonuses as a reward or punishment respectively play a crucial role. Furthermore, we will discuss the possible influence of attractiveness on the punishment of unethical behavior as a challenge to ethical leadership, as it could potentially have detrimental effects on the motivation of third-party observers. Therefore, in the second part, we consider the advantages and disadvantages appearance offers in different contexts and situations and how this might influence decision-making processes and leadership. State of the art 1. Ethical leadership As mentioned earlier, equity and anti-discrimination are the current buzzwords in society. This is nonetheless the case in business as well. Therefore attractiveness and the possible benefits for the lucky carriers are not supposed to play a role in recruiting, training, rewarding, and punishing. This places a huge burden on leaders in different settings. In business, ethics have always occupied a central position inside but also outside firms in interaction with the environment. Besides, its importance is only increasing, something we see in concepts such as corporate social responsibility, sustainable development, social entrepreneurship and ethical leadership (Groves & LaRocca, 2011). Still, the ethical dimension of leadership only recently established itself as a topic in academic research and needs further systematic consideration (Brown, Trevino, & Harrison, 2005). Research regarding leadership has mainly focused on change-oriented leadership and its transactional and transformational/charismatic dimensions (Avolio, Bass, & Jung, 1999; Brown et al., 2005; Burns, 1978; Groves et al., 2011). Burns (1978, p. 19) emphasizes leadership must include its followers and strive for common goals, based on values and motivations of both the leader and the followers. Therefore, interaction between leaders and followers is necessary and in fact, the essence of leadership. Burns (1978, p ) defines two ways in which this interaction can take place. Transactional leadership occurs when one person takes the initiative in making contact with others for the purpose of an exchange of valued things (Burns, 1978, p. 19). Transformational leadership occurs when one or more persons engage with others in such a way that leaders and followers raise one another to higher levels of motivation and morality (Burns, 1978, p. 20). To characterize these leadership styles, Bass (1990) built a model of leadership, consisting of six factors; five leadership factors and a passive-avoidant/lassaiz-faire factor. The author mentioned three main transformational factors; including charismatic-inspirational leadership, intellectual 2

3 stimulation, and individualized consideration. Furthermore, Bass stated two transactional leadership factors; contingent reward and management-by-exception (Avolio et al., 1999). Besides these factors correlate with each other, reflecting a continuum between transforming and transactional leadership. Research has shown that this continuum nowadays consists of a broad range of leadership styles (Avolio et al., 1999). Transformational leadership incorporates an ethical component, which leaders decide to adopt or not. This leads to a distinction between authentic (ethical) transformational leadership and pseudo- (unethical) transformational leadership. The latter does not hold legitimate intentions and goals, whereas the first has a strong moral compass and serves the organization (Kalshoven, Den Hartog & De Hoogh, 2011, p. 350). But instead of distinguishing ethical components of different leadership styles, recent research prefers to handle ethical leadership as a separate style (Brown et al., 2005; Kalshoven et al., 2011). In order to characterize this new style of leadership, Brown et al. (2005) define ethical leadership as: the demonstration of normatively appropriate conduct through personal actions and interpersonal relationships, and the promotion of such conduct to followers through twoway communication, reinforcement, and decision-making (Brown et al., 2005, p. 120). First of all, by proposing this definition, the authors emphasize the role model a leader is supposed to be by being honest, trustworthy, fair and caring. The normatively appropriate conduct obviously depends on the context, culture and also the perceptions of others (Brown et al. 2005). Moreover the perceptions of employees and stakeholders are crucial in developing a reputation for ethical leadership. More importantly, according to Trevino, Hartman and Brown (2000) reputation is the key to executive ethical leadership. Developing this reputation for ethical leadership rests upon other s perceptions of the leader on two essential dimensions: the leader as both a moral person and a moral manager. Individual traits such as honesty and integrity determine the characterizations of an executive as a moral person. Being an ethical person, however, does not necessarily allow someone to be perceived as an ethical leader. Therefore the CEO needs to be a role model and more specifically a moral manager by creating a strong ethics discourse that draws employees attention and influences their thoughts and behaviors. Introducing ethical guidelines for all employees actions is part of the job. Moreover, the ethical executive leader must also communicate clearly and inspire the whole organization to focus on ethics and values. Values are necessary to maintain cohesion within and outside the organization. Last but not least, the reinforcement part of the definition emphasizes that ethical leaders need to reward ethical conduct and discipline deviations from the ethical standards (Brown et al., 2005). This reward system needs to keep everyone on track with the standards and values (Trevino et al., 2000). This view will play a central role in the present study. We will examine the allocation of bonuses in an experimental setting, whereby these bonuses can be used as a reward or as a punishment of fraud. Punishing unethical behavior How managers handle unethical behavior of subordinates and punish them can be crucial for the future of a firm and their own reputation (Trevino et al., 2000). Trevino et al. (2000) acknowledged that reward systems are crucial to hold employees accountable for the values important to the organization. In a work situation often goals have to be achieved before rewards are in place. Trevino and Nelson (2007, p. 185) are convinced ethical goals are sometimes set aside when striving to accomplish a task. This task goal is more likely to cause risky behavior. Moreover, when employees fail to reach a certain goal, they intend to lie more about their performances (Trevino et al., 2007, p. 185). Therefore, reward systems can have a detrimental impact on unethical behavior. This leaves leaders in organizations with a complex situation when confronted 3

4 with unethical conduct of an employee or colleague. To be clear: setting high standards is not the problem, as we try to live up to them. Moreover, leaders who are aware of this effect can apply this human behavior to encourage ethical behavior. Trevino et al. (2007) call this the ethical Pygmalion effect; as we try to meet high ethical expectations, we will consider our behavior more consciously. Thus, in this way we do not only think about what to achieve but also how we achieve our goals (Trevino et al., 2007, p. 187). Considering the reinforcement theory, reward systems have a decisive impact on behavior at work. Without doubt incentives and setting goals motivate behavior. But Trevino and Nelson (2007, p. 184) also consider the costs. The authors mean rewards do not come for free. Punishment, on the other, hand advises us not to follow a certain path. Operant or instrumental conditioning, originating from social psychology, clarifies this approach. Operant conditioning is a type of learning that uses reinforcement or punishment to change one s behavior. People learn there is a link between their own actions and changes in the environment following these actions. This teaches us how to control our environment. Reinforcement will cause an increase in certain behavior, while punishment aims to reduce it. Thus the consequences following certain (operant) behavior modify this behavior negatively or positively. Therefore, reinforcement can be either positive, when an appetitive or rewarding stimulus is linked to a situation, or negative, when someone can escape an aversive stimulus by engaging in certain behavior (Nuttin & Hoorens, 2008, p ). For the present study punishment plays a crucial role. Punishment too can be either positive or negative. One has to be careful though; positive punishment does not offer an incentive, but adds an unpleasant stimulus in order to discourage certain actions (Nuttin et al., 2008, p. 50). A common example is spanking a child when it is being disobedient. On the other hand, negative punishment takes away a pleasant stimulus, such as a child s toy. Positive rewards and especially negative punishment will be central to the scenario-experiment for the present study. By allocating a bonus, an employee feels rewarded for his or her performance. This is a positive reinforcement. On the other hand, in the experimental condition, the respondent in the role of (ethical) leader can decide to withhold (a part of) the bonus to punish an employee who committed fraud. This is a situation of negative punishment, where a pleasant stimulus will be taken away. A leader has to be aware of the signal he or she gives by making certain decisions towards employees, but also others. An extension of the reinforcement theory is Bandura s social learning theory. Rewards and punishments offer information to peers and will influence people s behavior; we even don t have to experience it ourselves. As ethical behavior is mostly the expected way of acting, rewarding seems useless, at least in the short run (Trevino et al., 2007, p. 189). You do not get rewarded for not stealing money from clients for example. On the other hand, disciplining your employees is necessary and effective, but therefore the punishment needs to be perceived as fair and consistent by the recipient and the outsiders. Thus, leaders must consider the example they set when offering bonuses or promotions to cheating employees, or when punishing (un)fairly. Considering the social learning perspective, punishing unethical behavior can have constructive indirect effects when done without exception and fair (Trevino et al., 2007, p.191). In the present study, participants as leaders can decide on the bonus they assign to a certain employee. Bonuses are a common and useful tool in business to reward and punish. Therefore, this seems an appropriate measure of the punishment a leader will give to a (less or more attractive) fraudulent employee. By withholding a bonus, the leader effectively uses a tool for punishment that can also serve as a trigger towards peers and other employees. Perpetrators of unethical behavior will learn from their mistake and can be motivated to inhibit the temptation to dishonestly boost performance. In addition, peers will experience the consequences of unethical conduct indirectly, but will nonetheless engage in a social learning process. 4

5 It is clear leaders play a significant role in the development of employees and work performance. Burke, Stagl, Klein, Goodwin, Salas, and Halpin (2006) conducted a meta-analysis to examine the relationship between leadership behavior and the performance in the team of the leader. Personfocused leadership behavior, something we can find in transformational and ethical leaders, was significantly related to perceived team effectiveness, team productivity and learning in the team. Moreover, the behavior of the leader seemed to be significantly related to team performance outcomes in general. In general, research showed ethical leadership predicts outcomes such as perceived effectiveness of leaders (Brown et al., 2005), work unit effectiveness (Lowe, Kroeck & Sivasubramaniam, 1996), follower s job satisfaction, dedications (Brown et al., 2005) and effort (Groves et al., 2011, Lowe et al., 1996), and their willingness to report problems to management (Brown et al., 2005). Also considering Bandura s social learning theory, leaders set an example for their subordinates and how managers handle their team can be decisive for its performance and its future (Trevino et al., 2000). We will use the bonus allocation as an indicator of ethical leadership in a person. As leaders and especially ethical leaders are concerned with engaging in a true role model, they are not supposed to be biased regarding more or less attractive employees. This bias does not correspond to ethical leadership and sets the wrong example, which can threaten the future of a team and even a whole organization. The motivation to be (un)ethical It is important to consider the reasons that underlie unethical behavior. In discussions about ethics, the rational choice approach has prevailed for a long time (Trevino et al., 2007, p. 24). Following the path of classical economists, self-interest would be the first and foremost motivation for humans to behave ethically. This view considers human beings as entirely rational when making decisions. Therefore, we are supposed to use cost/benefit analyses. On the other hand, one cannot deny the homo economicus sometimes behaves irrational. For that reason, behavioral economists acknowledge the situation is more complex. Humans not only posses bounded rationality, but are also more moral and altruistic than classical economists propose (Trevino et al., 2007, p. 24; Etzioni, 1988). Eventually Etzioni (1988) claimed that human action has two distinct sources: the pursuit of self-interest and moral commitments (Trevino et al., 2007, p. 24). Thus people are influenced by ratio and ethics when making choices. This is an important consideration we have to take into account when discussing ethical leadership. Not only our rationality is bounded, Chugh, Bazerman, & Banaji (2005) are convinced we also suffer from bounded ethicality. There are limitations to our ability to behave ethically. Collins (1990) sums up three main raisons why employees may engage in unethical behavior. Unethical behavior can rise from the self interest of employees, as happens when stealing from the company, but it can also occur because of (mis)understood expectations when subordinates truly believe the unethical behavior is in the company s best interest. And finally, it is possible employees do not realize they are behaving unethically (Collins, 1990; Trevino et al., 2007, p. 30). The type of unethical behavior we will use in the experiment for this study, Collins (1990) classifies as ethical egoism. In this case self-interest is the main motivation to act unethically and for example outperform colleagues unfairly (Collins, 1990). Collins suggests the cure for ethical egoists is an environment where unethical conduct is discouraged, something we will also use in the experiment for this study, where respondents in the unethical condition can decide upon the punishment they give in terms of withholding a bonus. By doing this, the leader deviates from the equity rule to allocate higher bonuses for better performance if the performance was in fact dishonestly boosted (e.g., as is the case in fraud). The author even states an organization should be aggressively hostile to any unethical conduct in which it discovers its employees have engaged (Collins, 1990, p. 20). Therefore, policies are in place but cannot be rigid systems, because every situation is different (Collins, 1990). 5

6 Gender differences in ethical leadership and the evaluation of unethical behavior Research on ethical leadership also focused on gender differences in ethical perceptions. Ergeneli and Ankan (2002) presented various scenarios describing possible ethical misconduct to managers and salespeople in Turkey. After that, the participants indicated in how far they agreed with this situation. The researchers could not find any gender difference in the evaluation of these scenarios and thus concluded women share the same values as men. Still, female salespeople and managers showed more ethical responses to the scenarios. Interestingly, male and female respondents expected their other-sex counterparts to react in the same ethical way as themselves. Schminke (1997) investigated gender differences in managers judgments about other leaders ethical decision-making. Overall, male and female managers agreed more with a male manager, who retained a less-qualified employee, than with a female manager making the exact same decision. Besides, women judged another female manager, who retained a less-qualified employee, harsher than male evaluators. Betz, O Connell and Shepard (1989) conducted a study to investigate the relationship between gender and the willingness to engage in unethical business behavior. The results showed men are twice as likely as women to act unethically. The findings also suggested females are more sensitive to ethics and ethical information. Owhoso (2002) on the other hand, could not establish a gender difference in ethical sensitivity among experienced and inexperienced auditors. Next to differences in ethical perceptions, decision-making differences between men and women formed the basis of leadership research. For the present research, where respondents will imagine themselves in the role of a leader, it is important to consider if men and women act differently as a leader. In a meta-analysis, Eagly and Johnson (1990) found that women tend to lead more democratically and participative. Men adopt a more autocratic and directive style. In a study by Bass, Avolio and Atwater (2008), leaders of both sexes were rated on transformational and transactional leadership aspects by their male and female subordinates. Female leaders appeared to be more transformational oriented than men, as they display more aspects of this leadership style (i.e. charisma and individualized consideration). Besides, the subordinate s gender did not influence his or her evaluation of the leader. Eagly, Johannesen-Schmidt and van Engen (2003) as well found that women display more transformational leadership characteristics than men. In addition, female leaders engaged more in contingent reward, which means they recognize accomplishments more and offer more material and psychological reward as incentives. It must be said that the established differences were rather small, but still, the authors suggest women might exceed men on aspects of leadership that are crucial for leaders effectiveness (Eagly et al., 2003). On the other hand, in a meta-analysis, Eagly, Karau and Makhijani (1995) could not establish an overall difference in effectiveness of male and female leaders, but there are conditions when female or male leaders may excel. When leadership roles were defined in masculine terms (e.g. required ability to direct and control people), men experienced an advantage and were more effective, while feminine defined roles (e.g. required interpersonal skills) favored female leaders. Furthermore, Eagly et al. (1995) put forward that male leaders are more effective when subordinates are men. Thus, men and women show different leadership characteristics, but also their effectiveness differs. Each sex may be especially effective in a leadership role, regarded as congruent with their gender. The process of decision-making among male and female (ethical) leaders is still unclear and offers an interesting additional viewpoint from where to investigate punishment of unethical behavior. The body of research that focuses on gender differences in leadership indicates that this area must not be ignored when conducting research on ethical leadership. Gender might in fact influence the decisions a leader makes regarding his or her subordinates. Therefore, we will explore how male vs. female decision-makers handle unethical situations, more specifically a situation of fraud by an employee. 6

7 As mentioned before, how leaders handle situations where punishments or rewards are in order, plays a crucial role in motivating other employees. Equity is the norm, and is often enclosed in ethical codes of large corporations. The managers of these corporations set an example and can use their position to spread an ethical way of thinking and working. On the contrary, when employees do not perceive a fair treatment and consider leaders as making unjust decision, they will experience distress end might even develop hostile feelings towards the leader and/or organization. This can be detrimental for their motivation on the work floor, morale, efficiency, and eventually, the firm s performance. There are many antecedents and factors that might lead to preferential treatment of one person above others. In the present study we will focus on the influence of employees attractiveness on leaders bonus decisions as a punishment or reward. 2. Attractiveness: a challenge to ethical leadership The myth surrounding beauty has captured human attention from the rise of mankind, over the history of philosophy towards the seventies and its scientists in the field of for example social psychology and behavior studies (Etcoff, 1999, p. 9, 26). The what is beautiful is good idea suggests that good-looking people benefit from their physical attractiveness compared to less attractive human beings (Johnson, Podratz, Dipboye, & Gibbons, 2010). This stereotype functions as a guideline and causes people to attribute unrelated, positive characteristics to physically attractive people (Abel & Watters, 2005; Dion, Berscheid, & Walster, 1972; Johnson et al., 2010). Not only do attractive people develop more social skills, their future also looks brighter according to research of Dion et al. (1972). Moreover Dion and Berscheid (1974) found that even at the early age of four to six years old children prefer more attractive classmates and acknowledge them as being more social. Scientist and psychologist Nancy Etcoff (1999) states the importance we attach to beauty is rooted in our human nature. Babies as old as three months prefer to look at beautiful instead of ugly faces (Etcoff, 1999, p. 30). Following upper mentioned findings one could say that the effect of attractiveness kicks in very early. What makes someone beautiful? Beauty is in the eye of the beholder (Hamermesh, 2011, p. 11), but Etcoff (1999, p ) emphasizes people across cultures, sexes and ages generally agree about which faces they find attractive. Personal taste plays only a marginal role. Also Langlois, Kalakanis, Rubenstein, Larson, Hallam and Smoot (2000) discovered an overall agreement about attractiveness within and across cultures. But, what is it that makes a face attractive? According to Etcoff (1999, p , 150) two factors, originating from biology, influence attractiveness. Next to symmetry, average shape, meaning shapes excluded from individual variations and deviation such as the size of one s nose, composes a beautiful face. Besides, we like people that look similar to us (Etcoff, 1999, p. 136). In addition, there are some factors we can control to look good. A smiling facial expression makes someone look more attractive and is associated with more positive attributes (Abel et al., 2005). In a study about the effects of smiling, participants liked smiling people more and evaluated them more positively than the same person not smiling (Lau, 1982). Reis, Wilson, Monestere, Bernstein, Clark, Seidl, Franco, Gioioso, Freeman, and Radoane (1990) too established the positive influence of smiling on the perceived attractiveness compared to a neutral expression. Besides smiling people are perceived more intelligent (Lau, 1982), sincere, sociable and competent (Reis et al., 1990). Therefore smiling seems a component of attractiveness that influences the what is beautiful is good stereotype. All these factors and components of beauty have to be taken into account when researching the influence of attractiveness on several outcomes. 7

8 Doing research on a vague, subjective aspect of human life such as beauty, asks a lot of consideration on how to accurately investigate it. Still, Hamermesh (2011, p. 18) is convinced there must be at least a somewhat common standard of beauty, otherwise it cannot have any independent effect on outcomes such as earnings, which will be discussed in the second part of this state of the art. To find out about these common standards, we must measure and compare people s views regarding beauty (Hamermesh, 2011, p. 19). In the present study, we carefully selected pictures of women differing on perceived facial attractiveness. To distinguish less from more beautiful women, a stimuli-selection pre-test was conducted in order to select two pictures of women out of nine, respectively high and low attractive. The women were comparable regarding age, style, looks, and smile, but are rated on the crucial differing variable: facial attractiveness. Does beauty pay? a. In a corporate context Etcoff (1999, p. 30) is convinced beauty plays a significant role in our day-to-day lives by affecting our perceptions, attitudes and behavior vis-à-vis others. In a longitudinal study Jaeger (2011) found support that physical attractiveness matters throughout the life course. Langlois et al. (2000) established the influence of attractiveness on daily lives and interactions and demonstrated that attractive adults are judged more positively on different attributes and competences. Etcoff (1999, p. 30) even goes one step further by referring to the conviction of economist David Marks that beauty influences society by the same amount as race and gender. Appearance matters in different settings, throughout different times, but research has also focused on its potential influences, benefits, and costs. In organizations equity and anti-discrimination are highly valued, while Langlois et al. (2000) discovered an advantage of attractiveness in the workplace. Jaeger (2011) found that women with a lower Body Mass Index and more attractive faces reached higher socio-economic status in their careers. In household surveys Hamermesh and Biddle (1994) discovered less attractive women have a lower participation rate in the labor force. These women also seem to marry men with less human capital. Research of Johnson et al. (2010) supported the idea that attractive men and women get higher rating of employment suitability and therefore benefit from their looks when applying for a job. Watkins and Johnston (2000) established a positive effect of attractiveness in hiring practices. Especially with a mediocre résumé, beauty could get a person ahead of others. In an experimental labor market Mobius and Rosenblat (2006) discovered three main advantages to beauty: first of all, physically attractive workers got higher wages thanks to their higher confidence. Secondly, employers considered beautiful workers as more competent. And finally, beautiful workers showed better oral skills, such as communication and social skills, which led to higher wages. This effect was independent of higher confidence among attractive workers. Next to experimental settings, also real data of the labor market showed a beauty premium, although in lesser extent than experimental studies. Hamermesh et al. (1994) found a relationship between attractiveness and earnings; plain people earn less than average-looking people, who earn less than the good looking. Moreover the authors suggest that attractive people are fit into occupations where their looks can be productive. The wage gap, also between men and women, will be further discusses in a later section. b. In an unethical (criminal) context When we want to discover the what is beautiful is good effect in unethical situations, the body of research regarding criminal cases is more extensive than the corporate context. Unethical behavior does not necessarily imply a crime. Simple, natural actions that cross the line can be classified as 8

9 unethical behavior, as for example lying. When studying the punishment of unethical behavior, most research focuses on crime and serious criminal settings in general. Remarkably, even in these severe unethical situations, beauty can pay off. Efran (1974) found support for the easier treatment of guilty but physically attractive defendants. Later, this conclusion has further been confirmed by Stewart (1980, 1985), who discovered a negative relationship between the attractiveness of criminal defendants and the severity of punishment. The author called this the attractiveness leniency effect (Stewart, 1980, 1985). The effect of attractiveness on the sort of sentence did not depend on the seriousness of the crime. In general, more attractive criminal defendants received a more lenient treatment. Considering the side of the victim, Callan, Powell, and Ellard (2007) discovered a harsher punishment for criminals when the injured party was physically attractive. Respondents also considered the crime as more tragic and unjust. All these findings point in the direction of the what is beautiful is good stereotype. In contrast to previous research, McKelvie and Coley (1993) did not find any support for the attractiveness leniency effect. On the other hand, the same researchers discovered an ugly is bad stereotype regarding mental illness but not regarding crime. Less attractive robbers were more easily appointed towards psychiatric care. Also the research from Griffin and Langlois (2006) confirms the ugly is bad stereotype, indicating the disadvantages of unattractiveness among adults as among children. According to Etcoff (1999, p. 51) ugly is bad gets more scientific support than beautiful is good. Given that we only discriminate between high and low attractive women in our study, and do not include a moderate condition, this will not be something that will be tested here. Drawbacks of beauty: when beauty is beastly The what is beautiful is good stereotype found support in early and several studies (Dion et al., 1972, 1974). Next to the positive characteristics we believe beautiful people have, Etcoff (1999, p. 49) is convinced we also set higher standards for them. According to the author of survival of the prettiest: the science of beauty these expectations can work out negatively for attractive human beings. Andreoni and Petrie (2008) demonstrated this in a work-related context. Due to higher expectations regarding cooperation, beauty becomes a penalty and leads to harsher treatment. Only when no information regarding performance was provided, beauty offered a premium. The beauty is beastly effect found support in a small body of research and points toward different effects for men and women (Heilman & Saruwatari, 1979; Heilman & Stopeck, 1985; Johnson et al., 2010), which will be discusses in the next section. In a criminal context Sigall and Ostrove (1975) stated that attractive defendants in crimes unrelated to attractiveness, such as burglary, were sentenced less severely than unattractive defendants. But when defendants used their attractiveness in offenses as swindle and deception, the punishment was more severe. So, when abusing looks to cheat or commit fraud, beautiful people can be disadvantaged compared to unattractive cheaters, who get punished more softly (Etcoff, 1999, p. 51; Sigall et al., 1975). In negligent homicides, i.e. unintentional murder, attractive defendants also tend to be treated more harshly (Mazzella & Feingold, 1994). Abwender and Hough (2001) suggest this might be the case because these beautiful defendants should have exhibited better judgment, which is also an application of the what is beautiful is good stereotype. When judging unethical behavior, attractive people may be held to higher standards. When they do not live up to these standards, beautiful people face harsher punishments (Abwender et al., 2001, Mazella et al., 1994). 9

10 In the present study though, we will not explicitly refer to the misusage of looks when committing fraud. Besides, this fraud is depicted in a corporate instead of criminal context. Still, the effect of attractiveness could depend on many factors, such as the type of unethical behavior. Also Mazella et al. (1994) suggested that the type of offense might influence the leniency bias. We could say that the effect of attractiveness on punishment depends on the context and situation, and of course people s perception and judgments. Thus, despite extensive evidence that physical attractiveness leads to a preferential treatment and discriminates less physically attractive people, there are possible drawbacks to beauty when punished for unethical behavior (Abel et al., 2005; Efran, 1974; LaFrance & Hecht, 1995; Mazella et al., 1994; Sigall et al., 1975; Stewart, 1980, 1985). In certain situations attractiveness can have a detrimental effect, specifically to women. It is important to take the possible drawbacks of beauty into consideration when conducting research on ethical leadership. The next section will clarify this approach further and focus on how both sexes are influenced by attractiveness and the effect on (preferential) treatment. Gender and attractiveness influences on favoritism Visual stimuli, and therefore physical attractiveness, can influence men and women in various ways. This different processing of visual information between men and women plays a role when discussing perceptions and effects of beauty in various settings. Lykins, Meana and Strauss (2008) confirm that men and women do not visually process erotic and non-erotic information in the same way. Firstly, men significantly look longer at women, the opposite sex, than at other men. Women, on the contrary, do not differ in time spent looking at the same or the opposite sex. Secondly, women spend considerable more time examining other women, than men looking at other men. Therefore, women seem to investigate other women more critically than men analyze their same sex peers. On the other hand, men value attractiveness more than women (Aronson, Wilson & Akert, 2010, p. 325). Thus, as men attach more importance to beauty, they could also be more sensitive for looks and easier influenced by a woman s appearance. This sensitivity can lead to a preferential treatment of beautiful women by male evaluators and eventually also male leaders. Consequently, the attractiveness-leniency effect might be more prominent among male evaluators, compared to females. Aside from the different perceptions of beauty among men and women, it is important for the present study to consider scientific research about gender differences in attractiveness effects, and the favoritism it is associated with. In a meta-analytical study Hosoda, Stone-Romero and Coats (2003) could not find a moderating effect of gender on job-related outcomes; attractiveness was as important for men as for women. Neither could these researchers establish the beauty is beastly effect for men or women; regardless of the sex and type of job, the authors are convinced physical attractiveness is always an asset. Another meta-analysis by Langlois et al. (2000) also failed to establish a sex-based different effect of attractiveness. In contrast to these findings, an extensive body of research documents the different effects of beauty for men and women. These studies clearly indicate that different treatment between the two sexes still exists. Ahola, Christianson and Hellström (2009) conducted an experimental study on different kinds of crimes and attractiveness of female and male defendants. The results showed that women, and more attractive women in particular, are treated more leniently compared to male defendants. In follow-up research the same scientists (Ahola et al., 2010) examined how various sources of information can cause this bias in a judicial process by also taking into account the influence of evaluator gender. The experiment used legal practitioners (e.g. law students, jurors, police officers, ) as evaluators of defendants in a criminal trial. The experiment presented different crimes, ranging from child molestation to homicide. Respondents received a booklet describing the crime and presenting a picture of the face of the male or female defendant (i.e. 10

11 highly vs. lowly attractive). The evidence in every condition was hard and clearly showed the offender was guilty, while he tried to deny or minimize his actions. Some respondents, more specifically the judges and jurors, had the role of sentencing, while other evaluators did not have a profession in the judicial process where they had a sentencing role. The results confirmed a significant effect of defendant s gender and appearance, which was qualified by evaluator gender revealing a same sex penalty effect. When respondents theoretically could decide on the sentence the defendants would get, legal practitioners evaluated defendants of their own gender more harshly compared to a defendant of the opposite sex. Thus, the position of the evaluator did play a key role in these effects; the same sex penalty depended on the type of the evaluator (sentencing or not-sentencing). We must take these findings into consideration when investigating leaders bonus decisions. In fact, leaders are in place to decide on rewards and punishments for their subordinates. Punishing unethical behavior is a leader s task and therefore might lead to the same sex penalty, as was the case with sentencing evaluators in the study of Ahola et al. (2010). But still, these findings came out of a criminal situation and therefore cannot be immediately extrapolated towards a corporate context. Regarding the discrimination of women in a working environment, Johnson et al. (2010) investigated the beauty is beastly effect, which found support in some earlier studies (Heilman et al., 1979; Heilman et al., 1985), but could not find an effect of attractiveness on employment suitability for women applying for masculine sex-typed jobs. But, when women applied for a masculine job where looks do not play a crucial role, they were disadvantaged (Johnson et al., 2010). In an experimental study, Heilman and Saruwatari (1979) did find support for the beauty is beastly effect, as attractiveness advantaged men but disadvantaged women in their career paths. Only when applying for non-managerial positions, attractiveness was also for women an advantage (Heilman et al., 1979; Heilman et al., 1985). Jaeger (2011) discovered different effects of attractiveness for men and women on socio-economic and marital success over the life course. In a longitudinal study, the author found that women with attractive faces and lower BMI reach a higher socio-economic status and more prestigious occupation later in their careers. This was not the case for men. On the other hand, attractive men did benefit from their looks with regard to earnings, which was not the case for women (Jaeger, 2011). The wage gap is one of the most concrete and significant indications of different treatment of men and women in the business world. Attractiveness also plays a role in this matter. Hamermesh et al. (1994) could only establish a small difference between the two sexes when it came to earnings. Men would benefit slightly more from their looks than women. Andreoni et al. (2008) also examined the role of gender and beauty premium in the labor market and found support for the preferential treatment of attractive people and especially women in a public goods experiment. On the other hand, the researchers suggest that when information regarding the contributions of each group member is available, beauty becomes a penalty and the beauty premium switches to a male premium. Especially when performance numbers are given, men benefit from their looks. The authors attribute this to the fact that men are better leaders and set an example by making large contributions. If men and women actually do act different as a leader and might be influenced by attractiveness in a different way, will also be examined in the present study. Furthermore, research on the wage gap indicates that women perceive it as fair that they earn less than men. Empirical evidence shows women also pay themselves less for comparable work (Hogue & Yoder, 2003). In social psychology, this effect is called depressed entitlement. Women feel less deserving than men and consider lower wages equitable. System justification theory explains this effect by proposing that even the disadvantaged can start to believe the status quo is legitimate and eventually justify the inequalities that oppress them (Hogue et al., 2003). As women in business perceive themselves as the low-status group compared to men, they show more out- 11

12 group favoritism and believe the group they belong to is inferior to the out-group (Dasgupta, 2004). However, humans do not only differentiate in-groups from out-groups (inter-group differentiation) and normally show general favoritism towards the in-group, but they also differentiate between individual members within a group (intra-group differentiation). Generally, people tend to favor individuals who align and cooperate with the in-group. On the other hand, when a group member deviates from the in-group, in-group favoritism can be eliminated and reversed. This happens when a group member shows anti-normative behavior. People tend to feel less favorable towards in-group members whose attitudes or behavior suggest relative rejection of in-group norms (Abrams, Rutland, Cameron & Marques, 2003). Gino, Gu and Zhong (2009) suggest that feelings of guilt, induced by the transgression of an in-group member who engaged in unethical behavior, can cause other group member to compensate this behavior. Also Lewis and Sherman (2010) suggest that a confrontation with a negative in-group member can lead to harsher punishments compared to an out-group member. The shared group membership increases embarrassment and this forms a threat to a positive social identity. This can lead to a biased evaluation of this in-group member in order to preserve the positive evaluation of oneself or the group (Lewis et al., 2010). This is also called the black-sheep effect, when individuals rate the poor performance of an in-group member more negatively than comparable out-group performances. Because people identify with their in-group and use it for their social identity, their judgments towards the in-group members can be more extreme (Marques & Izerbyt, 1988). In addition, Braun and Gollwitzer (2012) suggest that a lenient punishment for out-group offenders may be used by in-group members as a strategy to show they are not prejudiced (the patronizing leniency effect). These considerations are important in the light of the present study. Women, and especially female leaders, can portray less in-group favoritism when they feel a part of a disadvantages group (Dasgupta, 2004, Hogue et al., 2003) or when another female employee behaved unethically (Gino et al., 2009). In addition, a female employee who deviates from the norm by committing fraud, can be treated harsher by an in-group member (another woman) compared to an out-group member (in the present study a male evaluator). Men, on the other hand, can portray a patronizing leniency effect towards female employees and assign higher bonuses to them. These gender differences will be hypothesized as influences on bonus allocation towards a female employee. Problem statement, research questions & hypotheses As pointed out before, prior research has examined the attractiveness-leniency effect in a judicial context. Yet, until today very little research has been conducted on beauty in a working environment (Andreoni et al., 2008; Hamermesh et al., 1994; Heilman et al., 1979, 1985; Hosoda et al., 2003; Jaeger, 2011; Johnson et al., 2010; Watkins et al., 2000). The little research conducted on beauty in a corporate context mainly focused on the general advantage of physical attractiveness in the labor market, such as the influence on socio-economic status (Jaeger, 2011), participation rates (Hamermesh et al., 1994), ratings in employment suitability (Johnson et al., 2010), wages (Hamermesh et al., 1994; Mobius et al., 2006) and a variety of job-related outcomes, among which recruitment, selection processes (Hosoda et al., 2003; Watkins et al., 2000) and rewarding performance (Hosoda et al., 2003). The influence of attractiveness on ethical leadership and punishing unethical behavior in a corporate framework offers a new viewpoint from where to study the effect of attractiveness on punishment. In addition, the task of assigning bonuses as a reward or punishment did not pop up in attractiveness research before. Because of this lack in current research, we based the rationale and design of the present study on a master thesis by Vercamer (2012), which we will try to replicate. Vercamer (2012) already acknowledged the need for research regarding the link between attractiveness and bonus decisions in a corporate context. A scenario-experiment with a 3 (level of attractiveness) x 2 (unethical 12

13 conduct) x 2 (evaluator gender) between-subjects design explored the effect of unethical behavior on bonus decisions regarding a female employee. The employee was a sales-advisor in a clothing store. In all conditions, respondents received the performance numbers of the team and a file with information regarding sales advisor B. In addition, in the experimental condition respondents read about the employee, who violated the company s code of conduct to unfairly boost her performances. The file included a picture of this employee. Here, the manipulation of attractiveness took place. Three pictures were selected after a pre-test and differed significantly regarding facial attractiveness on three levels; lowly attractive, moderately attractive and highly attractive. After the presentation of the performance numbers and the employee s file, respondents decided on the bonus they wanted to assign to this certain employee. The author suggested men would judge women differently compared to female respondents. Women are very critical when looking at other women and could therefore make harsher punishments towards their same-sex peers. Vercamer (2012) proposed men would allocate more bonus towards female employees and therefore also treat women more leniently compared to female decision-makers. The results of the 3 (level of attractiveness) x 2 (unethical conduct) x 2 (evaluator gender) between-subjects experiment showed that a shop-assistant who violated the company s code of conduct received less bonus than an employee who did not engaged in unethical behavior. In addition, a main effect of attractiveness was found; the least attractive sales advisor received a lower bonus than the very attractive employee. Therefore the results support the ugly is bad stereotype, as the moderately attractive employee was not disadvantages when bonuses were assigned by the leaders of the clothing store. And last but not least, the study established a significant three-way interaction between the evaluator s gender, the attractiveness of the employee and the (un)ethical behavior of this employee. In the control condition, bonus assigned by men and women did not differentiate between more or less beautiful employees. On the other hand, when a lowly attractive sales-advisor violated the code of conduct, male managers of the clothing-store assigned significantly less bonus to this employee compared to the very attractive sales advisor. To conclude, the author suggests ethical leadership and the equal treatment of all subordinates needs further attention and elaboration. Therefore, in the present study we will focus on replicating the previous findings by Vercamer (2012), in order to generalize our understanding of the influence of attractiveness on the punishment of unethical behavior in a corporate framework. Compared to last year s study the experiment for the present study will present two new pre-tested pictures of female faces as stimuli. As the thesis research by Vercamer (2012) could not establish significant differences between three levels of attractiveness, but only between the two extremes, we will use a picture of a lowly vs. highly attractive woman. In addition, the scenario-experiment will present a clear situation of fraud in the banking sector instead of a violation of the code of conduct in a clothing store. This leads to less ambiguity in the scenario. In addition, we will ask leaders to assign a bonus to oneself and look into the factors that influence the process of decisionmaking among (ethical) leaders in a scenario-experiment. The crucial strength and added value of the present study lies in its experimental nature and investigation of a causal relationship. Besides, a replication study should offer a more general understanding of the challenges attractiveness pose to ethical leadership. We will examine the link between attractiveness, fraud and punishment in a corporate context. Therefore, this study will fill the gap in existing research by investigating a somewhat neglected context where most humans spend an important part of their life; a working environment. Following the main rationale of upper-mentioned research, next research questions and hypotheses arise: 13

14 RQ 1: In how far does attractiveness play a role in the punishment of unethical behavior (at the corporate level)? In addition, we will try to replicate thesis research by Vercamer (2012), in order to gain more general insight into the influence of beauty on bonus decisions and ethical leadership. RQ 2: In how far are last year s findings replicable when a. using new stimuli as manipulation for attractiveness b. the unethical behavior is explicitly referred to as fraud and, hence, leaves less ambiguity about its unethicality Regarding this central research questions and the research outlined above, we formulate three central hypotheses, focusing on the following main effects: H1: People allocate significantly lower bonuses to employees who obtained high performance scores through fraud than when nothing is mentioned about the manner in which the high score was obtained. H2: People allocate higher bonuses to attractive female employees than to their less attractive peers H3: Male evaluators assign higher bonuses than female evaluators (as already mentioned, in our research, the recipients of the bonus decisions are female employees). Furthermore based on research regarding the advantages of beauty in different settings (Abel et al., 2005; Dion et al., 1972; Dion et al., 1974; Hamermesh et al., 1994; Jaeger, 2011; Langlois et al., 2000; Mobius et al., 2006) and regarding punishment in criminal settings (Ahola et al., 2009, 2010; Callan et al., 2007; Efran, 1974; Griffin et al., 2006; Mazella et al., 1994; McKelvie et al., 1993; Sigall et al., 1975; Stewart, 1980, 1985) we predict the following interaction effect: H4: People allocate significantly higher bonuses to attractive female employees, particularly in the presence (vs. absence) of fraud. As the literature review on gender and ethical leadership suggests, men and women might behave differently as leaders and therefore make different decisions regarding the punishment of a fraudulent employee. In addition, the mentioned research on gender and attractiveness shows men and women react differently to the appearance of others and based on findings by Vercamer (2012), we propose a three-way interaction between evaluator gender, fraud, and attractiveness of the employee. H5: Male evaluators compared to female evaluators treat more (vs. less) attractive female employees more leniently in the presence (vs. absence) of fraud. Finally, as research on ethical leadership is still in its infancy, we will look at the process of decision-making among leaders, in order to gain insight into the factors that influence the bonus decision. RQ3: What influences the process of decision-making, when deciding on bonuses as a reward vs. punishment for an employee and bonus to one self. 14

15 Study 1: stimuli-selection test Method In order to select two suitable female faces of different levels of attractiveness, we conducted a stimuli-selection test 1 using a within-subject design, in which 13 men and 8 women participated. The stimuli-selection test consisted of a survey regarding the attractiveness of 9 different women. Similarity in the type of the selected stimuli was guaranteed; between 20 and 30 years old and similar looks, e.g. blonde, longer hair. The female faces could be categorized as highly or lowly attractive. Next to perceived facial attractiveness we included additional within-subject variables. After all it is important that the perception of the women did not differ in how trustworthy, sociable and intelligent they look. The stimuli should mainly vary regarding attractiveness; one of the crucial independent variables being manipulated in the scenario-experiment later. The participants judged the nine pictures by appointing points on a likert-scale from 1 (not at all e.g. attractive) to 7 (very e.g. attractive). Respondents could also choose the neutral option, by appointing 4. The sample for the stimuli-selection test consisted of 21 respondents, 13 men and 8 women, gathered using a convenience sample. The data from this stimuli-selection test were analyzed quantitatively using SPSS. The mean age was almost 23 years old (M = 22.81, SD = 6.27, N = 21). The youngest participant was 17 years old, while the oldest was 49. Most of the respondents were students living in Leuven during the academic year Table 1 depicts the descriptive statistics for the attractiveness of the different pictures. Table 1. Descriptive statistics attractiveness stimuli-selection test pictures (N = 21) Photo 1 Photo 2 Photo 3 Photo 4 Photo 5 Photo 6 Photo 7 Photo 8 Photo 9 Mean SD Results When comparing the mean perceived facial attractiveness, picture six received clearly the highest score (M = 6.14, SD = 0.91), while three pictures scored between two and three (two = not attractive and three = rather not attractive) on the seven-point likert-scale to measure perceived attractiveness (photo one M = 2.48, SD = 1.12; photo five M = 2.57, SD = 0.93; photo eight M = 2.81, SD = 1.03). These last three pictures differed strongly on perceived facial attractiveness compared to photo six. Before conducting further analyses, we compared the mean scores for sociability, intelligence, and especially trustworthiness. As the scenario-experiment will portray a situation of fraud, it is important that both stimuli were not perceived differently regarding how trustworthy they look. On trustworthiness, picture five and six were rated closest to each other (photo five M = 3.57, SD = 1.53; photo six M = 3.29, SD = 1.10). Picture one and eight scored higher than five (rather trustworthy) on a seven-point likert-scale for perceived trustworthiness, and therefore were excluded from further analyses (photo one M = 5.43, SD =.81; photo eight M = 5.00, SD =.78). In addition, intelligence scores were comparable between picture five and six 1 Appendix A: the stimuli-selection pre-test 15

16 (photo five intelligence M = 3.00, SD =.89; photo six intelligence M = 3.86, SD = 1.11). Sociability was slightly different between picture five and six (photo five sociability M = 3.71, SD = 1.31; photo six sociability M = 4.90, SD = 1.00), but analyses were conducted to compare upper mentioned differences in order to ascertain the suitability of picture five as lowly attractive and picture six as highly attractive for the scenario-experiment. After comparing the different scores on perceived attractiveness, sociability, intelligence and trustworthiness, we decided to conduct the analyses of (co)variance between picture five and six. To measure the difference in means between the pictures, we used a within-subjects analysis of covariance. In SPSS Statistics 20 for Mac, we selected a repeated-measures general linear model test with dependent variables picture 5 (e.g. beauty) and picture 6 (e.g. beauty). We tested the difference in means for perceived attractiveness, intelligence, sociability and trustworthiness. Age and gender were included as covariates. The results showed a significant difference between photo five and six on perceived facial attractiveness (F(1, 18) = 13.58, p <.005, ηp2 =.43). Therefore, we can conclude the attractiveness of picture five (M = 2.57, SD = 0.93) is significantly lower than picture six (M = 6.14, SD = 0.91). Furthermore, as the experiment concerns fraud and cheating, there must not be a significant difference regarding the trustworthiness of the two women depicted in the two pictures beforehand. After an analysis of covariance between picture five and six on the dependent variable trustworthiness and covariates age and gender, we could not establish a significant difference between the perceived trustworthiness of both women (Photo five M = 3.57, SD = 1.54; photo six M = 3.29, SD = 1.10; F(1, 18) =.40, p >.83). This is an important finding that supports the use of photo five and six for the scenario-experiment. In addition, we checked the disparity between the two women regarding intelligence and sociability. Sociability did not differ significantly between the two photographs when controlling for age and gender (F(1, 18) = 1.35, p >.25). Perceived intelligence too, did not lead to any significant result (F(1, 18) =.47, p >.50). We can conclude photo five and six offered the best fit for the scenario-experiment. After controlling for age and gender of the evaluators, only the perceived attractiveness showed a significant effect of the photo manipulation (F(1, 18) = 13.58, p <.005). But also, apart from the very comparable looks, the women smile in a similar way (slightly open mouth, little part of teeth appear) and the head is positioned in the same direction. Besides, both women wear comparable amounts of make-up and the haircut and -color appear very comparable. Therefore photo five and six will allow a valid manipulation of attractiveness. Study 2: Scenario-experiment Method Sample Originally, more than one hundred adult men and women in the active labor force within Flanders during March 2013 took part in the scenario-experiment, a paper and pencil task. In the final sample of one hundred respondents, the mean age was almost 42 years old and the median reached 45 years (M = 41.95, SD = 12.24, N = 100). The minimum age was 20 and the oldest person in the sample was 68 years old. More than half of the respondents (58 out of 100) had experience as a leader. On average, the respondents with leadership experience had 13 years of experience (M = 13.10, SD = 10.45, N = 58). Almost one in five respondents (19%) had a 16

17 secondary school degree, while 42% held a professional or academic bachelor s degree. More than one quarter (26%) reached the master s level and 5% studied a master-after-master. In addition 7% followed a postgraduate program and 1 participant had a doctoral degree (1%, N = 100). The population consisted of adults in the Flemish workforce during March The participants were selected using a simple random sample within Flanders. A random sample offers the best opportunity to draw valid conclusions about the population. When every unit in the population has an equal chance of being selected, the sample will be representative for the population. In this way the results can be generalized towards the population. Therefore we randomly selected people living in two areas of the province of Antwerp, namely in Schilde and Turnhout and surroundings. In addition, some respondents took part while traveling by train between Brussels and Leuven, and Antwerp and Leuven. And finally, a small proportion of friends and relatives, unaware of the design and purpose of the research, took part and also gathered participants in their own neighborhoods spread throughout Flanders. In total 112 people participated in the experiment. We removed 12 respondents from the analysis based on an outlier analysis of the most important dependent variable (employee bonus), and insight into the research design. Therefore the final dataset consisted of 100 respondents. In total 49 men and 51 women were included in the analysis. Figure 1 A and 1 B show the bonus decisions in every cell in the experiment. Figure 1 A depicts the boxplot with the distribution for the bonus assigned in the experimental condition, while figure 1 B presents the boxplot of the control condition, including the outliers that were removed later. Figure 1. Boxplot: distribution employee bonus fraud condition (A) and control condition (B) before removing outliers A B The scenario-experiment consisted of four different conditions, which will be clarified in the next section discussing the design of the experiment. Participants were randomly assigned to one of the conditions. We printed and randomized the four different scenarios beforehand and handed them over to the participants independent of their background, sex, or other external factors. As we also included gender as a determinant of ethical leadership into the hypotheses, it is important that all conditions contained more or less the same amount of men and women, in order to make an accurate and correct comparison between the different groups and conditions. Previous research by Vercamer (2012) experienced difficulties with the equal distribution of men and women over the four conditions. For that reason, we checked the division after gathering three quarter of the data, and completed every condition with the needed gender to reach equal sample sizes. Eventually, the 17

18 high-attractive fraud condition consisted of 20 respondents with exactly ten female and ten male respondents. In the fraud condition picturing the less attractive team member, 14 men and 15 women took part. The control condition also showed an almost equal distribution between the sexes, with 12 men and 12 women in the highly attractive and 13 men and 14 women in the low attractive condition. Design The experiment was built up using a 2 (presence vs. absence of fraud) x 2 (high vs. low attractive picture) x 2 (evaluator gender) between-subjects design. We used two main independent variables to manipulate in the experiment; fraud of the employee and the employee s facial attractiveness. The experiment started with a general outline about the study and demographic control-variables including age, gender, experience as a leader and educational level 2. Subsequently respondents were asked to imagine themselves as the leader of a team in a bank and he or she received information about the team members and their performances. The participant was responsible for assigning bonuses to the employees he is leading, but the experiment only focused on team member B. In the control condition the information consisted of the team performance numbers, where team member B obtained the highest score in the team. In the experimental condition respondents were shown the same performance numbers as in the control condition, but in addition participants read that the high performance scores of team member B were obtained by unfairly boosting the score and hence this employee committed fraud. Following this information, depicting fraud or not, respondents saw a general file containing all relevant job information regarding team member B. The file also included a picture of team member B. This picture either presented photo five as team member B, a picture of the face of a low-attractive woman selected during the stimuli-selection test. Other respondents saw a very attractive woman in the role of team member B, when the file showed photo six. After the presentation of the general file, respondents in all conditions were asked to assign a bonus to the female team member. This bonus could not exceed the amount of 1000 euro. Thus, in the control condition respondents assigned bonuses to a less or more attractive team member B, without reference to any notion of fraud. In the experimental condition, respondents came across a situation of fraud conducted by a less or more attractive female team member. After the employee bonus decision, respondents assigned a bonus to the leader of the team, respectively him or herself. Here too, the amount was 1000 euro maximum. Furthermore, to investigate research question three, we included a decision-making process questionnaire. Respondents answered different questions, measuring their opinion regarding the employee s suitability, competences and attractiveness (later used as a manipulation check), how sure they were about their decision and in how far they preferred further information. The answers were recorded using a likert-scale from 1 (not at all) to 7 (very). In addition to demographic variables including age, gender and educational level, the scenario-experiment contained a control variable to measure the years of work-experience as a leader. To measure the certainty respondents reported regarding the bonus decisions, we created a new variable in SPSS using three questions in the questionnaire about the bonus decisions. We made a new factor certainty, using three items; the reported values regarding how certain respondents were about their decision, how easy they thought the decision was, and in how far they needed more information to make this decision. Respondents answered with a score from 1 (not at all) to 7 (very). Therefore, we reverse coded the need for information question. The first two question loaded.86 each, and the latter had a factor loading of.68 (α =.72), meaning the three questions are valid measurements for the factor 2 Appendix B: example scenario-experiment 18

19 certainty, as there is enough internal consistency. Finally, respondents were asked to fill out what they thought the research was about. These results were used to check their insight into the research design and remove participants who were aware of the topic. Compared to the master thesis study by Vercamer (2012), we altered the scenario-experiment regarding some aspects. First of all, the photos used in our study differed from last year s pictures of women. Now the variation clearly focused on the general attractiveness of the women, as they looked very much alike, smile and hold their head in a comparable way. Besides, we selected the two photos after an elaborated stimuli test and only differentiated between high and low attractive women instead of three levels of attractiveness. In addition, we included a measurement of trustworthiness, as the employees should not be perceived differently on this matter. Secondly, the context of work and giving bonuses differs from Vercamer s experiment (2012). We looked at the punishment of unethical behavior (fraud) in the banking sector instead of a clothing store. Furthermore, respondents in the present study also assigned a bonus to themselves. Finally, the present scenario-experiment clearly identified the unethical behavior as a situation of fraud, which implied less ambiguity compared to the previous study. For a clear overview of the full scenarioexperiment including the selected photos and scales, one can look at appendix B. Results Manipulation check Before conducting the main analyses, we executed a small manipulation check for attractiveness in order to verify the difference in perceived attractiveness in both the stimuli-selection test and the scenario-experiment. Table 2: perceived facial attractiveness low-attractive (LA) vs. high-attractive (HA) stimuliselection (pre-test) and scenario-experiment (exp.) LA pre-test (N=21) LA exp. (N=54) HA pre-test (N=21) HA exp. (N=43) Mean SD Table 2 presents an overview of the different perceptions of attractiveness of the two stimuli selected during the pre-test and used in the experiment. In both studies (within-subject and between-subject) both pictures are judged in a comparable way and in the same direction: one can be categorized as low attractive, while the second is perceived as more attractive. In the experiment, the attractive woman received lower scores. Therefore we looked at the scores in different conditions, presented in table 3. Table 3: perceived facial attractiveness control vs. experimental conditions, low-attractive (LA) vs. high-attractive (HA) LA control (N=26) LA fraud (N=28) HA control (N=24) HA fraud (N=19) Mean SD

20 A one-way ANOVA with dependent variable the manipulation check for attractiveness and independent variable the attractiveness manipulation showed a significant effect of the manipulation on the perceived attractiveness (F (1, 95) = 29.92, p <.001). The highly attractive picture, selected during the pre-test, was also during the experiment judged as more attractive compared to the low attractive stimulus. The manipulation of attractiveness was thus successful. Furthermore, we conducted a 2 (presence vs. absence of fraud) x 2 (HA vs. LA employee) x 2 (evaluator gender) ANOVA with the manipulation check for attractiveness as dependent variable. The results still showed a main effect of the manipulation of the picture (F(1, 89) = 33.46, p <.001, n2 =.27); when the experiment showed the highly attractive picture, respondents rated the employee significantly more attractive than when the file presented the low-attractive team member. Also, we discovered a main effect of unethical behavior (F(1, 89) = 28.89, p <.001, n2 =.25). When caught committing fraud, the female employee was rated significantly less attractive (M = 2.91, SD = 1.80) compared to the control condition (M = 4.60, SD = 1.59). And the final main effect was the evaluator s gender (F(1, 89) = 5.90, p <.02). Compared to female participants (M = 3.43, SD = 1.92), men perceived the female employee significantly more attractive (M = 4.15, SD = 1.81), independent of the presented stimuli (high or low attractive), or the (un)ethical behavior of the team member. In addition, the ANOVA showed a significant interaction effect between the manipulation of fraud and gender; men and women differed in their attractiveness judgments when the employee committed fraud (F(1, 89) = 5.74, p <.02). Women significantly perceived the female team member as less attractive when this employee was fraudulent (M = 2.21, SD = 1.56). Men judged the attractiveness of the fraudulent team member significantly higher (M = 3.65, SD = 1.77). For that reason, we can conclude men and women do perceive female attractiveness differently. Women seem to be more critical and do not acknowledge other women s attractiveness that much as men do. This also points in the direction of the proposed hypothesis that men and women might judge differently regarding the bonus they assign to the employee. If the different perception of attractiveness between men and women also influences bonus decisions will be tested in the next section. Main analyses a. Bonus allocation We investigated the effect of an independent variable with two levels (fraud or no fraud, low or high attractiveness of team member B, and gender of the evaluator) on a dependent variable; the amount of bonus assigned to this certain employee. To compare the mean bonus assigned in different conditions with different respondents (between-subjects design) we used a univariate analysis of covariance. The null hypothesis (H0) stated there was no difference between the means of the dependent measure in each level of the independent variables. As independent variables in the ANCOVA we included (1) employee attractiveness, (2) presence/absence of fraud, and (3) evaluator gender. As we wish to take into account the amount of variance in the allocated bonus that is attributed to the demographic variables age, educational level, and experience as a leader, we included these as covariates. This will give a clear measure of how much variance in bonus is attributable to the manipulation of fraud and attractiveness, and the gender of the decision-maker. As ANCOVA compares the means between different groups, we must first consider the different amounts of bonuses assigned, depending on the three main independent variables (attractiveness, fraud and evaluator s gender). The mean bonus assigned to the employee in the control condition with the less attractive team member was 820 euro (M = , SD = , N = 27). On average men assigned 881 euro (M = , SD = , N = 13), while women only gave (SD = , N = 14) euro in the control condition with the less attractive employee. In 20