An analysis of altruism through deceptive behavior under conditions of anonymity and identification

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Faculty of Business and Economics

An analysis of altruism through deceptive behavior

under conditions of anonymity and identification

Marcos Silva 15/08/2016

Master thesis MSc Economics

Specialization Behavioral Economics and Game Theory 15 ECTS

Thesis supervisor: Ailko van der Veen

Student number: 11087285 E-mail address: marcos.miguelsilva@student.uva.nl

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Abstract

In this research, we perform a laboratory experiment to test (1) the difference in the amount of unethical behavior displayed when such behavior benefits oneself, as opposed to benefiting an anonymous third party, and (2) whether implementing the element of identity-revelation in the latter case induces higher levels of unethical behavior, by evoking reputational concerns and the associated norm of reciprocity. We found that the amount of unethical behavior is significantly higher when it benefits oneself compared to when it benefits an anonymous third party. However, in the latter case, and when the identity of the actor is made known to the beneficiary of his actions, the amount of unethical behavior displayed is not statistically significantly different from zero.

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1. Introduction

We live in a world where instances of fraud, corruption, and other forms of unethical behavior occur frequently and are often highlighted in the media. When such behavior results in a material payoff for the actor himself, it is obvious that the behavior is motivated by self-interest. Wiltermuth (2011) found that people are more likely to engage in unethical behavior when the benefits of such behavior are shared with someone else, as opposed to only benefiting themselves. Moreover, the research found that people categorize the former case as being less morally wrong than the latter, and propose that people are able to more easily discount the moral concerns of their behavior when the spoils are split with someone else (see also Erat and Gneezy, 2012; Gino and Pierce, 2010). However, since research has suggested that people do actually care about the outcome of others (e.g., Loewenstein, 1989), Gino et al. (2013) conducted a set of experiments to study how these two mechanisms (benefiting others to more easily justify one’s dishonesty versus benefiting others out of concern for their outcome) work to affect dishonesty. In experiment 3 of Gino et al. (2013), where they try to differentiate these two effects, they found that 79% of participants cheated when only they themselves benefited from it and 88% of participants cheated when only someone anonymous to them benefited from it. The fact that they observed cheating in the treatment where only an anonymous third party benefited from it lead them to conclude that “this finding suggests that people do care about the benefits of their actions for others.”

However, the observed cheating and high share of participants that cheated in the other-only-payoff condition of the aforementioned experiment are likely a result of the experimental procedure. In the experiment, cheating occurred by omission rather than engagement of action, and there were several rounds where they could do so. This probably made it easier for participants to cheat and they probably did more so than if they had to act to cheat in a single round. Hence, the extent to which participants cheated due to concern for their counterpart’s outcome remains ambiguous. It is the present research’s purpose to address this question with higher validity, and to test and compare, in the same experimental context, altruism that derives from actual genuine selflessness, and altruism that derives out of the evocation of the widely established and deeply ingrained norm of reciprocity. The latter will be attempted by implementing the reputation cue of identity-revelation. Hence, we formulate our research question:

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Do people engage in unethical behavior when it benefits someone else, and how does it differ under anonymity versus identification?

In attempting to answer this question, this thesis is structured as follows: First, we shall do a review on relevant literature and research done so far. We will begin by analyzing the origins and implications of homo economicus, as it is the most widely used abstraction of human behavior in mainstream economic models. We will pay particular attention to the assumption of self-interested behavior, and review some well-known economic theories that challenge it. We argue that self-interest lies behind of most of people’s behavior, even when this is not apparent. After that, we shall discuss the nature of altruism and how it can evolve out of self-interest, as it emerges under conditions where, on average, it increases personal fitness. Thus, an evolutionary perspective will be adopted. Associated to this, we will also discuss the concept of reciprocity and the power of reputation in shaping behavior. As we shall see, even minor reputation cues are enough to significantly change behavior. We will also discuss social distance as a mediator of altruistic behavior and how identity-revelation relates to this. To complete our literature review, we will address the motivation behind deceptive behavior and how people deal with the tension of ethical dilemmas. After this, we shall describe our method of research and formulate hypothesis based on our literature review. This will be followed by a description and analysis of our results, in order to test our hypothesis. We will then finish with a discussion of our results in light of our research question, also pointing to research limitations and potential venues for future research.

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2. Literature Review

2.1. Homo economicus

2.1.1. Origin and applications

The most widely accepted and taught microeconomic theories belong to the domain of neoclassical economics, which is largely based on the concept of economic man, or homo economicus. According to the contemporary account of this concept, humans are rational, strictly selfish agents with well-defined exogenous preferences which they pursue optimally (Gintis (2000) provides a comprehensive description of

homo economicus). Homo economicus has been the subject of much criticism by the large

body of empirical studies that show that many people display other-regarding behavior (e.g., Henrich et al., 2001; Fehr and Gächter, 2000), as well as common cognitive biases and other so called “anomalies” (e.g., Kahneman et al., 1991; Tversky and Kahneman, 1975). Studies on other-regarding behavior, as well as on unethical behavior, focus particularly on the “strictly selfish” assumption of homo economicus. They argue that their findings reject such assumption, because people do not display completely self-interested behavior (e.g., Henrich et al., 2001), or because people don’t lie, or don’t lie as much as they could, for the pursuit of their best possible material outcome (Gneezy, 2005). Though it is true that humans are not literal personifications of homo economicus, it can be argued that much of this criticism is based on a too narrow view of self-interest. This shall be discussed in more detail in the next section. Given the antagonism between the predominant use of homo economicus in mainstream economic theories and its challenged status in the fields of behavioral and experimental economics, it is useful to review its origin and some of its applications in mainstream economic theories.

Though the terms ‘economic man’ and ‘homo economicus’ were never used by him, it was John Stuart Mill (1836) who first described this concept as a useful abstraction of humans for economic analysis (Persky, 1995). In Mill (1836), political economy is described as concerned with man “(…) solely as a being who desires to possess wealth, and who is capable of judging the comparative efficacy of means for obtaining that end.” Mill’s hypothetical subject is even bestowed with four distinct desires: accumulation, leisure, luxury, and procreation (Persky, 2005). Procreation is rarely mentioned as one of

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approved that when it came to procreation, even homo economicus might not be all that rational (Persky, 2005). Mill’s central point for using this homo economicus’ modest psychological complexity was to show how institutions shaped behavior, without risking indeterminacy. Indeed, Mill’s homo economicus was not intended to be a complete representation of humans, nor a “money-making animal” as some of his critics claimed (Ingram, 1888), but to be used as a guinea pig in different institutional settings (Persky, 2005). This methodology still remains pivotal in modern economics.

Well-established theories based on the assumptions of homo economicus are John Nash’s (1950) Nash equilibrium; Kenneth Arrow’s (1962) contract theory, where contracts written in a world of asymmetric information cause principal-agent problems such as adverse selection; and George Akerlof’s (1970) theory on asymmetric information and market for lemons, which assumes that used car sellers will lie about the quality of their car if it is in their best interest to do so.

2.1.2. Defying selfish behavior

In this chapter, we shall focus on some works that challenge the self-interested assumption of homo economicus, given the attention given to it in the literature on other-regarding behavior and on unethical behavior. We will also argue how behavior that is usually perceived as opposed to this assumption can actually be considered as self-interested, if we adopt a broader perspective of this term.

Both Kenneth Arrow and George Akerlof, mentioned above for their well-known theories based on the concept of homo economicus, later also defied this concept. Arrow (1972) reformulates individual utility by including in it the welfare of others. His classification of utility is not exhaustive or exclusive, but consists of three classes: (1) Individual welfare depends both on one’s own satisfaction and on the satisfaction others; (2) Individual welfare depends on one’s own satisfaction and on one’s own contribution to the satisfaction of others; (3) Individual welfare depends on one’s own satisfaction, but there is an implicit social contract that forces one to act in favor of others, such that the satisfaction of all is enhanced. Though this reformulation of utility seems to defy homo

economicus’ strict selfishness, the fact is that the satisfaction of others in (1) and the

personal contribution to the satisfaction of others in (2) are taken into account to maximize individual utility. So, even though the means by which utility is maximized are not strictly selfish, the end, which is individual utility itself, can be regarded as a selfish

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motive. Moreover, if we ask ourselves the ‘why’ of such behavior, our attention must shift to evolutionary explanations, which argue that such altruistic behavior evolved because it increases inclusive fitness1_{on average (Barclay, 2011). We shall address this} in greater detail in the next chapter. In (3), Arrow (1972) refers to social norms shaping behavior to achieve ends that are not completely selfish. However, acting against social norms often results in the detriment of personal reputation and in negative feelings of guilt or shame (Charness and Dufwenberg, 2006). If such costs (even if not material) are felt more strongly than the benefits of acting against the implicit contracts of social norms, then it is indeed in one’s self-interest to comply with such social norms.

Akerlof (1982) developed the fair wage hypothesis, where wages are partly dependent on gift exchanges between the employer and employees, and do not correspond to the market-clearing wage price. His gift-exchange economy is sensitive to norms, which contrasts the neoclassical economy based on homo economicus, a being insensitive to norms. Besides the points made before about the negative effects of not complying with norms, one can also argue that such theory is consistent with selfish actors who have an understanding of human motivation (the employer wants productive workers and the employees want to be paid according to what they believe is fair).

In addition to the aforementioned works, a plethora of empirical studies (e.g., Henrich et al., 2001) describe the occurrence of altruistic behavior, which is counterintuitive if we assume people to behave according to homo economicus. But according to this notion, such behavior makes sense if there are expected gains that outweigh the respective costs. Expecting benefits out of altruistic behavior defies the definition of altruism itself, which we shall address in the following chapter.

Where it comes to deceptive behavior, for homo economicus, no negative outcome should be associated with lying per se (Gneezy, 2005). However, several studies (e.g., Gneezy et. al, 2005; Mazar et. al, 2008; Gino et. al, 2013) have demonstrated that people are not indifferent towards the mean by which they achieve their end, and will not behave in a payoff-maximizing way if it involves lying. This suggests that there is a psychological cost associated to lying. If we broaden the ‘self-interested’ assumption to non-material benefits and costs, then we can argue that people are in fact acting in a selfish

1_{The inclusive fitness of an individual corresponds to the combined reproductive success of that}

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maximizing way. The motives behind deceptive behavior shall be further discussed ahead.

2.2. Altruism

2.2.1. Conceiving altruistic behavior and psychology

Altruism is generally conceived as a form of behavior that benefits someone else at the cost of the actor (e.g., Gintis et al., 2003). It is usually addressed as taking one of two forms: pure and impure. With pure altruism, one does not expect to derive any utility from benefiting someone else (Batson, 2014). Impure altruism, however, is altruistic behavior from which the actor does, or at least expects, to derive some kind of utility. This utility can be derived, for instance, from self-esteem boost (Crocker and Park, 2004) or from reputational gains (Barclay, 2011). Pure altruism is largely criticized, particularly in economics, because it stands in sharp contrast with the economists’ model of the self-interested actor. Impure altruism, however, does not contradict this model, making it a more credible account of altruism that can be sustained when considering an evolutionary approach. In fact, if we wish to understand the motives behind altruistic behavior and how a psychology for helping can evolve, we must adopt an evolutionary approach to it. The next section is mainly intended to this, which will enable us to better interpret the results from our research.

In the science of ethology and the study of social evolution, altruism corresponds to behavior that increases the fitness2_{of another individual while decreasing the fitness} of the actor (Bell, 2008). From an evolutionary perspective, this behavior is very puzzling, given that by definition, it reduces personal fitness. However, we are confronted with altruistic conducts every day. Evolutionary researchers suggest that helping behavior exists because it increases inclusive fitness on average, i.e., it evolved because it brings more net benefits than not helping would (or would have done so in ancestral environments) (Barclay, 2011). Accordingly, empathy might have evolved because it resulted in the empathic person being reciprocated with better behavior (Frank, 1988). This, however, also leads people to sometimes help others, such as complete strangers, who will never be able to reciprocate. So, even though we are able to make adaptive judgements of who is worthy of being helped, (e.g., Stewart-Williams, 2007; Majolo et

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al. 2006), our decision making process will always be subject to errors (Haselton and Buss 2000; Nesse, 2005), such that not every moment of altruism will increase fitness. This shows how altruistic behavior is not always rational per se, but it does derive from self-interest.

According to evolutionary theory, with the evolution of altruistic behavior, also a psychology for altruism will evolve. The reinforcement of such behavior and the associated reputational gains cause, given enough time, the evolution of cooperative sentiment (Barclay, 2011). In the next section we will discuss the influence of reputation in shaping human behavior.

2.2.2. Reputation and reciprocity

Reputation is related to the concept of reciprocity. The latter is usually perceived as taking one of two forms: direct reciprocity or indirect reciprocity. With direct reciprocity, the receiver of a helping act reciprocates his benefactor with another helping act; with indirect reciprocity, the reciprocator is someone different from the recipient. Though reputation is usually related to indirect reciprocity (e.g., Nowak and Sigmund, 2005), one can easily argue that it is also related to direct reciprocity: if the recipient of the helping act does not have the opportunity to reciprocate immediately, at least the actor has established a reputation for himself such that the recipient will more likely reciprocate once the opportunity presents itself in the future. Even though Barclay (2011) also relates reputation to indirect reciprocity, he himself states that the reputational benefits can come not only from those who observed or heard about the help, but also from the recipients of it.

People are more willing to help others the stronger and more likely the reputational consequences of doing so (Barclay, 2011), and such prediction has been confirmed by several experimental studies. For instance, people give more money in public good situations when their identities and contributions are revealed to others. This has been registered both in field experiments (Alpizar et al. 2008; Soetevent 2005) as well as in laboratory experiments (Rege and Telle 2004; Van Vugt and Hardy, 2009). However, our decision-making behavior is based not only on explicit propositional information, but is also largely based on implicit cues and inferences built on limited and outside of consciousness information (see Haidt, 2001). Accordingly, several studies have registered that people react strongly to implicit reputation cues, which reveals the power

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of reputation in shaping people’s behavior. For example, Haley and Fessler (2005) found that the presence of an image of stylized eyes induced nearly twice as many participants to give money to their partners in dictator games. Similar results have been accomplished by other studies (e.g., Mifune et al., 2010). Bateson et al. (2006) showed the robustness of such cues in a real world setting: People paid nearly three times more money for drinks on an “honor system” when a stylized eyes image was displayed above the money jar, as opposed to when flowers were displayed.

In the present research, we explore the reputation cue of identity-revelation, and test whether it is strong enough to induce people to behave more unethically, when doing so benefits someone else. The next section expands on altruistic behavior in light of the social distance theory.

2.2.3. Social distance as a mediator of altruistic behavior

Hoffman et al. (1996) studied how instructional and procedural manipulations in dictator games, intended to affect social distance, have an impact in the amounts given by the dictators. Social distance3 was varied by manipulating the dictators’ degree of social isolation. They found that decreasing the degree of the dictators’ social isolation led to higher offerings by dictators, and argue that the significance of social isolation is that is eliminates all suggestion of the quid pro quo of reciprocity. Decreasing the degree of social isolation, hence decreasing social distance, activates individuals’ dispositional knowledge about the social norm of reciprocity and their associated reputation, even though dictator games do not allow for reciprocal behavior by design (Hoffman et al., 1996).

Bohnet and Frey (1999) critique Hoffman et al.’s (1996) interpretation of social distance, arguing that social distance influences other-regarding behavior independently of any norms of social exchange. They argue that by decreasing social distance, the “other” becomes an “identifiable victim” (Schelling, 1968) towards whom we show concern. To distinguish between reciprocity-based and identifiability-based other-regardedness, Bohnet and Frey (1999) used a dictator game with an anonymous condition that was compared with a one-way identification where recipients identified themselves to their respective dictators through numbered cards; a one-way identification where

3_{Hoffman et al. (1996) define social distance as the degree of reciprocity that subjects believe exists}

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recipients identify themselves to dictators by telling their names, majors, origins, and hobbies; and a two-way identification where dictators and respective counterparts visually identify themselves. They found that offers were higher in the one-way identification treatments than in the anonymous treatment, and argue that identification, not reciprocity, is responsible for the results under different social distance conditions.

Hoffman et al. (1999) replied to this critique, stating that Bohnet and Frey’s (1999) results do not contrast their own arguments. They argue that identification and the possibility of reciprocity are intimately connected, in the sense that “the higher the probability that you can be identified by your counterpart, the higher the probability that you will give to your counterpart an amount consistent with a social norm of reciprocity.”

Hoffman et al.’s (1996) theory that subjects bring their ongoing repeated game experience and reputations from the world into the laboratory, revealing “unconscious, preprogrammed rules of social exchange” is consistent with the evolutionary psychology notion that we are hard-wired to help and are extremely sensitive to reputation cues, as discussed in the sections above. In this thesis, we explore this sensitivity to reputation cues and the associated norm of reciprocity, and test whether it is strong enough to induce subjects to engage in more ‘unethical altruism’4. In order to better understand and predict such behavior, we shall discuss the nature and implications of deceptive behavior.

2.3. Unethical behavior

2.3.1. Understanding deceptive behavior

Ethics is the branch of philosophy that deals with moral principles, and the ethicality of an action can be analyzed according to the moral principles it follows, so that it can be regarded as “right” or “wrong” behavior. In this thesis, we deal with deceptive behavior, i.e., lying, which is generally regarded as unethical or “wrong” behavior. In spite of this, lying is a part of many economic interactions (it occurs, for instance, as a result of agents’ self-interested behavior in situations of adverse selection), and a huge body of empirical studies shows that such behavior occurs very frequently in everyday life (e.g., DePaulo and Kashy (1998); Camden et al., 1984; DePaulo et al., 1996; Hample, 1980; Lippard, 1988). So when do people lie?

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On one side of the spectrum, if we assume that individuals follow a Kantian categorical imperative (Kant, 1787), no one would ever lie. On the other side of the spectrum, if we assume that individuals act like homo economicus, in the purely materialistic sense of the concept, then people would lie whenever it would be materially beneficial for them. Moreover, there would be no negative consequence associated with lying per se. Everyday experience shows us that people do not follow any of these extremes. Recent research has shown that when individuals have the opportunity to lie and benefit from it, with minimized probabilities of getting caught, they will do so but not as much as they could (e.g., Ayal and Gino, 2011; Gino et al., 2009). This suggests that there is a psychological cost associated with lying, which has been investigated and supported by several studies (e.g., Gino et al., 2009; Mazar et al., 2008). This trade-off between material benefits and non-material costs of lying is discussed in the following section.

2.3.2. Coping mechanisms

Barkan et al. (2012), through a series of experimental studies, reveal that people’s moral values are inconsistent with their unethical conduct, i.e., people frequently act in ways that they themselves condemn morally. They defined this as ethical dissonance, and their findings suggested that people resource to coping mechanisms to deal with the resulting tension.

Several studies have shown that people who find themselves in ethical dilemmas, i.e., they can act ethically and preserve their positive self-image or they can act unethically and improve their self-interest, often resort to self-serving manipulations of their moral standards in order to engage and justify their unethical behavior (e.g., Gino et al., 2009; Mazar and Ariely, 2006). Mazar et al. (2008) have shown that people do so enough to profit but also enough to delude themselves of their positive self-image. They denote this process as self-concept maintenance theory. In accordance to this, recent research has shown that people rationalize their unethical behavior in several ways (e.g., Gino and Ariely, 2012; Shalvi et al., 2011). Wiltermuth (2011) showed how people engage in more unethical behavior if besides to themselves, they also benefit others by doing so, since they can more easily justify their actions to themselves. Gino et al. (2013) attempted to differentiate the extent to which such unethical behavior happens because it makes it easier to justify to oneself, as opposed to happening out of actual concern for the outcome

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of others. As was referred in the introduction, they found that a very large percentage of participants (88%) cheated on a task that only benefited someone anonymous to them, and concluded that people do actually care about the outcome of others. These results seem to contradict the social distance theory of altruism, given that participants were completely anonymous towards their counterparts. Moreover, in their experiment (experiment 3), participants cheated through omission of action rather than action, and they had several rounds where they could do so. This procedure very likely induced artificial high levels of cheating. Muraven and Baumeister (2000) showed that self-control resembles a muscle, in the sense that exerting self-self-control depletes the amount of strength available for subsequent self-control efforts. In addition to this, Gino et al. (2011) explicitly showed that self-control depletion reduces people’s moral awareness, thus promoting unethical behavior. Hence, having to engage in action in initial rounds in order to avoid behaving unethically very likely reduced participant’s self-control, thus inducing them to behave unethically in later rounds. This issue was not addressed in Gino et al.’s (2013) study.

In the present study, we employ the same task used by Gino et al. (2013) in their experiments 1 and 2, where participants had a single round where they had to act in order to behave unethically. Thus, we add consistency to their research.

3. Methodology

In this chapter, we shall discuss the experimental sample, design, and procedure employed to answer our research question. After that, based on our literature review, we formulate the hypotheses we plan to test.

3.1. Sample and design

The experiment consisted of two sessions, with two treatment groups in the first session and one treatment group in the second session. A between-subject design was employed, such that no participant participated in more than one treatment group.

In the first session, twenty four students of the University of Amsterdam participated in the study for potential pay (money they could earn from the experimental procedure). They were randomly assigned to one of two treatments, which were tested simultaneously: other-payoff-anonymity treatment (8 male; Mage = 24.33, SD = 1.83),

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towards whom they remained anonymous; and other-payoff-identity condition (6 male; Mage = 25.91, SD = 3.59), where their actions in the experiment decided the payoff of

another random participant towards whom their identity was revealed post hoc. Each condition consisted of twelve participants.

In the second session, twelve participants of the University of Amsterdam (7 male; Mage = 24.25, SD = 1.71) participated in the study for potential pay. They were assigned

to the self-payoff-anonymity condition, where their actions in the experiment decided their own payoff. Their actions remained anonymous towards other participants.

3.2. Procedure

In all three treatments, every participant received a full set of instructions for the experiment, so that they knew exactly what it involved. Each participant received an unidentified test sheet containing 20 matrices and a separate score sheet on which to later write down how many matrices they solved correctly. Each matrix contained a different set of 12 three-digit numbers, and participants had 5 minutes to find the only two numbers per matrix that summed up exactly to 10 (see Fig. 1).

Fig. 1. A sample matrix of the adding-to-10 task.

This task was selected because, as Mazar et al. (2008) pointed out, it is a search task for which the solution, once found, can be unambiguously confirmed to be the right one by the respondent without the need of a solution sheet and the possibility of a hindsight bias (Fischhoff and Beyth 1975). Given that all participants were university students attending English-taught degrees, they were all fluent in English and could add up to 10.

Participants were informed that each matrix correctly solved corresponded to €0.50, and that the total amount earned corresponded to the payoff of either themselves or of some other random participant, depending on the treatment they were in. However, after the 5 min task, participants folded their test sheet and placed it in a bag that was passed around by the experimenter, and were instructed to write down the number of matrices

5.64 2.85 9.48 1.68 9.52 2.15 6.71 4.36 1.67 8.1 5.48 8.91

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they solved correctly on a score sheet. It was the self-reported score on the score sheet that counted as the actual payoff. Thus, participants had the opportunity to cheat by misreporting the number of matrices they solved correctly, and consequently influence the corresponding payoff. This matrix-solving task with the opportunity to actively cheat in a single round is the same as the one employed by Gino et al. (2013) in their first two experiments.

The test sheets were unidentified and participants were instructed to fold them twice before placing them in the bag in order to have the test sheets appear anonymous to the participants (so that they would not deter from cheating because they expected someone to find out). However, every test sheet was the same except for a single three-digit number in one of the matrices, which was unique for each participant. By knowing beforehand which test sheet corresponded to which desk, the experimenter was able to match each participant’s test sheet with their score sheet, and directly measure the difference between self-reported and actual score.

In the other-payoff-anonymity condition, participants’ self-reported score corresponded to the payoff of another randomly selected participant towards whom they remained anonymous. Their own payoff corresponded to the self-reported score of a different participant. In the other-payoff-identity condition, participants’ self-reported score corresponded to the payoff of another randomly selected participant, towards whom they had to personally deliver their score sheet. Their own payoff corresponded to the self-reported score of a different participant. In the self-payoff-anonymity condition, each participant’s self-reported score corresponded to their own payoff. Their scores remained anonymous to other participants. In each experimental session, one participant was randomly awarded to have his/her payoff converted into money.

In the context of this experiment, behavior is classified as in Table 1: Table 1. Classification of possible behavior in the experiment.5 a. Self-reported score - Actual score > 0 Unethical behavior b. Self-reported score - Actual score = 0 Ethical behavior c. Self-reported score - Actual score < 0 Damaging behavior

5_{It is noted that in the context of this experiment, damaging behavior is, technically, also unethical}

behavior. However, for classification purposes, we generalize over reporting one’s score as unethical behavior, as under reporting is not expected to occur.

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3.3. Hypotheses

In the previous chapter, we discussed how individuals in ethical dilemmas do not act in a way that maximizes their material payoff, but they also do not act entirely ethically. Instead, they behave unethically just enough to profit from it and just enough to preserve a positive self-image. Moreover, experimental studies on unethical behavior (e.g., Mazar et al., 2008; Gino et al., 2013) have shown that people lie according to this prediction if only they themselves benefit from it.

However, in Gino et al.’s (2013) experiment 3, they found that the share of participants that cheated varied by condition (chi-square (2, N = 128) = 7.07, p < .05): 79% of participants cheated when only they themselves benefited from it, and 88% of participants cheated when only someone anonymous to them benefited from it. In addition to this, they found that the amount of cheating (unethical behavior) did not differ significantly between these two conditions (p = .85). Following our literature review, these results seem very artificially induced and counterintuitive. As discussed, under anonymity, i.e., in social isolation, one’s dispositional knowledge of the norm of reciprocity is minimal, so one’s incentive to help a third party, especially through unethical behavior, should be minimal. Hence, we formulate our first two hypotheses:

Hypothesis 1: The share of participants that show unethical behavior is larger when they themselves benefit from it, compared to when someone anonymous to them benefits from it.

Hypothesis 2: Participants show more unethical behavior when they themselves benefit from it, compared to when someone anonymous to them benefits from it.

Following our literature review on altruistic behavior, it seems very unlikely that such behavior manifests itself as a blind concern for the outcome of others. Rather, helping behavior is likely to have evolved because it brings, on average, more benefits than not helping would, given that it is reciprocated in times of need. This suggests that there is a selfish agenda behind altruism and, as we have discussed, the corresponding adaptive cooperative sentiment, can be easily triggered with minimum incentives. In order to compare these two views of altruism, we will compare the results of unethical behavior between the other-payoff-anonymity treatment and the other-payoff-identity treatment. If people manifest altruism as an actual concern for the benefits their actions

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have on them, then there should be no difference in the unethical altruism displayed between these two treatments. However, according to our literature review, this seems unlikely. Knowing that one’s identity will be revealed to the beneficiary of one’s actions reduces the existent social distance and should, thus, increase other-regarding behavior by the actor. This manipulation is interesting because in real world settings, one is more likely to engage in an altruistic act if he/she can be identified by the recipient of the help (Barclay, 2011). Moreover, as we have discussed, simple reputation cues are enough to trigger higher levels of altruistic behavior. Hence, we formulate our third and fourth hypothesis:

Hypothesis 3: The share of participants that show unethical behavior that benefits someone else is larger when the identity of the actor is revealed to the beneficiary, compared to when the actor remains anonymous towards the beneficiary.

Hypothesis 4: Participants show more unethical behavior that benefits someone else when the identity of the actor is revealed to the beneficiary, compared to when the actor remains anonymous towards the beneficiary.

Finally, following Shu et al.’s (2011) research showing that participants that cheat are likely to be more motivated to report that cheating is not very morally wrong, we formulate our third and final hypothesis:

Hypothesis 5: Participants that show unethical behavior perceive it to be more ethical than those who do not.

4. Results

In this chapter, we shall first give an overview of the experimental results by presenting some descriptive statistics. After that, we shall analyze the results according to the hypotheses formulated in the previous chapter: Hypotheses 1 to 4 will be analyzed in the ‘Unethical behavior’ section, and hypothesis 5 will be analyzed in the ‘Perceived ethicality of cheating’ section.

4.1. Descriptive statistics

In the figures 1 and 2, and in the tables 2 and 3 below, we can see the descriptive statistics of the experiment. As was described in the previous chapter, a participant shows

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unethical behavior whe he/she reports a number of correctly solved matrices higher than the actual number. In this study, we employ unethical behavior as a variable corresponding to the difference between these two amounts, i.e., the number of over reported matrices solved. Before dwelling into the descriptive statistics, it is worth mentioning that every participant answered in the question sheet at the end of the experiment (see appendix I) that they were aware of the opportunity to misreport their score.

Fig. 1. shows us that 50% (6/12) of participants in the self-payoff-anonymity treatment behaved unethically, whereas only 16,7% (2/12) and 8,3% (1/12) behaved unethically in the other-payoff-anonymity and other-payoff-identity treatments, respectively. At first sight, these results seem to support hypothesis 1, but not hypothesis 3. Looking at Fig. 2., we see that participants solved, in total, 99 matrices in the self-payoff-anonymous treatment, 100 matrices in the other-payoff-anonymity treatment, and 113 in the other-payoff-identity treatment. Unethical behavior in these three treatments was of 33, 2, and 14 matrices, respectively. Though the amount of unethical behavior was considerably larger in the identity treatment compared to the other-payoff-anonymous treatment, only one participant cheated in the former treatment (by fourteen matrices), whereas two participants cheated in the latter treatment (by one matrix each). Tables 2 and 3 show the descriptive statistics of the actual number of correctly solved matrices and of unethical behavior, respectively.

Fig. 1. Number of participants that show ethical behavior versus the number of participants that show unethical behavior, by experimental treatment.

0 2 4 6 8 10 12

Self-payoff-an. Other-payoff-an. Other-payoff-id.

N u m b e r o f p ar tici p an ts Treatment

Participants that show ethical behavior Participants that show unethical behavior

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Fig. 2. Actual versus reported number of matrices solved, by experimental treatment.

Table 2. Descriptive statistics of the actual number of solved matrices, by treatment. Actual number of solved matrices n Mean (SD) Min Max Median

Total sample 36 8.67 (4.61) 0 18 8 Self-payoff-anonymity treatment 12 8.25 (5.12) 1 18 6 Other-payoff-anonymity treatment 12 8.33 (4.54) 1 15 8 Other-payoff-identity treatment 12 9.42 (4.46) 0 16 9.5

Table 3. Descriptive statistics of unethical behavior, by treatment.

Unethical behavior n Mean (SD) Min Max Median

Total sample 36 1.36 (3.49) 0 15 0 Self-payoff-anonymity treatment 12 2.75 (4.31) 0 15 1 Other-payoff-anonymity treatment 12 0.17 (0.39) 0 1 0 Other-payoff-identity treatment 12 1.17 (4.04) 0 14 0 0 20 40 60 80 100 120 140

Self-payoff-an. Other-payoff-an. Other-payoff-id.

N u m b e r o f m atr ic e s so lv e d Treatment Actual Reported

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4.2. Unethical behavior

In this segment, we will test the first four hypotheses formulated in the previous chapter, which all relate to unethical behavior.

In order to test hypothesis 1: The share of participants that show unethical behavior

is larger when they themselves benefit from it, compared to when someone anonymous to them benefits from it; we test if there is a significant difference between the share of

participants that cheated in the self-payoff-anonymity treatment and in the other-payoff-anonymity treatment. Given that we are dealing with small sample sizes, we use a Fisher’s exact test, as opposed to a chi-square test. In accordance with what was speculated in the descriptive statistics section, we reject the null hypothesis that the share of participants that show unethical behavior in the self-payoff-anonymity treatment is the same as in the other-payoff-anonymity treatment in favor of the alternative hypothesis that the former is larger than the latter, at a 10% significance level (p = .097). Thus, we do not reject our hypothesis 1.

To test hypothesis 2: Participants show more unethical behavior when they

themselves benefit from it, compared to when someone anonymous to them benefits from it; we will test the null hypothesis that the amount of unethical behavior in the

self-payoff-anonymity treatment is the same as in the other-payoff-self-payoff-anonymity treatment. A two sample t-test would be adequate for this if each of our treatments were made of sample sizes larger or equal to thirty. However, our treatment groups are composed of only 12 participants each. Hence, we must first test for the normality of unethical behavior in both the self-payoff-anonymity and other-payoff-anonymity treatments, for which we use a Shapiro-Wilk test for normality. We reject the null hypothesis that unethical behavior is normally distributed in the self-payoff-anonymity treatment and in the other-payoff-anonymity treatment, both at a 1% significance level. Therefore, we assume that this data is not normally distributed, and we must thus resort to a Mann-Whitney U test, also known as a Wilkoxon rank-sum test, to test our hypothesis 2. Using this test, we reject the null hypothesis that unethical behavior in the self-payoff-anonymity treatment is the same as unethical behavior in the other-payoff-anonymity treatment, in favor of the alternative hypothesis that the former is larger than the latter, at a 5% significance level (p = .02). Hence, we do not reject our hypothesis 2.

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Hypothesis 3: The share of participants that show unethical behavior that benefits

someone else is larger when the identity of the actor is revealed to the beneficiary, compared to when the actor remains anonymous towards the beneficiary; is tested in the

same way we tested hypothesis 1. We perform a Fisher’s exact test to test the null hypothesis that share of participants that show unethical behavior in the other-payoff-identity treatment is the same as in the other-payoff-anonymity treatment. This null hypothesis cannot be rejected at a 10% significance level (p = .50). Hence, we reject our hypothesis 3.

Hypothesis 4: Participants show more unethical behavior that benefits someone

else when the identity of the actor is revealed to the beneficiary, compared to when the actor remains anonymous towards the beneficiary; is tested in the same way we tested

hypothesis 2. We have assumed that unethical behavior in the other-payoff-anonymity treatment is not normally distributed, and a Shapiro-Wilk test for normality of unethical behavior in the other-payoff-identity treatment leads us to reject the null hypothesis that the latter is normally distributed as well, at a 1% significance level. Hence, in order to test hypothesis 4, we perform a Mann-Whitney U test. We are unable to reject the null hypothesis that unethical behavior in the other-payoff-identity treatment is the same as in the other-payoff-anonymity treatment, at a 10% significance level (p = .69). Hence, we reject our hypothesis 4.

Following our descriptive statistics, these results are expected and indicate that when cheating benefits oneself, people have a strong incentive to do so, as opposed to when cheating benefits someone anonymous to the actor. Moreover, our results also show that the reputation cue associated with identity-revelation was not a strong enough incentive for people to cheat more, when the cheating benefits a third party. We also highlight that the amount of unethical behavior is not statistically significantly larger than zero in both the anonymity treatment (p = .08) and in the other-payoff-identity treatment (p = .16), at 5% and 10% significance levels, respectively. Given that unethical behavior is not normally distributed in any of these treatments, the former results were obtained by performing two separate one sample sign tests on unethical behavior (one for each treatment). Though the p-value is lower for the other-payoff-anonymity treatment, it is worthy to note that the two participants out of twelve that cheated in this treatment did so by only one matrix each, suggesting that they might have done so unintentionally.

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We were unable to obtain any statistically significant linear regressions modelling the impact of the treatment groups on unethical behavior, likely due to the aforementioned results.

4.3. Perceived ethicality of cheating

One of the questions participants had to answer at the end, was to rate on a scale of 1 to 5 how ethical/unethical it would be for a participant to cheat by misreporting their actual score (1 = very unethical, and 5 = very ethical). The variable ‘perceived ethicality of cheating’ corresponds to participants answer to this question. In order to test hypothesis 5: Participants that show unethical behavior perceive it to be more ethical than those

who do not; we test if there is any statistically significant difference between the perceived

ethicality of cheating of all participants that cheated, compared to all participants that did not cheat in the task. In order to do so, we first test for the normality of this variable for these two types of participants. Two separate Shapiro-Wilk tests for normality of the perceived ethicality of cheating lead us to not reject the assumption that this variable is normally distributed, both for participants that showed unethical behavior (p = .43) and for participants that did not show unethical behavior (p = .99). Hence, in order to test hypothesis 5, we use a two sample t-test, according to which we reject the null hypothesis that the perceived ethicality of cheating by participants that showed unethical behavior is the same as the perceived ethicality of cheating by participants that did not show unethical behavior, in favor of the alternative hypothesis that the former is larger than the latter, at a 1% significance level (p = .0075). Hence, we do not reject our hypothesis 5.

Moreover, we are able to estimate the impact of unethical behavior on perceived ethicality of cheating through the use of linear regressions, as depicted below in Table 4.

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Both regression models 1 and 2 pass the F-test of overall significance at 10% (p = .06) and 5% (p = .047) significance levels, respectively. As we can see, both unethical behavior, and unethical behavior dummy are statistically significant at a 1% significance level, in their respective regression models. From our results, we can estimate that for every additional over reported matrix solved (unethical behavior), perceived ethicality of cheating increases, on average, by 0.1428 points. Also, simply displaying unethical behavior increases perceived ethicality of cheating, on average, by 1.2920 points.

We note that it is possible that the effect of unethical behavior on the perceived ethicality of cheating could differ between treatments, and that it would be interesting to explore this using interaction variables. However, given our small sample sizes and insignificant amounts of unethical behavior in the payoff-anonymity and other-payoff-identity treatments, we are forced to do an analysis based on all participants that displayed unethical behavior.

Table 4. Determinants of Perceived ethicality of cheating.

(Model 1) (Model 2)

Unethical behavior 0.1428***

(0.0473)

Unethical behavior dummy 1.2920***

(0.4087) Self-payoff-anonymity dummy - 0.2050 - 0.3507 (0.4024) (0.4132) Other-payoff-identity dummy 0.5244 0.7104* (0.4060) (0.3941) Age - 0.0286 - 0.0348 (0.0634) (0.0625) Gender - 0.0306 0.0323 (0.3315) (0.3221)

Perceived relative performance 0.1401 0.1315

(0.1309) (0.1291)

N 34 34

Adjusted R2 0.1937 0.2129

P-value 0.0616 0.0479

Notes: A linear regression model is used. Both the dependent and independent variables are interval. Dummy variables are unethical behavior dummy (1 if unethical behavior is displayed, 0 otherwise), treatment variables (1 if belonging to the treatment, 0 otherwise), and gender (1 if male). Standard errors are listed in parentheses. Confidence is signified by *, **, and *** at the 90%, 95%, and 99% levels, respectively.

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5. Discussion

In this chapter, we shall first discuss our results and answer our research question. After that, we shall address this research’s limitations and possible venues for future research.

5.1. Discussion of results

This research takes as a starting point the study performed by Gneezy et al. (2013). We address, in particular, their results regarding the self-only-payoff and other-only-payoff treatments in their experiment 3. Moreover, we expand this research to get a deeper insight behind the nature of altruism in the same experimental context. We do so by including the reputation cue of identity-revelation, and test whether it is strong enough to have a significant effect on unethical altruism. In testing our first and second hypotheses, we get very contrasting results to those of Gino et al. (2013). The fact that both the share of participants that show unethical behavior and unethical behavior itself are statistically significantly higher in the self-payoff-anonymity treatment compared to the other-payoff-anonymity treatment suggests that benefiting oneself is a much stronger incentive to behave unethically than benefiting an unknown third party. In fact, when the beneficiary of unethical behavior is someone anonymous, we find that there is virtually no unethical behavior (see the Results chapter for details). The latter result is in line with the social distance theory of altruism discussed before: In the other-payoff-anonymity condition, participants were in complete social isolation from their counterparts, as there was no interaction or identification between them at all (or expectation of such). Hence, the mental saliency of the norm of reciprocity was minimal, and the psychological cost of lying was strong enough to deter participants from engaging in unethical altruism. It seems that Gino et al.’s (2013) experiment’s 3 results were indeed artificially induced by the experimental procedure.

However, when comparing the payoff-anonymity treatment with the other-payoff-identity treatment, our results did not match our predictions (hypothesis 3 and 4). In fact, as with the former treatment, in the latter treatment, unethical behavior was also virtually inexistent, with only one of the twelve participants displaying unethical behavior. This suggests that the reputation cue of identity-revelation was not strong enough to induce participants to lie in order to benefit their counterparts. Following the reviewed literature on reputation and reciprocity, it appears that the reputational incentive

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resultant from the presence of non-anonymity was overwhelmed by the internalized norm of not lying and the psychological cost associated to it. We are, thus, unable to differentiate the motivation behind altruistic behavior in our experiment. Based on our results, we must answer our research question negatively: People do not behave unethically when it benefits someone else, whether it is under anonymity or under identification.

Our results regarding the perceived ethicality of misreporting are in accordance with our hypothesis 5, as participants that cheated in the experiment did, on average, perceive it to be more ethical/less unethical than those that did not cheat. This stands in line with the results of Shu et al. (2011), who found that dishonest behavior induced moral leniency, i.e., people who behave dishonestly are more motivated to report it as not very unethical.

5.2. Limitations

This research was performed, unfortunately, with several resource limitations which probably affected its results. The most obvious limitation concerns our sample size. Twelve participants per treatment is far too small to achieve significantly valid results. There were also some limitations regarding the nature of our sample of participants. Besides the obvious Hawthorne effect that affects most experiments, i.e., participants’ behavior is modified by the simple fact that they know they are in an experiment; the fact that the great majority of the participants were friends with the experimenter, or knew him personally, probably also shaped their behavior in the experiment. This effect, either on the direction of behaving more unethically or less unethically, is probably dependent on the nature of the relationship between the experimenter and the participant. Thus, ideally, participants should not know who the experimenter is. Finally, due to financial limitations, only one participant per experimental session was awarded to have his/her payoff converted into money, whereas, ideally, every participant would be awarded.

5.3. Future research

This research’s results are a good starting point for future research. What is particularly noteworthy in our results is that a very insignificant portion of participants cheated in the treatments where someone else benefited from doing so. The fact that this happened in the absence of negative consequences of cheating suggests that participants behaved in way such that the ends did not justify the means. It would be interesting to see

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if there would be any significant change in unethical behavior if participants were, before the task, primed in one of two ways: Either in a way that makes it mentally salient in them that “the ends do not justify the means” or that “the ends justify the means”. This could be done with one control group (without priming) and two treatment groups (one for each of the priming effects), all under the same conditions of the other-payoff-anonymity treatment used in our research. Another interesting venue for research would be to explore unethical altruism under conditions where reciprocity is actually possible. Such study would show us if people will incur in unethical altruism due to an actual expectation of reciprocity, and whether such behavior is reciprocated.

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An analysis of altruism through deceptive behavior under conditions of anonymity and identification

Faculty of Business and Economics