EXAMINING ASSOCIATIONS BETWEEN MALADAPTIVE PERSONALITY TRAITS,
COMPETITION, AND FAIRNESS IN ECONOMIC DECISION-MAKING GAMES
By
Edward A. Witt

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
DOCTOR OF PHILOSOPHY
Psychology
2011

ABSTRACT
EXAMINING ASSOCIATIONS BETWEEN MALADAPTIVE PERSONALITY TRAITS,
COMPETITION, AND FAIRNESS IN ECONOMIC DECISION-MAKING GAMES
By
Edward A. Witt
Context: What do people do when they find themselves the victim or benefactor of an
unfair competition? Furthermore, do individual differences in personality, specifically those that
have been discussed in the context of greedy and manipulative behavior (i.e., maladaptive
personality traits) moderate these associations? To this point, few studies can answer these
questions. Objective: The goal of this dissertation was to better understand how competition and
fairness affect people’s behavior in situations in which resource allocation is the primary concern
and to also understand whether individual differences in maladaptive personality traits account
for variation in responses to these situations. Design, Setting, and Participants: 893 college
undergraduates completed these studies for course credit or extra credit. Participants first
completed a series of demographic and personality questionnaires then engaged in a
computerized version of an economic decision-making game where they bargained over points
(prize entries) with a group of ostensible opponents. The games were either competitive
(participants answered math questions quickly for a chance to make a proposal of points) or noncompetitive (the computer decided the proposer randomly) and either allowed participants the
choice of accepting/rejecting proposals (i.e., “the Ultimatum game”) or to forced them to accept
proposals (i.e., “the Dictator game”). Furthermore, within the competitive games, competition
was manipulated to be either fair (opponents had questions of equal difficulty) or unfair (one
opponent had an advantage). Main Outcome Measures: The outcomes of interest were
participants’ proposals of points made to their ostensible opponents (in both Ultimatum and

Dictator variants of the game) and their acceptance rates of offers made to them by their
ostensible opponent (in Ultimatum variants only). Results: Competition increased participants’
acceptance of unfair (1 or 2 point) offers (MNon = .27, MComp.= .35; d = .24) and decreased
proposals of points (MComp = 2.89, MNon = 3.45; d = .47). Manipulating the fairness of the
competition resulted in increased acceptance rates of unfair offers such that they were
significantly higher when participants lost at an advantage (M =.38) than when the competition
was fair (M = .35; d = .07) or they lost at a disadvantage (M = .33; d = .13). Manipulating
fairness also had an effect on participants’ proposals such that they offered more points to their
opponents when they won at an advantage (M = 3.05) and less when they won at a disadvantage
(M = 2.72). Finally, there was little evidence of associations between individual differences in
maladaptive personality traits and acceptance rates or proposals. Likewise, there was little
evidence to suggest that these associations were moderated by game type (i.e., Ultimatum vs.
Dictator). Conclusions: The presence of competition appears to change the norm of what
constitutes a fair distribution of resources from one of equality (everyone gets an equal share) to
one of equity (some parties deserve more) as demonstrated by higher acceptance rates of unfair
proposals and lower proposals made in competitive versus non-competitive games. Furthermore,
people are somewhat sensitive to the procedural injustice (i.e., fairness) of competition and
behave in a manner that suggests they are attempting to redress an unfair advantage by offering
more of the resource when it was won unfairly and rejecting small proposals of the resource from
individuals who may be exploiting the unfairness of the situation. Last, there was little evidence
to suggest that individual differences in personality are predictive of behavior in these games or
that the presence/absence of rejection moderates associations between personality attributes and
game behavior.

TABLE OF CONTENTS

LIST OF TABLES

v

LIST OF FIGURES

vi

CHAPTER 1: INTRODUCTION

1

CHAPTER 2: METHODS

17

CHAPTER 3: RESULTS

23

CHAPTER 4: DISCUSSION

35

APPENDICIES

59

REFERENCES

73

iv

LIST OF TABLES

TABLE 1: Frequencies and Percentages for Demographic Variables by Game

49

TABLE 2: Inter-correlations Between Individual Difference Measures

50

TABLE 3: Means, Standard Deviations, and Internal Consistency Estimates
for Psychological Measures by Study

51

TABLE 4: Individual Differences and Acceptance Rates

52

TABLE 5: Individual Differences and Proposals

53

v

LIST OF FIGURES

FIGURE 1: The Effect of Game Type and Competition on Proposals

54

FIGURE 2: The Effect of Manipulating Fairness of Competition on Ultimatum
Acceptance Rates

55

FIGURE 3: Gender Difference in Acceptance Rates by Fairness of Competition

56

FIGURE 4: Proposals by Difficulty

57

FIGURE 5: Game Enjoyment as a Function of Competition and Game Type

58

vi

CHAPTER 1: INTRODUCTION
Individuals sometimes hold advantages over others in competitive contexts. However, not
all advantages are earned or received fairly. For instance, a worker might be promoted to
manager, not because of merit, but because a family member is on the board of directors. This
individual is then in a position to make decisions that affect others in the organization. What do
people do when they are given a competitive advantage that they don’t deserve? Some people
would choose to use any advantage they could get, fair or unfair, whereas others may try to
compensate for the unfairness of such a situation. Empirically, economic decision-making games
such as the Ultimatum game (Guth, Schmittberger, & Schwarze, 1982) and the Dictator game
(e.g., Forsythe, Horowitz, Savin, & Martin, 1994) are often used to study perceptions of fairness
and competitive behavior. These games mimic situations where people can either act in a selfinterested or an egalitarian manner while also manipulating the presence or absence of
retribution for self-interested behavior. Moreover, these games provide researchers with a tool
for understanding the individual differences that predict observed exploitative and punitive
behavior in a controlled setting. Accordingly, the goal of this dissertation is to use modified
versions of these economic decision-making games to better understand how people react in
situations of unfair competition and to evaluate whether individual differences in personality
predict differential reactions to these situations.
Economic decision-making games are well-suited for examining how people respond to
fair and unfair competition because they are tightly controlled and their conditions are easily
manipulated. Furthermore, a wealth of research has been conducted on these games and
cumulative results provide an important context for personality-related predictions. In this
dissertation I begin by reviewing theory on perceptions of fairness. I then introduce the

1

Ultimatum and Dictator games by outlining their procedures, reviewing relevant research, and
describing the modifications to these games carried out in the current research. Next, I introduce
a maladaptive set of personality traits often referred to as the “Dark Triad.” These traits are often
discussed in the context of exploitative and manipulative behavior, and therefore should be
particularly relevant in situations of unfair competition. Finally, I provide a set of hypotheses that
guide this dissertation.
Perceptions of Fairness: Distributive and Procedural Justice
Fairness is thought to be so integral to human existence that evolutionary theorists have
proposed humans have an evolved cognitive mechanism for “cheater detection” (e.g., Cosmides
& Tooby, 1992). This system is thought to alert people to unfair or selfish behavior that could be
detrimental to personal survival. The explanation is that humans are a social species who often
live in communal groups with a division of labor. Humans must therefore rely on others to
survive. Unfortunately, this reliance allows for exploitation and exploitation could have
detrimental effects on human reproductive fitness. Indeed, fairness concerns are not limited to
humans as the food sharing behavior of chimpanzees also reflects these concerns (de Waal,
1989). In situations in which primates compete for limited and finite resources, it appears that
fairness concerns are extremely important. The combination of a system for detecting fairness
and the fact that perceptions of fairness are seemingly integral for harmonious social interactions
underscores the importance of fairness as a topic of psychological inquiry. Nonetheless, there are
a number of concerns surrounding the definition of fairness.
There are several ways that fairness concerns can play into situations involving
competition over resources. Two such ways involve the fairness of the division of resources and
the fairness of the competition for resources. Psychologists refer to these as concerns over

2

distributive and procedural justice, respectively (Deutsch, 2006). According to Deutsch (2006),
distributive justice refers to whether the allocation of a resource is seen as fair or just. For
example, a tribe of hunters may be faced with the task of dividing the day’s kill among their
members. There are at least three methods of distribution that can be considered “fair”: equity,
equality, and need. Keeping with the previous example, the tribe could choose to divide the food
proportionally to those who invested the most time or effort into procuring it (equity), providing
even portions to all members (equality), or giving more food to the larger members and less food
to the smaller members regardless of the effort invested in hunt (need). The kind of division and
the degree to which it is considered fair by the individuals involved depends, in part, on
contextual features. In instances of competition, equity is likely to be the normative means of
division. That is, the competitor who performs the best should receive the most benefits – to
quote an old cliché “To the victor go the spoils.” In other instances, especially those in which no
party has a clear right or need for more of the resource, the fairest distribution is likely to be
equality. Although distributive justice is clearly an important aspect of daily life it is only one
consideration when evaluating the fairness of a particular situation. Fairness concerns also arise
when considering the features of the competition itself as the fairness of the procedures likely
affects how much of the resource should be given to the deserving party.
Procedural justice concerns the degree to which the processes that lead to the division of
resources are seen as fair. For example, companies evaluating job candidates usually have many
criteria on which to judge the applicants but often only use a handful of these criteria when
making the decision to hire a particular individual. If the candidates are aware of the criteria
being used for selection and believe them to be reasonable then the process is considered fair.
Deutsch (2006) suggests that “one wants procedures that generate relevant, unbiased, accurate,

3

consistent, reliable, competent, and valid information and decisions” (p. 45) and that in situations
“where it is not clear what ‘fair outcomes’ should be, fair procedures are the best guarantee that
the decision about outcomes is made fairly” (p. 44). In short, people like fair procedures because
they believe that such procedures precede fair outcomes.
What happens when people’s notions of distributive and procedural justice are violated?
Obviously, what is considered fair varies from context to context and can also vary depending on
whether one is the benefactor or victim of an injustice. For example, an individual who gets a job
because the hiring process is based on a subset of all potential criteria may be more likely to
believe the use of those specific criteria was fair than the individual who did not receive the job.
Self-serving biases may of course shape perceptions of fairness. Nonetheless, despite any
potential for an imbalance in perceptions of fairness, research suggests that when a perceived
injustice has occurred people feel compelled to restore justice or seek retribution, regardless of
whether they were the benefactor or the victim of the injustice (Deutsch, 1985).
Although both victims and benefactors seek to redress unfairness, the motivations for
these behaviors may differ. Victims of injustice may seek retribution for personal or social
reasons. For example, a person who was passed over for a promotion may attempt to sabotage
company morale for self-serving reasons (i.e., an attempt to make themselves feel better by
hurting others), accuse their boss of bias (i.e., an attempt to reform the perpetrator of injustice),
or write a letter to corporate leaders about promotion practices (i.e., an attempt to reform the
unjust system). By contrast, the benefactor of the injustice may seek to alleviate guilt or anxiety
over having benefited for no good reason due to forces outside their control. Keeping with the
previous example, the individual who gets a promotion via unfair procedures may choose to turn
it down or to work exceptionally hard in an attempt to justify their being selected for the

4

position.
Economic Decision-Making Games and Distributive Justice
Although psychological researchers have many experimental paradigms for
understanding retaliation in response to provocation (e.g., aggression studies like the “Hot
Sauce” paradigm; Lieberman, Solomon, Greenberg, & McGregor, 1999), paradigms in which
individuals benefit from an injustice and have the opportunity to engage in some sort of either
conciliatory/compensatory or exploitative behavior are far less common. How then are
psychological researchers to study individuals’ reactions to this interesting situation? One
possibility is to co-opt paradigms used in the economics literature – in which individuals are
required to divide a shared resource – to create such a situation.
Economic decision-making games are simple paradigms that can be useful for
understanding human fairness concerns in the context of resource division. One such game,
commonly referred to as “the Ultimatum game” (Guth et al., 1982) involves two individuals
engaging in a bargaining interaction. In a standard game, pairs of individuals are given the task
of dividing a sum of money (usually $10) between themselves. One individual in the pair is
randomly assigned to the role of the “Proposer” and the other is then designated as the
“Responder.” The proposer chooses a division of money or points (e.g., $3 to the responder and
$7 to the proposer) to present to the responder and the responder chooses to accept or reject the
proposer’s offer. If the responder accepts the offer, both players get the proposed amounts.
However, if the responder rejects the offer, then both individuals receive nothing.
Although the Ultimatum game may appear to be of limited ecological validity, this game
has real world analogs. For example, the proposals of settlements in legal trials have a similar
structure to this experimental game. Before a case goes to trial the defense will often make a

5

(usually monetary) proposal to the prosecution in order to avoid prolonging the legal process.
The prosecution must then evaluate the terms of the proposal and decide whether or not to accept
it. If the proposal is accepted each side gets whatever is agreed upon in the proposal. If the offer
is rejected the case goes to trial, often resulting in a time and cost for both sides. In these
situations, the prosecution’s decision over whether to accept the offer of settlement depends on
whether or not they believe the settlement is reasonably fair given that particular case, much in
the same way that individuals in the Ultimatum game must decide on the fairness of the division,
given the circumstances of the experiment. It is for this reason that both the defense and the
participants in the Ultimatum game must be aware of the features of the particular situation if
their proposals are to be accepted.
In its most basic form, research with the Ultimatum game suggests that the default mode
of distributive justice is equality when there is little reason to favor any of the parties involved in
the bargain. As mentioned previously, the proposers in these games are randomly assigned the
task of splitting the money. Nothing about the situation favors the proposer aside from luck. The
proposer did nothing special to earn the role and presumably does not have any particular reason
to expect that he or she would be assigned to it. Because of this, the implicit “fair” split of money
in this situation seems to be an equal division (i.e., a modal offer in these games tends to be 50%
of the total amount, Thaler, 1988; Camerer, 2003). Further evidence supporting this notion
comes from the fact that the more the proposal favors the proposer the more likely it is to be
rejected (Camerer, 2003), implying that responders generally anticipate a fair allocation and will
tend to punish deviations from equality even at a cost to themselves.
These findings regarding actual behavior in the Ultimatum game clash with classical
economic theory which suggests a rational agent would accept any proposal provided it results in

6

a monetary gain (e.g., Camerer, 2003). However, evidence suggests that responders find unequal
proposals insulting (i.e., their notion of distributive justice has been violated) and research
suggests that the rejection of small offers is driven, in part, by the desire of responders to punish
proposers who have treated them unfairly (e.g., Bolton & Rami, 1995). If people were only
concerned with their own monetary gain it stands to reason that they would make and accept low
offers. However, in this situation an acceptance of a small sum carries with it the knowledge that
the other party is going to receive disproportionately more of the resource despite the fact that
neither party has any reason to feel entitled to more than half of the pie. Thus, the responder is
often willing to punish their partner, at some personal cost, provided that the results are costlier
for the individual who has violated the distributive justice norm of equality. Again, as with the
basic structure of the Ultimatum game, there are real world analogs of this self-injurious
behavior. For example, people going through divorce disputes sometimes make decisions that are
costly to themselves provided they are costlier to their former spouses, though in these instances
it is not always the case that the decisions are the direct result of a violation of distributive
justice.
The norm of equality for resource distribution in a typical Ultimatum game is strong,
especially given that unequal proposals can be rejected. Accordingly, this game represents a
situation that heavily constrains individuals’ behavior. Absent the constraints of the game,
individuals vary in their desires or preferences for different resource allocation from pure selfinterest to egalitarianism to perhaps even self-sacrifice. That is to say, the modal response of
equality in Ultimatum game proposals is likely due to the possibility that responders could reject
self-interested proposals. Accordingly, the high rate of compliance to this norm suggests that
some proposers might be only be “playing the part” of the fair partner because making the

7

proposal they actually desire could result in a zero gain. An experimental variant of the
Ultimatum game called the “Dictator game” (e.g., Forsythe et al., 1994) addresses this possibility
by removing the responder’s power to accept or reject the proposer’s offer. As Roth (1995) notes
“in the Dictator game player 1’s proposal can be interpreted as a pure expression of his [sic]
preferences” (p. 270). In other words, with the threat of rejection removed people should be more
likely to propose a split that is aligned with their ideal distribution and this should shift the
average distribution of game outcomes in the favor of pure self-interest.
As it stands, there is evidence to suggest that people, on average, behave more selfishly in
the Dictator game than the Ultimatum game. For example, in one comparison study 36% of
Dictator proposers offered 0 to their opponents while not a single Ultimatum proposer made an
offer of 0 (Forsythe et al., 1994). Thus the distributions of proposals appear to differ significantly
between games. Therefore, these games represent psychologically different situations and it is
important to examine both within the same experimental context in order to gain a fuller
understanding of the processes at in resource distribution and perceptions of procedural justice.
Introducing Competition and Manipulating Procedural Justice
Most previous research using these economic decision-making games has used a random
process to assign players to the two roles. As of yet, no study has systematically manipulated the
method through which individuals gain the role of proposer. This dissertation is concerned with
behavior in competitive situations, so in the current work I introduce a competition between
individuals as a way to determine who is given the role of proposer. By doing so, the implicit
norm of what constitutes a fair distribution should shift from equality (i.e., an equal or close to
equal division of points) to equity (i.e., the winner gets to take more of the pie).
One previous study has examined competition in the context of the Ultimatum game.

8

Hoffman, McCabe, and Smith (1996) had individuals compete in a trivia challenge with the
better performing players earning the role of proposer. The addition of competition shifted the
distribution of proposals from near equality toward the self-interest of the proposer. The authors’
interpretation of this result was that the winning individuals felt justified in taking more of the
pot, given that they earned the right to divide it through the process of a presumably fair
competition. In other words – the addition of competition changed the expected distribution
method from pure equality (i.e., neither player “deserves” more so they should split it evenly) to
equity (i.e., one player has earned the right to divide the money and should therefore take more
for themselves). The current work replicates and extends Hoffman et al. (1996) by including
competition for the role of proposer while also controlling participants' wins and losses. By
controlling wins and losses, the current work ensures that all individuals have an equal number
of wins and losses for comparison.
Importantly, the present study also manipulates the perceived fairness (i.e., the procedural
justice) of the competition by creating situations where individuals win or lose unfairly.
Specifically, the study will create situations of matched or unmatched (advantaged or
disadvantaged) competition between partners. For example, on some rounds participants will be
answering questions of equal difficulty, while on other rounds the level of difficulty will vary
between players. Manipulating the playing field in this way should activate concerns about
procedural justice as individuals will be made aware that they are competing at an unfair
advantage (or disadvantage) and it should also affect individuals’ perception of what constitutes
an equitable outcome. For example, the normative split of the pot when competition is fair (i.e.,
the level of difficulty is the same for both players) should differ markedly from conditions of
unfair competition. In general, individuals should recognize the unfairness of the situation

9

(regardless of whether they are the beneficiaries) and take steps to redress the procedural
unfairness, which should be reflected in their behavior (i.e., distributions offers and acceptance
rates). For example, when a participant wins a round with an advantage that he or she did not
deserve his or her proposal should be larger, on average, than in situations where neither player
had a competitive edge. Similarly, when a participant loses a round at a disadvantage that he or
she did not deserve his or her acceptance rate for low offers (i.e., < 20%) should be lower, on
average, than when he or she lost in an equal competition.
Personality and Behavior in Fair and Unfair Competition
The work summarized above describes the expected average behavior of people in the
original and modified economic games. Despite the fact that Ultimatum and Dictator studies
often focus only on average behavior they also demonstrate a fair degree of variability in
behavior both between and within studies. As previous psychological research demonstrates,
people do not always behave similarly, given the same psychological situation, even in very
extreme circumstances (see Milgram, 1963). This variation in behavior given the same
circumstances could partially be accounted for by individual differences in thoughts, feelings, or
actions (i.e., personality attributes; Allport, 1931). Recent research has provided some evidence
that responder behavior in the Ultimatum game is at least partially heritable (Wallace, Cesarini,
Lichtenstein, & Johannesson, 2007). Such a result suggests that individual differences might play
an important role in understanding differential behavior in situations of unfair competition within
these economic decision-making games.
One set of individual difference constructs that seems particularly likely to be influential
in these situations is drawn from the so-called “Dark Triad” of personality traits outlined by
Paulhus and Williams (2002): Machiavellianism (manipulative personality), psychopathy (high

10

impulsivity and thrill seeking coupled with low empathy and anxiety), and Narcissism
(grandiosity, entitlement, dominance, and superiority). These traits should be particularly
relevant here because the games involve a blend of elements – competition, reward, retribution –
that are associated with these constructs. What follows is a brief overview of research and theory
on each of these constructs. Wherever possible, findings of research from the psychological and
economic literature are drawn upon to make predictions about the behavior of individuals with
high levels of these traits in situations of unfair competition.
Machiavellianism .Christie and Geis (1970) wanted to better understand the willingness
of cult leaders and other influential individuals to manipulate others for personal gain. In order to
accomplish this, they looked to the writings of Niccolo Machiavelli and drew inspiration for their
eventual measure of manipulativeness from Machiavelli’s work The Prince (1513/1966). Thus,
Machiavellianism has become the choice term to describe this kind of strategic manipulation of
others for personal gain and power. Correlational work has demonstrated that people who score
higher on a measure of Machiavellianism (often referred to as high Machs) are income
maximizers (i.e., are likely to make the choice that results in the most monetary gain for
themselves) and are untrusting of potential economic partners who they also believe to be
income maximizers (Sakalaki, Richardson, & Thepaut, 2007). Thus, high Machs should be likely
to capitalize on opportunities for personal gain and believe that others will do the same.
Moreover, research suggests that high Machs have higher external economic loci of control than
low Machs (Sakalaki, Kanellaki, & Richardson, 2009). In other words, Machiavellians believe
economic success is more strongly influenced by chance than by factors such as effort or
perseverance.
Only one study has examined the behavior of high Machs in the Ultimatum game. Meyer

11

(1992) found that high Machs accepted low offers in single shot games but refused them in
repeated interaction games. Thus high Machs behave as income maximizers in single-shot
interactions, but punish perceived unfairness in repeated interactions more so than low Machs.
Because Meyer (1992) did not allow individuals to also play the role of proposer, there is no
empirical evidence on which to make a prediction for the present studies. The behavior of high
Machs in Ultimatum games (as a responder) suggests that they are opportunists. Because of this,
high Machs should make the income-maximizing choice in every situation. When playing the
proposer in the Ultimatum game, the income-maximizing choice may be a relatively fair offer
(because low offers can be rejected) whereas in the Dictator game, the income-maximizing
choice is to take as much money as possible. Therefore, with regard to proposals,
Machiavellianism should be a negative predictor of proposals in the Dictator game but unrelated
to proposals in the Ultimatum game. The income-maximizing choice when playing the role of
responder in the Ultimatum game is to accept any positive offer regardless of the size. However,
Meyer’s (1992) work suggests that Machs only behave in this manner in single-shot interactions.
Given that the current study is a multi-round game Machiavellianism should be negatively
correlated with acceptance of low proposals.
Psychopathy. People often consider antisocial behavior and manipulativeness to be two
of the cardinal features of psychopathy. However, impulsivity, stress immunity, and social
dominance have also been discussed as behaviors relevant to the construct. Recently, Patrick and
Bernat (2009) have proposed a two factor model of psychopathy that accounts for this dual
nature. According to the theory, psychopathy is the result of deficits in two underlying
neurobiological systems: one that governs fear (Fearless Dominance) and another related to
executive functioning (Impulsive Antisociality). Research using measures of Fearless

12

Dominance and Impulsive Antisociality often finds opposite associations between these traits
and outcomes of interest. Specifically, Fearless Dominance is associated with positive outcomes
like adjustment and social zest, whereas Impulsive Antisociality is most often associated with
negative outcomes such as antisocial behavior and substance use (Witt, Donnellan, Blonigen,
Krueger, & Conger, 2009). Work with measures of these traits suggests that Machiavellianism
correlates strongly with Impulsive Antisociality and weakly or not at all with measures of
Fearless Dominance (Witt et al., 2009).Thus, it appears that Machiavellianism and aspects of
psychopathy overlap to some degree (with regard to Impulsive Antisociality). However, Fearless
Dominance represents aspects of psychopathy not tapped by Machiavellianism.
The empirical basis for making predictions about these psychopathic traits with regard to
economic decision-making outcomes is mixed to non-existent. For example, Osumi and Ohira
(in press) found that people pre-selected for “high” scores on a self-report measure of
psychopathy were more likely to accept low offers in the Ultimatum game than people who
scored “low” on this measure whereas Koenigs, Kruepke, and Newman (2010) found that people
categorized as primary psychopaths (who demonstrated extremely low levels of anxiety) had
lower acceptance rates of low offers in group of inmates than those classified as secondary
psychopaths (who demonstrated high levels of impulsivity), and non-psychopaths. With regard
to proposals, Koenigs et al. (2010) found no differences between primary, secondary, and control
participants on Ultimatum proposals, but found that primary psychopaths made significantly
lower Dictator proposals than secondary psychopaths or non-psychopaths whereas Osumi and
Ohira (in press) did not collect data on Ultimatum proposals. Furthermore, the small sample sizes
and questionable analytic techniques (e.g., the use of median splits to categorize participants into
high and low groups) used in these studies calls the validity of these findings into question.

13

On the other hand, there is a body of related evidence in the literature upon which to
make predictions for Impulsive Antisociality and to a lesser extent, Fearless Dominance with
regard to economic decision-making behavior. Impulsive Antisociality has been found to be
associated with externalizing problems (Witt et al., 2009) as well as being associated with
displaced aggression (Witt & Donnellan, 2008). Furthermore, with regard to the five factor
model of personality, Impulsive Antisociality is equally strongly negatively associated with
Agreeableness and Conscientiousness (Witt et al., 2009). This pattern of correlates suggests an
individual who is emotionally reactive, lacks self-control, and lacks affiliative tendencies.
Curiously, Impulsive Antisociality is positively associated with Machiavellianism but negatively
related to reward responsiveness (Witt et al., 2009). Thus high scorers on Impulsive Antisociality
express a willingness to manipulate others but might not be particularly susceptible to the
rewards within the Ultimatum game.
This line of reasoning also suggests that Impulsive Antisociality should not predict
proposals in the Ultimatum game and may be a slight negative predictor of them in the Dictator
game. The rejection of low offers is often thought to be motivated by an emotional reaction to a
perceived slight. This suggests that people higher on Impulsive Antisociality should be
particularly sensitive to the insult of a low offer and thus more likely to reject (i.e., have lower
acceptance rates) than people lower on this dimension of personality. The predictions for
Fearless Dominance are less clear. Fearless Dominance is negatively associated with
Internalizing problems but is positively associated with a BAS (i.e., reward sensitive) orientation
– including reward responsiveness (Witt et al., 2009). Thus people who score higher on Fearless
Dominance should be less emotionally affected by low offers, but should be just as likely (if not
more likely), to reject low offers as low scorers because they desire the prizes associated with the

14

game. This also suggests Fearless Dominance should be a negative predictor of proposals in the
Dictator game but not in the Ultimatum game because people higher on this trait want to
maximize their chances to win a prize.
Narcissism. Narcissism is often characterized as an exaggerated sense of self-importance
and entitlement coupled with the need for admiration from others. Over the past twenty years the
construct of Narcissism has received considerable attention in the social, personality, and clinical
psychology literature (Cain, Pincus, & Ansell, 2008). In contrast, it does not appear to have
garnered as much interest in the economic games literature as to date there are no published
studies examining the impact of Narcissism in these games. Further complicating the picture is
the fact that the most commonly used measure of Narcissism in social/personality psychology–
the Narcissistic Personality Inventory (NPI; Raskin & Hall, 1979) – is not unidimensional. In
fact, there is reason to believe that it conflates an array of adaptive and maladaptive content
(Cain et al., 2008). Among the traits suggested to be captured by the NPI are Entitlement,
Exploitativeness, Authority, Self-Sufficiency, Superiority, Vanity, and Exhibitionism (Raskin &
Terry, 1988). Of these traits, the two that should be most relevant to competitive situations are
Entitlement and Exploitativeness. Entitlement has been found to be associated with reactivity to
ego threat (e.g., Witt et al., 2009) and more entitled individuals tend to believe they are more
deserving than others. Therefore, entitled individuals should be more likely to reject low offers
while also being more likely to make low offers (regardless of the type of game) because it fits
with their exaggerated sense of what constitutes a fair division. Exploitative individuals should
behave in much the same way as Machiavellian individuals. Specifically, Exploitativeness
should be unrelated to Ultimatum offers, slightly positively or unrelated to Ultimatum
acceptance rates, and should be negatively associated with Dictator proposals.

15

Predictions
H1: Consistent with the results of Hoffman et al. (1996) the addition of competition
should shift the distribution of proposals to be more in favor of the proposer (relative to
well-established results from non-competitive games) and it should increase overall
acceptance rates such that responders are more willing to accept smaller offers than in
non-competitive games.
H2: The addition of unfair competition should activate perceptions of procedural justice
such that individuals will be more generous in their offers when they are the beneficiary
of the unfair procedure and more punitive (with regard to the rejection of low offers)
when they are the victim of such procedures.
H3: Game behavior (i.e., offers made and rejection behavior) should be predicted by
individual differences in maladaptive personality traits (i.e., Aspects of the Dark Triad).
Machiavellianism and Exploitativeness should be unrelated to Ultimatum proposals,
positively or unrelated with acceptance rates, and negatively related to Dictator
proposals. Impulsive Antisociality should be unrelated to Ultimatum proposals,
negatively related to acceptance rates, and negatively or unrelated to Dictator proposals.
Fearless Dominance should be unrelated to Ultimatum proposals, negatively or unrelated
to acceptance rates, and negatively related to Dictator proposals. Finally, Entitlement
should be negatively related to Ultimatum proposals, acceptance rates, and Dictator
proposals. A secondary hypothesis, suggested by Hilbig and Zettler (2009) is that
personality coefficients should be larger in the Dictator game than in the Ultimatum game
because the threat of rejection has been removed. Accordingly, game type will be

16

examined as a moderator of the association between personality traits and game
outcomes.
CHAPTER 2: METHODS
Participant Sign-Up and Study Description - All Games
For all games collected in the present work participants logged onto the Human
Participation in Research System (HPR) and signed up for a study called “Multi-Site Economic
1

Game Study.” The study description suggested that they would come into the lab to play an
online game against a random selection of participants from other universities (in reality they
played against a computer that controlled wins and losses) for a chance to win prizes. The
description of the study did not vary across game type or level of competition.
Participants
The total sample for this study consisted of 893 college undergraduates (NonCompetitive Ultimatum Game: n = 162, Non-Competitive Dictator Game: n = 101; Competitive
Ultimatum Game: n = 311, Competitive Dictator Game: n = 319). Participants were primarily
Caucasian (81.5%) women (62.8%) who were between the ages of 18-20 (75.2%) and in their
first or second year of college (60.7%). A breakdown of demographics by game type is provided
in Table 1.
Game Procedures
When participants were brought to the laboratory they were asked to read and sign a
consent form and then were given instructions on how the game would be played (See Appendix
B for specific instructions). Experimenters were instructed to log each participant into the game
program and to ask them to create a unique username for the task (this name would be displayed

1

The exact wording from the HPR web site is provided in Appendix A
17

on the screen during the game as a means for the participant to know whether or not they won
the round). Each game involved a series of rounds (24 in non-competitive games, 36 in
competitive games) the rounds differed from competitive to non-competitive games to keep the
numbers of rounds similar for comparison while also preventing fatigue in participants who were
completing the non-competitive games. In each round participants were assigned a different
“partner” from another university, however this partner was non-existent and they were playing
the computer on all rounds.
Role Assignment. In the non-competitive games participants were told that each round the
role of proposer would be randomly assigned by the computer. Each round they would see a
screen with a button labeled “decide winner” that they clicked for the assignment. After clicking
the button they would see a screen that said “deciding winner” with a loading-type bar at the
bottom of the screen (the length of time this screen was displayed varied randomly from trial to
trial from 1 to 3 seconds). After this screen, participants would either see a screen saying “you
lost the round” or “you won the round.”
In the competitive games participants were told that each round the role of proposer
would be determined by the outcome of a competition between the participant and his or her
partner. Specifically, participants were instructed to answer a series of multiple-choice math
problems as quickly and accurately as possible with the promise that the player with the higher
score would earn the role of proposer. If participants tied, the winner would be the participant
with the faster reaction time. In reality wins and losses were controlled by the computer. To
create the perception of unfairness in competition, participants (and their virtual “partner”) were

18

2

randomly given a set of pre-determined “easy” or “hard” questions on each trial and at the end
of the trial they were presented with a results screen indicating the difficulty of the questions
they just answered, the difficulty of the questions their partner ostensibly answered, each
player’s scores and reaction time, and the outcome of the trial (win or loss). This manipulation
allowed for situations in which the participant won/lost when the competition was fair (matched
difficulty) or unfair (they were at an advantage or at a disadvantage). The order of these trials
was randomized and all participants received an equal number of trails for each level of fairness
(12 advantaged, 12 matched, 12 disadvantaged, 50% wins).
For all games the order of wins and losses was randomized but the win/loss ratio was
held constant at 1:1. The specifics of winning and losing trials are outlined below:
Losing Rounds. If participants lost the round they saw a screen that said “you lost the
round” (in competitive games, this screen also contained all relevant information related to the
competition) and had to click “continue” to proceed. They then saw a screen that said “waiting
for offer” (the length of which varied randomly round to round from 1 to 3 seconds) after which
they would see a screen that said “username offers you: X pts” (where username was the
randomly determined username of the “partner” for that round, and X was a value from 1-5). In
the Ultimatum version of the game participants were given the opportunity to accept or reject the
offer whereas in the Dictator game they were given no such option. An acceptance of the offer in
the Ultimatum game meant that the participant was agreeing to that division of points and that
2

A paired samples t-test revealed that participants found the “hard” questions (M = 3.49, SD =
.83) to be significantly more difficult than the “easy” questions (M = 1.45, SD = .65) t(630) = 53.03, p < 001, d = 2.11. There was no evidence to suggest that game type (Ultimatum vs.
Dictator) moderated this association. There was also no suggestion of gender differences in
perceptions of the difficulty of the “hard” questions. However, there was a gender difference
such that women rated the “easy” questions as harder (M = 1.49, SD = .66) than men (M = 1.36,
SD = .56) t(514.293) = -2.697, p = .007, d = .20.
19

each person in the pair would get the points stated in the offer (e.g., 6 pts partner, 4 pts
participant) whereas a rejection meant that both partners received zero points for that round.
Computer generated offers were either “fair” (i.e., 4 or 5 pts) or “unfair” (i.e., 1 or 2 pts). The
order of offers was randomized and participants received equal numbers of fair and unfair offers.
Moreover, the chances of receiving one “fair” offer versus the other (i.e., 4 or 5 pts) was 50%, as
were the chances of receiving one “unfair” offer versus the other (i.e., 1 or 2 pts).
Winning Rounds. If participants won the round they saw a screen that said “you won the
round, how much would you like to offer?” (in competitive games, this screen also contained all
relevant information related to the competition). To make an offer, participants slid a slider bar
either toward their username or toward their partners. The closer the bar was to the participant’s
username the more points they offered themselves and the fewer they offered their partner (by
default the bar was set at the center with each partner getting 5 pts). Participants then clicked
“submit” and saw a screen that said “waiting for partner” (the length of which varied randomly
trial to trial). The proposal procedure was identical for both the Ultimatum and the Dictator
game. However, the response procedure differed between games (i.e., reject vs. no reject) as
detailed in the previous section.
Participant Incentive. To motivate participants to take all trials seriously, they were told
that the point division from one randomly selected round would determine the number of raffle
tickets they would receive to win one of five iPod nanos (in reality all participants were given
equal consideration for the prizes). Points, as opposed to money, were chosen to allow for larger
samples as using money would have made larger sample sizes prohibitively expensive. However,
using points rather than money should not affect the results of the game, as previous research has
found that proposal and rejection rates are not affected by changes in stakes (List & Cherry,

20

2000; Hoffman et al., 1996) even when no money is used (Forsythe et al., 1994).
Measures
All participants in this study completed the same set of individual difference measures.
For a full list of measures, including items, please see Appendix C. Table 2 reports intercorrelations between these measures across all games whereas Table 3 reports means, standard
deviations, and alphas for these measures separated by game. To ensure adequate content
coverage, multiple measures of each maladaptive trait, with the exceptions of Fearless
Dominance and Exploitativeness, were used. What follows is a series of brief descriptions of
these measures.
Machiavellianism
Mach-IV (Christie & Geis, 1970). The Mach-IV is a 26 item measure designed to capture
the interpersonal manipulativeness of the construct of Machiavellianism. Though other measures
exist, the Mach-IV by far the most popular, as it has been used in over 2,000 published studies
(Jones & Paulhus, 2009).
Machiavellian Personality Scale (MPS; Dahling, Whitaker, & Levy, 2009). The MPS is a
recently developed 16 item measure of Machiavellianism. According to Dahling et al. (2009) the
MPS captures a tendency to mistrust, manipulate, and control others as well as proclivity to
status seeking behavior. In the current work the MPS and MACH-IV were strongly correlated (r
= .54).
Narcissism
Narcissistic Personality Inventory 40 item version (NPI; Raskin & Terry, 1988). The NPI
40 is a very common measure of Narcissism used in non-clinical Narcissism research. It captures
a broad range of constructs that are more or less related to the construct of Narcissism. For the

21

purposes of this study, the Raskin and Terry (1988) factors of Exploitativeness and Entitlement
were scored and examined rather than the overall scale as the available research suggests that the
overall score conflates many different constructs (e.g. Ackerman, Witt, Donnellan, Trzesniewski,
Robins, & Kashy, 2011).
Psychological Entitlement. (Campbell, Bonacci, Shelton, Exline, & Bushman, 2004) This
9-item instrument captures exaggerated perceptions of deservingness. Campbell et al. (2004)
designed the scale as a standalone measure of Psychological Entitlement to avoid problems
associated with the Psychological Entitlement subscale of the NPI (i.e., poor face validity, poor
reliability, and forced-choice format). The resultant scale does have a higher internal consistency
then the NPI entitlement scale (as = .82-.86 versus .30-.48) and correlates moderately with the
NPI entitlement scale (r = .40).
Psychopathy
Self-Report Psychopathy Scale III (SRP–III–R12; Paulhus, Hemphill, & Hare, 2007).
This is a 64-item inventory designed to measure subclinical psychopathy. The overall scale can
be divided into four 16-item subscales: Interpersonal Manipulation, Callous Affect, Erratic life
style, and Criminal Tendencies. However, evidence suggests little discriminant validity for these
content scales (e.g., Witt, Donnellan, Blonigen, Krueger, & Conger, 2009). Thus for the current
research only the total score was used.
Fearless Dominance and Impulsive Antisociality (Witt, Donnellan, & Blonigen, 2009).
Fearless Dominance and Impulsive Antisociality represent the two factors of psychopathy in the
Psychopathic Personality Inventory (PPI; Lilienfeld & Andrews, 1996). Witt et al. (2009) created
proxy measures of these traits from the 120 item IPIP. Existing psychopathy measures appear to
adequately tap Impulsive Antisociality but the PPI and its proxy measures are the only existing

22

self-report measures of psychopathic traits that tap Fearless Dominance. Therefore, these
measures were included in this study in the interest of comprehensiveness and expanding the
nomological network of this potentially important construct.
Measures of Psychological Perceptions of Economic Decision-Making Games. To
evaluate psychological perceptions of the gameplay experience and participant preferences, I
included two questions at the end of the lab gaming session. The first question asked participants
to indicate how much they enjoyed playing their respective game on a five point scale from “did
not enjoy at all” to “enjoyed very much.” The second question asked them to assess the minimal
amount of points they would be willing to accept from their partner (this is sometimes referred to
in the economic literature as the participant’s “minimal acceptable offer”) and was only
administered to Ultimatum game participants. Participants indicated their preference by selecting
a whole number from 1-9.
CHAPTER 3: RESULTS
For the following sets of analyses I begin by assessing the results of the basic (noncompetitive) games and comparing these results with those found previously in the literature.
After establishing these effects, I then evaluate my three research hypotheses:
1. Does the addition of competition affect proposals and acceptance rates such that
participants offer less and accept less when competition is present?
2. Do people react to unfair competition by altering their proposals and acceptance rates
in a manner that suggests reconciliatory/punitive behavior?
3. Do maladaptive personality traits predict variability in proposals and acceptance rates
and do these effects (if present) vary in size dependent on game type?
Because gender has been discussed previously with regard to both game outcomes (e.g., Eckel &

23

Grossman, 2001) and procedural justice (Hack & Lammers, 2009) I also examine gender
alongside all analyses conducted.
Preliminary Analyses: Non-Competitive Ultimatum and Dictator Results
Acceptance Rates (Ultimatum). In total, participants lost 12 out of 24 rounds. In 6 of
these loss trials, they were randomly offered a fair offer (i.e., 4 or 5 points) or an unfair offer
(i.e., 1 or 2 points) by the computer. Separate averages of participants’ responses to the
computer’s fair and unfair offers were computed (where 1 = accepted and 0 = rejected). Thus,
this variable reflects the proportion of fair and unfair offers that were accepted. A paired
samples t-test revealed that participants were significantly more likely to accept fair offers (M =
.98, SD = .07) than unfair offers (M = .27, SD =.31) t(161) = 29.16, p < .001, d = 3.74. The mean
in this instance can be interpreted as the average percent accepted. In other words, this result
indicates that when the offer was 4 or 5 points (a fair split) participants accepted it on average,
98% of the time, whereas when the offer was 1 or 2 points (an unfair split) participants accepted
it on average, 27% of the time. This finding is consistent with previous findings in the economics
literature suggesting that offers of less than 20% of the pot are often rejected (e.g., Camerer &
Thaler, 1995).

3

Proposals (Ultimatum and Dictator). In total, participants won 12 of the 24 rounds.
Separate averages of participants’ offers to their opponent were computed for both the noncompetitive Ultimatum and non-competitive Dictator games. An independent samples t-test
revealed that participants offered significantly less to their opponents on average in the Dictator
game (M = 3.23, SD = 1.33) than in the Ultimatum game (M = 3.68, SD = .86) t(152.94) = 3.002,

3

Acceptance rates of fair and unfair offers did not differ significantly by gender
24

4

p = .003, d = .41 .
Taken together, the results of the acceptance rate and proposal analyses suggest that these
non-competitive games align nicely with the outcomes observed previously in the literature and
support the use of these games as a basis of comparison for the competitive variants of the games
carried out in the current work. Thus the typical participant in these non-competitive games
offers larger amounts (closer to equal) in the Ultimatum game and smaller amounts in the
Dictator game. Participants reject fair proposals 2% of the time and reject low proposals about
73% of the time.
Assessing the Effect of Competition on Game Outcomes
Acceptance Rates (Competitive vs. Non-competitive Ultimatum). Hypothesis one states
that the introduction of competition should affect acceptance rates such that the acceptance rate
of unfair offers will be higher in the competitive Ultimatum game than in the non-competitive
game.
First, overall acceptance rates were calculated across advantaged, matched, and
disadvantaged conditions (6 rounds each; 18 total) for both fair and unfair offers in the
competitive Ultimatum game. A paired samples t-test indicated that participants were
significantly less likely to accept unfair (M = .35, SD = .36) than fair offers (M = .97, SD = .11)
5

t(310) = -30.18, p < .001, d = 2.45. This finding replicates the high level of acceptance for fair
offers observed in the non-competitive Ultimatum game (MNon = .98, MComp. = .97). However,
4

There was no main effect of gender on Ultimatum and Dictator proposals and no interaction
between gender and game type.
5
Gender differences were found for Unfair offers such that women were more likely to accept
unfair offers than men (Women: M = .39, SD = .38; Men: M = .25, SD = .31) t(160.431) = 3.246, p = .001, d = .40 an effect that has been demonstrated previously in the literature in noncompetitive games (Eckel & Grossman, 2001) but was not found in the non-competitive
Ultimatum conducted in the present work.
25

the acceptance of unfair offers in the competitive Ultimatum game was significantly higher than
in the non-competitive Ultimatum game (MNon = .27 MComp.= .35) t(370.869) = -2.577, p =
.010, d = .24. These results suggest that the overall effect of competition was such that
participants were more likely to accept an unfair offer when competition was present.
These results are consistent with the first hypothesis offered in this dissertation such that
the acceptance rates of low offers in the competitive game were significantly higher than those in
the non-competitive game. These findings suggest that proposers and responders are aware that
the distributive justice norm has shifted from equality to equity in that their acceptance behavior
(higher acceptance of low offers) reflects a seeming acceptance in this shift.
Proposals (Competitive vs. Non-Competitive Ultimatum and Dictator). Hypothesis one
also states that proposals in competitive games should be lower than in non-competitive games.
Additionally, previous research suggests that proposals in the Dictator games should be lower
than in Ultimatum games (e.g., Kahneman, Knetsch, & Thaler, 1986). To test the overall effect
of competition (present vs. absent) and game type (Dictator vs. Ultimatum) had on proposals, I
conducted a 2 X 2 between-subjects ANOVA with game type and competition as separate
factors. The results of this analysis revealed a significant main effect for game type F(1, 889) =
91.151, MSE = 107.614, p < .001, d = .80 such that, across competitive and non-competitive
games, participants made smaller proposals of points in the Dictator game (M = 2.78, SD = 1.25)
than in the Ultimatum game (M = 3.56, SD = .93). This analysis also revealed a significant main
effect for the presence of competition F(1, 889) = 47.83, MSE = 56.47, p < .001, d = .47 such
that participants playing a competitive game were less generous in their proposals (M = 2.89, SD
= 1.23) than participants playing a non-competitive game (M = 3.45, SD = 1.09).
Importantly, there was also a significant game type by competition interaction F(1, 889)

26

= 16.50, MSE = 19.48, p < .001. To break down this interaction I followed it up with separate
independent samples t-tests for the Dictator game t(156.989) = 5.99, p < .001, d = .67 (MComp =
2.34, SD = 1.22; MNon = 3.23, SD = 1.33) and the Ultimatum game t(354.56) = 2.68, p = .010, d
6

= .25 (MComp = 3.44, SD = .95, MNon = 3.68, SD = .86). This interaction is represented
graphically in Figure 1. As can be seen in the Figure, competition and the absence of the
possibility of proposal rejection both contribute to lower proposals but the combination of these
7

two situational aspects results in especially low proposals .
Hypothesis one states that competition should have an effect on game proposals such that
they will be uniformly lower across both Ultimatum and Dictator games. The preceding analyses
were consistent with this prediction. Moreover, there were main effects for both competition and
game type as well as significant interaction between the two. This result was not hypothesized
but does suggest that the unique combination of the presence of competition and the absence of
the ability to reject proposals has an especially strong effect on participants’ proposals.
Individuals are the least egalitarian when competition is present and rejection is absent.
Assessing the Effect of Unfair Competition on Game outcomes
Acceptance (Ultimatum). Hypothesis two states that manipulating the fairness of the
competition will make players aware of a procedural injustice in the game. This should cause
them to adjust their acceptance rates of unfair proposals up or down depending upon whether
they were the benefactor or the victim of the injustice. When they lose the game and they had the
advantage, participants should be more likely to accept an unfair proposal than when the
6

Effect sizes for this analysis are based on the larger standard deviation because a pooled
standard deviation was not available.
7
This analysis was also run controlling for gender and it did not appreciably affect the results.
27

competition is equal or they are at a disadvantage because they feel they are more deserving of
the outcome. In contrast, when players lose at a disadvantage they should be significantly less
likely to accept a low proposal than when competition is equal or they are at an advantage
because they have been doubly insulted (i.e., the procedure did not favor them and neither did
the distribution of the pie). A repeated measures ANOVA with a Greenhouse-Geisser correction
was conducted to examine the effects that the manipulation of the fairness of the competition
8

(advantaged, matched, disadvantaged) had on the acceptance rates of unfair proposals . The
overall F-test was significant F(1.917, 620) = 6.309, MSE = .262, p = .002, indicating that
manipulating the fairness of the competition had an overall effect on the acceptance rates of
unfair proposals. Post hoc tests revealed that acceptance rates for the advantaged trials (M =.38,
SD = .41) were significantly higher than the acceptance rates for both the matched trials (M =
.35, SD = .40; p = .025, d = .07) and the disadvantaged trials (M = .33, SD = .39; p = .001, d =
.13). Acceptance rates for the matched trials were higher but not significantly different from
those of the disadvantaged trials (p = .202). This pattern of results, as well as the average
acceptance rate for the non-competitive Ultimatum is represented in Figure 2. Overall, the
pattern of results is consistent with the prediction that manipulating the fairness of competition
affects acceptance rates such that individuals adjust their behavior when they lose at an
advantage or disadvantage. Specifically, when losing at an advantage, participants are more
likely to accept lower offers than when they were on an equal playing field or when they were at
a disadvantage whereas when losing at a disadvantage their acceptance rates are lower than when
they lose at an advantage. However, the associated effect sizes accompanying these results

8

Fair proposals were also tested to determine if manipulating the fairness of the competition had
an effect on acceptance rates, the overall F-test was not significant F(1.954, 620) = .266, MSE =
.001, p = .766 suggesting no effect.
28

suggest that this is a small effect. What remains to be seen is whether a 3% upward or downward
shift in acceptance rates is of practical significance. A test of gender differences suggested an
interaction between Fairness of Competition and Gender F(1.914, 610) = 3.051, MSE = 1.28, p =
.05. As can be seen in Figure 3, men’s acceptance rates differed from women’s in all conditions
and differed especially in the disadvantaged condition. Specifically, women’s acceptance rates in
the disadvantaged condition (M = .38) did not differ from the matched condition (M = .38)
whereas men’s acceptance rates in the disadvantaged condition (M = .18) differed significantly
from acceptance rates in the matched condition (M = .26). Previous research suggests that
women are particularly attuned to the procedural fairness of Ultimatum games but that it does
not affect the behavior of men in these games (Hack & Lammers, 2009). However, the current
pattern of results suggests that men’s acceptance rates in situations of unfair procedures are more
nuanced than women’s. Men were more likely to react to unfair offers when they lost at a
disadvantage than women were.
Proposals (Ultimatum and Dictator). Hypothesis two also states that manipulating the
fairness of the competition should affect game proposals such that participants will offer larger
amounts to an opponent when the role of proposer was won with an unfair advantage relative to
wins on an equal playing field whereas the proposals should be smaller when participants won
the role of proposer at a disadvantage. It is also possible (though not predicted) that these
conditions could interact with game type, so it is important to assess both factors concurrently. In
order to accomplish this a 2 X 3 repeated measures ANOVA using a Greenhouse-Geisser
correction with game type (Ultimatum vs. Dictator) as a between-subjects variable and Fairness
(advantaged, matched, disadvantaged) as a within subjects variable was conducted. Cell means
and standard deviations are presented in Figure 4.

29

The test of the between-subjects effect of Game type (Dictator vs. Ultimatum) was
significant F(1, 628) = 161.019, MSE = 579.128, p <.001. Suggesting that, across all levels of
fairness, Ultimatum proposals were significantly higher (M = 3.44, SD =.95) than Dictator
proposals (M = 2.34, SD =1.22) d = .90. The results also suggested an overall effect of Fairness
F(1.879, 1256) = 74.960, MSE = 18.696, p < .001 such that proposals differed as a result of
whether the competition was fair or unfair. Moreover, there was a significant linear trend in
means F(1, 628) = 120.068, MSE = 34.926, p < .001. As can be seen in Figure 4, there was a
clear decrease in proposals from the advantaged (M = 3.05, SD = 1.31) to matched (M = 2.91, SD
= 1.28) to disadvantaged (M = 2.72, SD = 1.28) rounds but no fairness by game type interaction
F(1.879, 1256) = 2.248, MSE = .561, p = .110. Post hoc tests revealed that all three levels of
Fairness differed significantly from one another (ds = .11 - .26). In short, individuals did offer
more to their opponents when they won at an advantage and less to their opponents when they
won at a disadvantage relative to when they were competing on equal grounds. A test of gender
differences revealed no difference between men and women in proposals across competition and
game type.
Taken together these results support the predictions made in hypothesis two that
participants are sensitive to the procedural fairness of competition and that acceptance and
proposals reflect this sensitivity such that when they are the benefactor of an injustice they are
more generous to the victim whereas when they are the victim of the injustice they are more
likely to punish a partner who attempts to exploit the situation.
The Association Between Maladaptive Personality Traits and Game outcomes
The inter-correlations between the measures of maladaptive personality traits used in
these studies are contained in Table 2. As can be seen in the table, convergent correlations

30

ranged from small to large for Psychological Entitlement (NPI-Ent & PE; r = .40),
Machiavellianism (MACH-IV & MPS; r = .54), and the Impulsive and Antisocial aspects of
psychopathy (IA & SRP; r

= .70). Consistent with previous research, Machiavellianism

(measured by both the MACH-IV and MPS) was strongly correlated with the Impulsive and
Antisocial aspects of psychopathy (rs = .51 - .57) whereas it was negatively to unrelated to
Fearless Dominance depending on the measure of Machiavellianism examined (rs = -.15 and .02
for MACH-IV and MPS, respectively). Altogether, Fearless Dominance exhibited the smallest
correlations with the other measures while all other measures yielded small to large positive
correlations with all other measures suggesting relatedness among these aspects of the so-called
“dark triad” and the relative independence of Fearless Dominance from these constructs.
Hypothesis 3 made specific predictions about the relations between maladaptive
personality traits and game outcomes. Correlations between personality traits and acceptance
rates are reported in Table 3. As can be seen in the table, Machiavellianism as measured by the
MACH-IV was the lone significant (negative) predictor of acceptance rates and was only
predictive of acceptance rates in the non-competitive Ultimatum game. This finding suggests that
individuals scoring higher on Machiavellianism were more likely to punish a partner for
behaving unfairly than individuals scoring lower on Machiavellianism and are consistent with
the results reported by Meyer (1992) who found that High Machs were less likely to accept
unfair offers than Low Machs in multiple trial games. However, given the number of
comparisons, interpretive caution is warranted until this result has been replicated. Table 4
reports associations between personality traits and proposals. As can be seen in the table, there
were no significant predictors of non-competitive game proposals. The largest coefficients were
in the non-competitive Dictator game for Psychological Entitlement (as measured by the

31

Campbell et al. scale; r = -.15, ns), Machiavellianism (as measured by the Machiavellian
Personality Scale; r = -.14, ns), and Impulsive Antisociality (as measured by the IPIP scale: r =
.14, ns). These results are likely due to a combination of the lack of power from these studies
(i.e., small sample sizes) and the seemingly small size of the coefficients for these personality
traits in relation to these outcomes.
Table 4 also contains associations between personality traits and competitive proposals.
Machiavellianism (as measured by both the MACH-IV and the Machiavellian Personality Scale)
and Psychological Entitlement (as measured by the NPI) were significant negative predictors of
proposals in the competitive Dictator game. Thus when competition was present and rejection
was absent people scoring higher on Machiavellianism and Psychological Entitlement were more
likely to take advantage of the situation by keeping more of the points for themselves than people
scoring low on these measures. Psychological Entitlement (as measured by the Campbell et al.
scale) was the only significant negative predictor of competitive Ultimatum proposals. This
suggests, if anything, that entitled individuals are less sensitive to the fairness norms associated
with these situations and still ask for more points than non-entitled individuals. The fact that
Machiavellianism was only predictive of proposals in the Dictator game and not in the
Ultimatum game suggests that high scorers on this measure are attuned to the features of the
game and only make self-interested offers when it is “safe” to do so is consistent with the
assertion that high Machs are income maximizers whereas the finding that high scorers on
measures of Psychological Entitlement show a rigidity in their proposals such that they expect
more of the pot regardless of whether rejection is a possibility is also consistent with theorizing
on the construct. Again, although these associations are more or less consistent with predictions,
their size and inconsistency cautions against drawing strong conclusions. The generally small

32

estimates of these effects for personality variables suggest that these games represent a situation
with strong “press” and thus personality may not have much of an effect above and beyond the
features of these situations.
One final aspect of Hypothesis three is a formal test of the Hilbig and Zettler’s (2009)
assertion that the association between personality traits and proposals is dependent on the
presence or absence of rejection such that coefficients representing the association between
personality traits and game outcomes will be larger in Dictator games than in Ultimatum games.
To test this assertion I conducted a series of multiple regressions examining the interaction
between each personality trait and game type (Ultimatum vs. Dictator) for predicting proposals
while controlling for the presence/absence of competition. Utilizing this analytic technique
resulted in no statistically significant interactions, suggesting no overall effect of game type on
the associations between individual differences and game proposals. Thus, although the assertion
that the Dictator game affords for more opportunity for the expression of individual differences
than the Ultimatum game, I found no formal empirical evidence to support this hypothesis using
a two-tailed significance test with an alpha level of .05.
Ancillary Analyses: Psychological Perceptions of Economic Decision-Making Games
Participants indicated how much they enjoyed playing their respective game on a five
point scale from “did not enjoy at all” to “enjoyed very much.” To evaluate the effects that
competition and game type have on the general enjoyment of the game I conducted a 2 by 2
between subjects ANOVA with game type and competition entered as separate factors. Results
indicated significant main effects for both game type F(1, 887) = 10.400, MSE = 11.886, p =
.001 and competition F(1, 887) = 62.927, MSE = 71.798, p < .001 that was qualified by an
interaction between game type and competition F(1, 887) = 4.029, MSE = 4.597, p = .045. An

33

examination of the means (represented graphically in Figure 4) revealed that on average, noncompetitive games were seen as less enjoyable than competitive games and Dictator games were
rated as less enjoyable than Ultimatum games with the non-competitive Dictator game being
rated as particularly less enjoyable than the other variants.
I also investigated individual difference predictors of game enjoyment, results indicated
that high scorers on the Campbell Psychological Entitlement scale enjoyed the game slightly
more (r = .11, p <. 05) than low scorers whereas people who scored higher on the self-report
psychopathy scale (r = -.08, p <. 05) and the Impulsive Antisociality scale (r = -.09, p <. 05)
enjoyed the games less than lower scorers. The correlations between these variables and
enjoyment separated by level of competition and game type are presented in Table 5. However,
these coefficients are small and if anything, speak to the general modesty of individual difference
effects evaluated in the current work.
In the Ultimatum games participants were asked to indicate the minimal amount of
money that they would be willing to accept (minimal acceptable offer) at the completion of the
study. An independent samples t-test revealed that competition lowered participants’ minimal
acceptable offer significantly (Non-Competitive: M = 2.87, SD = 1.01; Competitive: M = 2.55,
SD = 1.18) t(367.420) = 3.018, p = .003, d = .28. This suggests, along with the observed
behavioral measures, that a participant’s mental expectations of what is considered a fair offer do
in fact shift when competition is added to the equation. It is also worth noting that the average
actual offer in these games was reliably 4/5 pt higher than the average minimal acceptable offer
(Mdiff = .81 - .89) which is made even more remarkable with the realization that participants
never received any form of feedback concerning their offers and thus were left to their own
devices to determine what constituted a fair offer. Individual differences in personality were

34

largely unrelated to participants’ minimal acceptable offer when considered across levels of
competition or together. One notable exception is that Machiavellianism (as measured by the
MACH-IV) was significantly positively associated with the minimal acceptable offer in the noncompetitive game (r = .18, p < .05) whereas it was unrelated to the minimal acceptable offer in
the competitive Ultimatum game (r = .02, ns). However, Machiavellianism was unrelated to
actual game behaviors so this finding raises some interesting questions about the construct of
Machiavellianism and its relation to observable behavior in these kinds of tasks.
CHAPTER 4: DISCUSSION
The goal of this dissertation was to better understand how competition and fairness
concerns affect people’s behavior in situations in which resources are allocated. Specifically, I
addressed how fair and unfair competition affects individuals’ decision-making when the
division of resources is their primary concern. The current work also addressed whether
individual differences in maladaptive personality traits have a moderating effect on these
decision processes. To address these issues in a systematic setting, I modified economic
decision-making games to create situations of fair and unfair competition. These games were
ideal for my purposes because they are well-established, tightly controlled, and their features are
easily manipulated. Furthermore, these games involve the division of a finite resource between
two individuals and thus provide a direct, albeit simplified, analog to important real world
situations. Humans often compete for resources and sometimes the competition is unfair (i.e.,
one competitor has an edge that he or she does not deserve). In the current work I manipulated
the competition in these games such that on some trials participants would be evenly matched
(fair competition) and on other trials they would be at an advantage or disadvantage that they did
not deserve (unfair competition). Finally, I collected information about participants’ personalities

35

using self-reports to better understand the role that individual differences play in human
decision-making.
To achieve my overarching goal, I addressed three research questions. First, I evaluated
the effect that adding competition to these games had on proposals and acceptance rates. Next, I
built upon this work by manipulating the procedural fairness of the competition – creating fair
and unfair competitive rounds -- and examined the effects that this had on game outcomes.
Finally, I examined associations between individual differences in personality and proposals and
acceptance rates across all game types and levels of competition. Results revealed that the
addition of competition decreased proposals from an average of 3.45 points out of 10 to 2.89
points out of 10 and increased acceptance rates of unfair offers (i.e., offers of 2 pts or less out of
10) from 27% to 35%. These effects were small to moderate in size. Unfair competition affected
proposals and acceptance rates in a pattern that suggested participants were aware of the
unfairness and attempted to rectify it. For example, when participants won at an advantage they
offered their opponents an average of 3.04 points whereas when they won at a disadvantage they
only offered 2.71 points, representing a small effect size. Similarly, when participants lost at an
advantage they accepted unfair offers 38% of the time versus 33% when they lost at a
disadvantage. Finally, there was little evidence that individual differences in maladaptive
personality traits were consistent predictors of behavior in these games regardless of the level of
competition, fairness, or game type. At best, the effect sizes were small and the vast majority of
coefficients were not statistically significant.
All in all, this work represents a contribution to the behavioral economics literature as
well as to the social and personality psychology literature because it extends work on the
economic decision-making paradigms and gives insight into individuals’ reactions to procedural

36

injustice. To my knowledge, it represents the first study using economic decision-making games
that has not only manipulated the level of competition but also manipulated the fairness of the
competition. Moreover, it provides interesting insights into the behavior of people in competitive
circumstances by suggesting that people generally recognize injustice and make an effort to
address it. Finally, it adds to a growing literature that examines how strongly individual
difference measures are related to behaviors in these long-standing economic paradigms.
Consistent with previous research (e.g., Hoffman et al., 1996), I predicted that the
addition of competition for the role of proposer would affect game outcomes such that proposers
would offer less to responders and responders would be willing to accept less from proposers
when competition was present. The reasoning for this prediction is that the nature of competition
creates a situation in which the person who wins the role of proposer believes that she or he has
earned the right to more of the resource. Consistent with this prediction, competition resulted in
lower proposals than in the non-competitive games (for both Dictator and Ultimatum games).
Likewise, competition resulted in higher acceptance rates than in the non-competitive games, an
effect that suggests losing players are aware of and conform to the norm of awarding the winner
more of the resource. The effect of competition was stronger on proposals (d = .47) – when
participants were actively making a decision – than on acceptance rates (d = .24) where
participants had to make an all or none decision about an offer from the computer. This
difference might be partially explained by the greater reliability of proposals (a continuous
variable) than the acceptance rates (a series of dichotomous decisions) but nonetheless these
effects are not trivial. Interestingly, there was also significant interaction between competition
and game type such that proposals were especially low in competitive Dictator games. It appears
that the combination of competition for resources and the absence of punishment for self-

37

interested behavior results in the strongest “winner takes all” mindset.
It appears that the addition of competition alters the implicit norm of what constitutes a
fair distribution from one of equality to one of equity. In other words, participants seem to
accept, on some level, that the winning player has earned the right to more of the pot. Although
this is not necessarily a novel finding (see Hoffman et al., 1996), it does add to the literature as
an extension of previous work in that the competition here took place over multiple rounds and
in that wins and losses were controlled for even comparison.
The second prediction was that manipulating the procedural justice of the situation (i.e.,
the fairness of the competition) would result in behavior suggestive of an attempt to rectify the
injustice on the part of the participants who benefitted unfairly from this advantage. This
situation was experimentally created by manipulating the difficulty of questions participants (and
their virtual partners) had to complete. On some rounds the partners had to answer questions of
the same difficulty (i.e., both easy or both hard) whereas on other rounds the participant was at a
competitive advantage (i.e., completed easier questions than their partner) or at a competitive
disadvantage (i.e., completed harder questions than their partner). To my knowledge, the
procedural fairness manipulation used in this research has never been used before in conjunction
with Dictator and Ultimatum games. Thus, this experimental paradigm extends of previous work.
Results suggested that participants took steps to address the unfairness by adjusting their
acceptance rates and proposals accordingly.
Acceptance rates in the competitive Ultimatum were higher (38%) when participants lost
than when they had a competitive advantage (i.e., they were beaten by a player who had to
answer harder questions than they did) and lower (33%) when participants lost when they were
at a competitive disadvantage (i.e., they were beaten by a player who had to answer easier

38

questions than they did) than when they were competing with another player on equal grounds
(35%). However, these effect sizes were small. These results are surprising, especially when
considered in the context of non-competitive acceptance rates. In the non-competitive Ultimatum
game the average acceptance rate for unfair proposals was 27%. Thus, despite the fact that
responders in these situations could reject these lopsided offers and improve their own chances
of winning a prize with relatively little cost to themselves they did not do so. In fact, the
acceptance rates for all conditions in the competitive game (fair or unfair) were higher than for
the non-competitive game. However, a more interesting comparison is whether fairness concerns
can moderate the “winner take all” mindset of proposals in these competitive games (especially
the Dictator game).
Results did indeed indicate that manipulating the fairness of competition had small to
moderate effects (ds = .11-.26) on participants’ average proposals. Proposals (in both the
Ultimatum and Dictator games) were higher in situations where participants won at an advantage
(3.05) and lower in situations when they won at a disadvantage (2.72) than in situations where
they won on equal grounds (2.91). However, in comparison to the average proposal for noncompetitive games (3.45) these effects look much larger. Thus participants were more generous
in their proposals when they were the benefactors of an injustice (even when the opportunity for
rejection was absent) and less likely to accept an unfair offer when they were the victims of the
injustice. The fact that these results were not moderated by game type suggests that fairness
concerns affected participants’ decisions even in a game where they could take as much as they
wanted after winning without any threat of retribution.
The present results offer a somewhat positive perspective on human psychology. The
results suggest that individuals are sensitive to procedural injustice in the bargaining situations

39

created by economic decision-making games (and likely others where fair procedures are
desired) and that, all else being equal, they will take steps to rectify the injustice to some extent
when compared to those trials in which competition was fair. The fact that this kind of
compensatory behavior was also evident in the Dictator game suggests that a norm of fairness is
strong and often overrides personal concerns because participants in these game were under no
obligation to give points to their partners and could take the points for themselves without any
fear of retribution. However, this represents only one study with a relatively circumscribed
sample and thus cautions about over-generalization of findings at this point are warranted.
The third hypothesis was that individual differences in personality would predict
proposals and acceptance rates. However, personality effects were inconsistent at best and the
few significant associations that did arise were small in size. This was unexpected as previous
work has identified individual difference predictors of these behaviors (e.g., Hilbig & Zettler,
2009). Although it makes intuitive sense that individual tendencies toward greed and
manipulativeness should predict exploitative behavior in competitive situations, I found no
evidence to substantiate this claim in the current work.
As always, the absence of evidence of an effect does not necessarily mean that the effect
does not exist. It is quite possible that these effects are real but small and thus hard to detect. It is
possible that the sample size in this report was not sufficient to detect these effects (i.e., the
sample was underpowered). However, the total sample size in this study was relatively large (n =
893) in comparison to the sample sizes in previous studies that were successful in finding
reliable individual difference prediction of game outcomes. For example, the sample size
reported in Hilbig and Zettler (2009) was 134 participants, roughly 15% the size of the sample
collected in this dissertation. Thus it is not likely that the paucity of individual difference effects

40

in the current work can be attributed to power issues. On a related note, it is difficult to comment
on the size of these effects given that there is little consensus on what the benchmark effect size
for a personality trait prediction of a behavior in a laboratory setting should be. For example,
Hilbig and Zettler (2009) reported a regression coefficient of -.20 between Honesty-Humility and
Dictator proposals whereas Witt et al. (2009) reported a range of effect sizes (rs = .00 - .33) for
personality trait prediction of hot sauce allocation in a laboratory task. Thus, judgment on the
relative size of these effects should be withheld until a more of a consensus on this issue is
reached.
A more reasonable explanation for these findings (or lack thereof) is that the situation
created by these games has a strong “press” and that even though the variance differs between
game types it does not differ enough to suggest a heavy influence of individual differences. That
is, the implicit norms of distributive and procedural justice in these games are strong enough to
wash out individual difference effects especially in light of the strength of the situational
manipulations used here. Based on these results it seems that bargaining situations – especially
those that involve competition – have a reasonably strong set of implicit norms associated with
them analogous to real world situations were behavior is heavily constrained (e.g., a funeral) and
thus individual differences may not be responsible for the lion’s share of the variance in any
given individual’s behavior in these situations.
However, given that the assessment method used herein was self-report and the traits
assessed are socially undesirable (e.g., greed) it is also possible that the lack of association could
be the result of the chosen assessment method. That is, individuals may be unable, or at least
unwilling, to report on these characteristics of their own personality and thus a well-acquainted
observer would be better suited to the task. So perhaps observer reports would provide higher

41

validity coefficients than self-reports in this circumstance. However, an opposing case could be
made suggesting that the “letter of reference effect” (i.e., the tendency of individuals to nominate
informants who will give them positive ratings) would negate the potential advantage of observer
reports. The best solution would be to obtain both self and informant reports in future studies.
Collecting both sources of information would allow the evaluation of both sources predictive
validity in this experimental context.
A second part of the individual difference hypothesis – suggested previously in the
literature (Hilbig & Zettler, 2009) – was that the coefficients between individual differences and
game outcomes would be larger in the Dictator game than in the Ultimatum game. The rationale
for this moderation hypothesis is that the opportunity to reject proposals places constraints on the
preferences of individuals who would otherwise propose smaller amounts. For example, a selfish
person, by definition, should desire more of the resource than a non-selfish person. In the
Dictator game, this person may be as selfish as they wish because his or her partner has no
choice but to accept whatever is offered whereas in the Ultimatum game a selfish proposal has
the very real possibility of being rejected and the consequence of the greedy proposer being left
with no points at all. For this reason, even selfish people may look egalitarian in the Ultimatum
game while showing their true colors in the Dictator game.
Formal tests of the Hilbig and Zettler (2009) moderation hypothesis did not provide any
statistical evidence that the individual differences found in my work had stronger effects in the
Dictator game than in the Ultimatum game. However, in some cases the correlations appeared
slightly larger in the Dictator game than in the Ultimatum game and the variance of proposals
was larger in the Dictator games (both competitive and not) than in the Ultimatum games. Thus,
there may be some veracity to this claim, but the evidence in this report is not substantial.

42

Limitations
Although this research provides several novel and informative findings about conditions
associated with economic decision-making, and more broadly, about the way that individuals
react to injustice, it is not without its limitations. One limitation is the current work’s reliance on
college samples. This is often cited as a limitation of psychological and behavioral economics
research (e.g., Sears, 1986). Although in many cases the use of such convenience samples is not
a concern, it is possible that college students’ decision-making tendencies differ from that of the
general population and therefore their responses are not generalizable. In fact, there is now ample
evidence to suggest that there are cross-cultural differences in Ultimatum and Dictator proposals
(e.g., Henrich, Heine, & Norenzaya, 2010). For example, when comparing across cultures, U.S.
(non-student) participants are at the upper end of proposals in both the Ultimatum and Dictator
game (i.e., ~47% of the total pot, range: ~25% to ~51%). Therefore, although the results
presented here with regard to the non-competitive games are more or less consistent with
previous research using both college and reasonably educated North American samples, caution
should be taken when generalizing these results to other populations and it is important to
replicate these procedures with other samples to better understand potential boundary conditions.
Another limitation of this research may have been the use of the word “game” in the title
and description of the study on the HPR web site (though this was constant for all variants, even
non-competitive). It has been demonstrated that subtle changes in the wording of experimental
advertisements can have unseen selection effects in subsequent studies (e.g., Carnahan &
McFarland, 2007). Admittedly, the word game was partially an intentional attempt to increase
lab attendance (attrition has become a serious problem in hybrid online/lab studies within the
department during the past year), but I cannot rule out the possibility that this could have

43

affected the results. It is possible that many of the participants in this study came into it with a
“gaming” mindset and that this could have augmented the effects of the competition
manipulation. It is also possible that a subset of the population that enjoy games and are extra
competitive sought this study out specifically. Because of this, it might be useful to collect a
study with more generic advertising to see if the effects demonstrated here are replicated.
However, given that most economic decision-making studies involved the division of money or
points, it is unclear how one would go about advertising such a study without mentioning
something about monetary or material reward and/or competition or gaming.
Another limitation is the sample size of the non-competitive studies. The sample sizes of
these studies were smaller than that of the competitive studies. This was partially by design (the
proposed sample size for the non-competitive studies was 150 whereas the proposed sample size
for the competitive studies was 300) but was also an issue with the time frame and supply of
participants for data collection. Specifically, the semester in which these data were collected
suffered from an excess of experiments and a limited supply of experimental participants and
thus the sample size fell just short of the target number. Ideally the samples would all have been
of similar size. Thus the precision of estimates for the competitive games is greater than that of
the non-competitive games. This likely was not an issue for the estimates of game outcomes as
the sample sizes used in the non-competitive games dwarf that of the sample sizes typically
employed in the behavior economics literature. However, given the size of the correlations for
individual differences and game outcomes (or lack thereof), the effects of personality are
seemingly quite small and thus require very large sample sizes to be reliably detected.
Therefore, this work may not represent the best test of individual difference prediction of
economic decision-making.

44

A final limitation may be the choice of individual difference measures employed in this
work. Many of these measures such as the Narcissistic Personality Inventory and the MACH-IV
have known structural and validity issues (Ackerman et al., 2011; Hunter, Gerbing, & Boster,
1982). Thus, they may have been poor choices to include for the current research aims. However,
to combat this concern I included multiple measures of each construct and was still unable to
find consistent results. This suggests that even the new measures have significant flaws or that
the true effect size is really quite small. It also could be an issue of social desirability in that there
are stable individual differences in these non-desirable traits, but that these individuals might be
hesitant to express this through self-reports. Therefore, future work examining questions
involving undesirable personality traits – such those examined here – may benefit from the use
of alternative modes of measurement (e.g., informant report) in addition to traditional selfreports. It is also possible that the measures chosen for this work just are not relevant in these
contexts and that other individual differences that were not included are relevant. Hilbig and
Zettler (2009) were able to find effects for the Honesty-Humility factor of the HEXACO PI-R,
thus it is possible that other measures would be more successful towards this end. Toward this
end, future research should consider a broadband measure of personality in an attempt to capture
some more specific facets of personality not measured in the current work such as assertiveness
or conformity.
Future Directions
One future direction in line with this research may be to create procedural unfairness in a
non-competitive game. In the current games the procedural unfairness was obvious, but the
participant still had some amount of control over the outcome. For example, let’s say a
participant received hard questions on a given round of the game. Given this information, the

45

player knows that the round will either be fair (i.e., his or her opponent also had hard questions)
or it will be unfair (i.e., his or her opponent has easy questions). Even though the second scenario
seems bleak, there is still a chance that the participant can prevail or at least believe that she or
he can prevail. Now imagine a game where the participant knows that the decision rule for
choosing the winner was unfair, but he or she has no affect on the outcome. For example,
participants are told that the winner is determined by the computer but that the odds are affected
by the prestige of their university. What would players do in this situation? I suspect that the
same effects observed here would be also be seen in this variant of the game, but that the
conciliatory or retaliatory behavior would be stronger (i.e., participants would give more points
when winning at an advantage and would reject low offers more often when losing at a
disadvantage) than found in the current work.
Another future direction concerns the use of repeated interaction “partners” for these
games. Most Ultimatum and Dictator studies are conducted in a single-shot bargaining
interaction (e.g., Thaler, 1988). The current research expanded this to a multi-shot format where
participants ostensibly had multiple partners. Thus the games conducted here were essentially
repeated single-shot games. These games were constructed in this manner to allow for more
reliable estimate of individuals’ preferences than a typical single-shot game would afford while
also avoiding participant learning or familiarity effects. Although this type of design is useful for
experimental clarity and control because it avoids these issues, it does not mirror how bargaining
is usually conducted in the real world. Although it is true that bargaining often involves more
than one round, these rounds usually involve the same pair of partners. A future extension of this
work may be to have pairs of individuals bargain with or without competition over a number of
trials. This would extend the current work by making the competition and bargaining more

46

ecologically valid. Furthermore, the dyadic nature of this interaction would allow for a test of not
only how a player’s strategies change over time, but also of how these strategies interact with his
or her partner’s strategies.
Finally it may be useful to conduct a within-subjects study where participants compete in
both the ultimatum and dictator games (counterbalanced) using either a single-shot or multi-shot
format. This would allow participants to serve as their own controls and could provide
interesting insights into the general relatedness of behavior in both games as well as pinpoint
individuals whose behaviors are quite discrepant between games (e.g., individuals with generous
ultimatum proposals and stingy dictator proposals).
Conclusion
The current work represents a novel contribution to the economic and psychological
literatures. Not only does it expand upon and contribute to previous work using economic
decision-making games but it also expands the psychological understandings of how people
respond to the fairness of the context of a bargaining interaction between two individuals.
Overall, these results suggest that the old cliché “to the victor go the spoils” has some truth to it,
but could use some further qualifications.
The results of this study revealed that the introduction of competition shifts the normative
concept of the division of resources from one of equality to one of equity. Though, interestingly,
winners and losers were far less greedy and spiteful than they could have been. Thus, although
participants both in the role of proposal and responder appear to recognize the norm that in
competition the victor deserves more of the spoils the norm apparently dictates that he or she
does not deserve all of the spoils. This effect might explain why presidential candidates who win
their primaries often select their opponents as future running mates or appoint these individuals

47

to their cabinets. In a sense, this might be the candidate’s way of giving some of the pot back to a
good opponent.
The further introduction of unfair competition demonstrates that individuals do not like
unfair procedures and when given the opportunity they will make concessions to rectify these
procedures or to punish those who they perceive are exploiting the results of said procedures.
Thus, the amount of spoils the victor gets depends heavily on the processes that lead to the
victory. If he or she earned the victory via a competitive advantage he or she deserves fewer
spoils and attempts to give back to the disadvantaged opponent. This is not unlike the co-worker
who unfairly gains a promotion and promises to “put in a good word” for his or her
disadvantaged co-worker was passed over. Conversely, when the victor attempts to take
advantage of an unfair edge his or her opponent will take punitive action, if possible. Keeping
with the previous example, the co-worker who loses a rigged competition for a promotion might
engage in subversive acts toward his or her employer in an attempt to punish the system.
Although the current work found little evidence of a strong (or even medium-sized)
association between personality and behavior in these games, for the moment, the question of
whether individual differences matter in these situations remains open until more data have been
collected. Thus, the question of what kinds of people are sensitive to features of these situations
is still a matter of debate and deserves more empirical attention.
Finally, from a practical point of view, adapting these long-established paradigms for
studying competition has provided a new platform for research and suggests many interesting
extensions. It is my hope that by extending the literature in these ways I have pushed this area of
research toward a more ecologically valid model of bargaining and have begun to explore the
elements of bargaining and competition that until this point have been unstudied.

48

Table 1
Frequencies and Percentages for Demographic Variables by Game
NonNonCompetitive Competitive
Ultimatum
Dictator
(n = 162)
(n = 101)
n (%)
n (%)
Age
18
47 (29%)
14 (13.9%)
19
54 (33.3%)
32 (31.7%)
20
25 (15.4%)
26 (25.7%)
21
25 (15.4%)
13 (12.9%)
22
5 (3.1%)
8 (7.9%)
23
1 (.6%)
4 (4%)
24
1 (.6%)
2 (2%)
25
0 (0%)
0 (0%)
26 +
4 (2.5%)
0 (0%)
Missing
0 (0%)
2 (2%)
Year in School
1
84 (51.9%)
34 (33.7%)
2
27 (16.7%)
26 (25.7%)
3
33 (20.4%)
25 (24.8%)
4
17 (10.5%)
9 (8.9%)
5
1 (.6%)
7(6.9%)
6+
0 (0%)
0 (0%)
Missing
0 (0%)
0 (0%)
Gender
Women
97 (59.9%)
58 (57.4%)
Men
63 (38.9%)
43 (42.8%)
Did not Specify
2 (1.2%)
0 (0%)
Racial/Ethnic Group
White/Caucasian
132 (81.5%) 74 (73.3%)
Black/African American
8 (4.9%)
12 (11.9%)
Latino/Latina
4 (2.5%)
4 (4%)
Asian American
9 (5.6%)
7 (6.9%)
Racial/Ethnic Group not listed
8 (4.9%)
4 (4%)
Missing
1 (.6%)
0 (0%)

49

Competitive
Ultimatum
(n = 311)

Competitive
Dictator
(n = 319)

n (%)

n (%)

99 (31.8%)
75 (24.1%)
70 (22.5%)
38 (12.2%)
15 (4.8%)
7 (2.3%)
1 (.3%)
0 (0%)
6 (1.9%)
0 (0%)

88 (27.6%)
83 (26.0%)
58 (18.2%)
63 (19.7%)
13 (4.1%)
6 (1.9%)
1 (.3%)
0 (0%)
6 (1.9%)
1 (.3%)

101 (32.5%)
88 (28.3%)
69 (22.2%)
37 (11.9%)
13 (4.2%)
3 (1.0%)
0 (0%)

97 (30.4%)
86 (27.0%)
69 (21.6%)
54 (16.9%)
12 (3.8%)
0 (0%)
1 (.3%)

230 (74.0%)
79 (25.4%)
2 (.6%)

177 (55.5%)
139 (43.6%)
3 (.9%)

260 (83.6%)
15 (4.8%)
7 (2.3%)
20 (6.4%)
9 (2.9%)
0 (0%)

264 (82.8%)
24 (7.5%)
4 (1.3%)
23 (7.2%)
4 (1.3%)
0 (0%)

Table 2
Inter-correlations Between Individual Difference Measures
Measure
1
2
3
4
5
6
7
8
1. MACH
2. MPS
.54
3. NPI-EXP
.24
.33
4. NPI-ENT
.21
.42
.29
5. PE
.23
.51
.23
.40
6. SRP
.57
.57
.39
.33
.33
7. FD
.02
-.15
.29
.23
.09
.11
8. IA
- .04
.51
.55
.32
.26
.32
.70
Note: n = 893. Coefficients in Bold are significant at p < .05. MACH = MACH-IV, MPS =
Machiavellian Personality Scale, NPI-Exp = Narcissistic Personality Inventory Exploitativeness
Subscale, NPI-ENT = Narcissistic Personality Inventory Entitlement Subscale, PE =
Psychological Entitlement scale, SRP = Self-Report Psychopathy Scale, FD = Fearless
Dominance, IA = Impulsive Antisociality.

50

Table 3
Means, Standard Deviations, and Internal Consistency Estimates for Psychological Measures by
Study
NonNonCompetitive
Competitive
Competitive
Competitive
Ultimatum
Dictator
Ultimatum
Dictator
(n = 311)
(n = 319)
(n = 162)
(n = 101)
M
SD
α
M
SD
α
M SD α
M
SD
α
.36
.72
2.78
.33
.66 2.74 .34 .68
2.74 .35
.72
MACH
2.84
MPS
2.72
.52
.83
2.65
.49
.85 2.71 .50 .84
2.74 .51
.86
NPI-EXP
.39
.29
.58
.38
.29
.58 .36 .27 .54
.38 .29
.59
NPI-ENT
.29
.22
.44
.26
.20
.30 .27 .23 .48
.30 .23
.43
PE
2.59
.60
.85
2.54
.53
.82 2.64 .58 .85
2.61 .61
.86
SRP
2.43
.42
.93
2.43
.38
.91 2.30 .38 .92
2.41 .39
.92
FD
3.45
.42
.82
3.49
.42
.84 3.40 .49 .86
3.44 .47
.87
IA
2.47
.50
.87
2.43
.51
.89 2.31 .46 .86
2.44 .46
.87
Note: MACH = MACH-IV, MPS = Machiavellian Personality Scale, NPI-Exp = Narcissistic
Personality Inventory Exploitativeness Subscale, NPI-ENT = Narcissistic Personality Inventory
Entitlement Subscale, PE = Psychological Entitlement scale, SRP = Self-Report Psychopathy
Scale, FD = Fearless Dominance, IA = Impulsive Antisociality.

51

Table 4
Individual Differences and Acceptance Rates
nonCompetitive Ultimatum
competitive
(n = 311)
Ultimatum
overall
overall
advantaged
matched
disadvantaged
(n = 162)
MACH
.02
.08
.02
-.04
-.17
MPS
.00
.00
.03
.02
-.05
PE
.09
.09
.10
.09
.06
NPI-Exp
.08
-.03
-.07
.02
-.03
NPI-Ent
.12
-.01
-.03
.01
-.01
SRP
-.01
.03
.08
.04
-.05
FD
-.04
.04
.00
.08
.01
IA
-.01
.04
.05
.06
-.01
Note: Coefficients in Bold are significant at p < .05. MACH = MACH-IV, MPS = Machiavellian
Personality Scale, NPI-Exp = Narcissistic Personality Inventory Exploitativeness Subscale, NPIENT = Narcissistic Personality Inventory Entitlement Subscale, PE = Psychological Entitlement
scale, SRP = Self-Report Psychopathy Scale, FD = Fearless Dominance, IA = Impulsive
Antisociality.

52

Table 5
Individual Differences and Proposals
Non-Competitive
Competitive
Dictator
Ultimatum
Dictator
Ultimatum
-.03
MACH
-.09
.07
-.13
MPS
-.14
.02
-.08
-.14
PE
-.15
.10
-.05
-.14
NPI-Exp
-.11
-.05
-.04
-.02
.02
NPI-Ent
-.04
-.04
-.14
SRP
.04
-.03
-.11
-.06
FD
.01
-.04
-.07
-.07
IA
.14
.02
-.07
.05
Note: Coefficients in Bold are significant at p < .05. MACH = MACH-IV, MPS = Machiavellian
Personality Scale, NPI-Exp = Narcissistic Personality Inventory Exploitativeness Subscale, NPIENT = Narcissistic Personality Inventory Entitlement Subscale, PE = Psychological Entitlement
scale, SRP = Self-Report Psychopathy Scale, FD = Fearless Dominance, IA = Impulsive
Antisociality.

53

Figure 1: The Effect of Game Type and Competition on Proposals
The Effect of Game Type and Competition on
Proposals
3.8
3.6
Proposal (Points)

3.4
3.2
3
2.8
2.6

Ultimatum
Dictator

2.4
2.2
2
Absent

Present
Competition

For interpretation of the references to color in this and all other figures, the reader is referred to
the electronic version of this dissertation.

54

Figure 2: The Effect of Manipulating Fairness of Competition on Ultimatum Acceptance Rates
The Effect of Manipulating Fairness of Competition on
Ultimatum Acceptance Rates
.40

Acceptance (%)

.38
.36
.34
.32
.30
Competitive Ultimatum
Non-Competitive
Ultimatum

.28
.26
.24
.22
.20
Advantaged

Matched

Disadvantaged

Fairness of Competition

55

Figure 3: Gender Difference in Acceptance Rates by Fairness of Competition
Gender Difference in Acceptance Rates by Fairness of
Competition
.45

Acceptance (%)

.40
.35
.30
.25

Men

.20

Women

.15
.10
Advantaged

Matched

Disadvantaged

Fairness of Competition

56

Figure 4: Proposals by Difficulty
Proposals by Difficulty
3.8
3.6

Points Proposed

3.4
3.2

Ultimatum

3.0

Dictator

2.8

Non-Competitive
Ultimatum Average

2.6

Non-Competitive
Dictator Average

2.4
2.2
2.0
Advantaged

Matched

Disadvantaged

57

Figure 5: Game Enjoyment as a Function of Competition and Game Type
Game Enjoyment as a Function of Competition and Game Type

Overall Game Enjoyment

3.5
3
2.5
2
1.5

Ultimatum
Dictator

1
.5
0
Absent

Present
Competition

58

APPENDICIES

59

APPENDIX A: HUMAN PARTICIPATION IN RESEARCH STUDY DESCRIPTION

HPR Study Title:
Multi-Site Economic Game Study
HPR Study Description:
“Students will play an online game against students at other universities for a chance to win
prizes.”

60

APPENDIX B: INSTRUCTIONS TO PARTICIPANTS
Non-Competitive Ultimatum Game:
After participants read and signed the consent forms they heard the following:
In today’s experiment we are interested in understanding how people choose to divide
resources in a competitive environment. There are two phases to this study. You have already
completed one phase by filling out questionnaires online when you signed up. The second phase
will take place today and should take about 45 minutes.
For this phase you will play an interactive game on-line against students from other
universities across the U.S. On each round of the game the computer will assign you a different
opponent from another school. At no time will you be competing with another MSU student
including those present here. Once assigned a partner the computer will then randomly decide
which one of you is the winner for that round.
On each round you are competing for ten points. The winning player gets to make a proposal
of points between themselves and the losing player. For example, let’s say that I won the first
round. Now I have to decide how I want to divide the points between myself and my opponent. I
could choose any division, so I might choose to make an offer of 7pts for me and 3pts for my
opponent or 8pts for me and 2pts for opponent and so on. I won, so I get to choose. The amount
proposed counts as the point total for that round. Does everyone understand?
The points won on each round will become important at the end of the game. When you
finish, the results from one of your rounds will be chosen at random and the point division for
that round will count as your number of entries to win one of five iPod shuffles. So, if on that
round you proposed 7 points for yourself and 3 points for your opponent, that would count as 7
entries into the drawing for you and your opponent would get 3 entries. Does anyone have any
questions? Is everyone clear on the gameplay and the rules?
Participants then completed the study on the computer, answered manipulation check and funnel
debriefing questions, and were debriefed.
Non-Competitive Dictator Game
The above script was identical for the Dictator Game with the exception that language related to
acceptance/rejection of offers was removed.

61

Competitive Ultimatum Game
After participants read and signed the consent forms they heard the following:
In today’s experiment we are interested in understanding how people choose to divide
resources in a competitive environment. There are two phases to this study. You have already
completed one phase by filling out questionnaires online when you signed up. The second phase
will take place today and should take about 45 minutes.
For this phase you will play an interactive game on-line against students from other
universities across the U.S. On each round of the game the computer will assign you a different
opponent from another school. At no time will you be competing with another MSU student
including those present here.
Each round you and your opponent will be asked to answer three multiple-choice math
problems. Whoever answers the most questions correctly will win the round. If you both of you
get the same number of correct answers whoever answered the fastest will win the round.
On each round you are competing for ten points. The winning player will propose a division
of these points to the loser. For example, let’s say that I won the first round. Now I have to
decide how I want to divide the points between myself and my opponent. I could choose any
division, so I might choose to make an offer of 7pts for me and 3pts for my opponent or 8pts for
me and 2pts for opponent and so on. I won, so I get to choose.
The losing player only has two options. They can choose to accept the offer of points from the
winner, in which case the winner and loser get the proposed point totals OR they can choose to
reject the offer, in which case neither player receives any points for that round. So let’s say that
on the second round I lost. The computer will show me the offer from my opponent. Let’s say
they offered me 2 pts. If I accept the offer, I will receive 2 pts and they will receive 8 pts. If I
reject the offer, we will both get zero pts for that round. Does everyone understand?
Finally, a quick word about the math questions. The questions you and your opponent need
to answer to win the round are drawn at random by the computer from pools of problems that
have been pre-determined to be either easy or hard. So on any given trial, you may both have
easy questions, both have hard questions, or one of you will have easy and the other will have
hard questions.
At the end of the round you will be presented with a “results” page. This page will tell you
your score, the difficulty of the questions you just answered, your opponent’s score, the difficulty
of the questions he or she had to answer and whether you won or lost the round .
The points won on each round will become important at the end of the game. When you finish
the results from one of your rounds will be chosen at random and the point division for that
round will count as your number of entries to win one of five iPod shuffles. So, if on that round
you received 7 points and your opponent received 3 points, that would count as 7 entries into the
drawing for you and your opponent would get 3 entries. If one of you rejected the offer, you both
62

would have 0 points and neither of you would receive an entry to win the prize. Does anyone
have any questions? Is everyone clear on the gameplay and the rules?
Before you play the game for real, I am going to have you run through a short tutorial on the
computer just so you can get a feel for the gameplay. Your wins and losses on this tutorial will
not be counted. If no one has any questions, I will come around and get each of you started on
the tutorial.
Competitive Dictator Game
The above script was identical for the Dictator Game with the exception that language related to
acceptance/rejection of offers was removed.

63

APPENDIX C: MEASURES OF DEMOGRAPHICS AND MALADAPTIVE PERSONALITY
TRAITS ADMINISTERED
Demographic information:
Gender
Year in School
Age
Ethnicity
Personality Measures:
Mach IV
Christie, R., & Geis, F.L. (1970). Studies in Machiavellianism. New York:
Academic Press.
Scoring Key:
Disagree Strongly (+3) 1
Disagree Somewhat (+2) 2
Disagree Slightly (+1) 3
Agree Slightly
(-1) 5
Agree Somewhat
(-2) 6
Agree Strongly
(-3) 7

Listed below are a number of statements. Each represents a commonly held opinion and
there are no right or wrong answers. You will probably disagree with some items and agree
with others. We are interested in the extent to which you agree or disagree with such matters
of opinion.
First impressions are usually best in such matters. Read each statement, decide if you
agree or disagree and the strength of your opinion, and then select the appropriate response.
Please give your opinion on every statement.
If you find that the responses do not adequately indicate your own opinion, use the one
which is closest to the way you feel.
1.
2.
3.
4.
5.

Never tell anyone the reason you did something unless it is useful to do so.
The best way to handle someone is to tell them what they want to hear.
One should take action only when sure it is morally right.*
Most people are basically good and kind.*
It is safest to assume that all people have a vicious streak and it will come out when they
are given a chance.
6. Honesty is the best policy in all cases.*
7. There is no excuse for lying to someone else.*
64

8. Generally speaking, men won’t work hard unless they’re forced to do so.
9. All in all, it is better to be humble and honest than to be important and dishonest.*
10. When you ask someone to do something for you, it is best to give the real reasons for
wanting it rather than giving reasons which carry more weight.*
11. Most people who get ahead in the world lead clean, moral lives. *
12. Anyone who completely trusts anyone else is asking for trouble.
13. The biggest difference between most criminals and other people is that the criminals are
stupid enough to get caught.
14. Most men are brave*
15. It is wise to flatter important people
16. It is possible to be good in all respects.*
17. Barnum was wrong when he said that there’s a sucker born every minute.*
18. It is hard to get ahead without cutting corners here and there.
19. People suffering from incurable diseases should have the choice of being put painlessly
to death.
20. Most men forget more easily the death of their father than the loss of their property.
Note: * = reversed item
Machiavellian Personality Scale: (Dahling, Whitaker, & Levy, 2009)
1. I am willing to be unethical if I believe it will help me succeed.
2. I am willing to sabotage the efforts of other people if they threaten my own goals.
3. I would cheat if there was a low chance of getting caught.
4. I believe that lying is necessary to maintain a competitive advantage over others.
5. The only good reason to talk to others is to get information that I can use to my benefit.
6. I like to give the orders in interpersonal situations.
7. I enjoy being able to control the situation.
8. I enjoy having control over other people.
9. Status is a good sign of success in life.
10. Accumulating wealth is an important goal for me.
11. I want to be rich and powerful someday.
12. People are only motivated by personal gain.
13. I dislike committing to groups because I don’t trust others.
14. Team members backstab each other all the time to get ahead.
15. If I show any weakness at work, other people will take advantage of it.
16. Other people are always planning ways to take advantage of the situation at my expense.

NPI-40
Read each pair of statements and then choose the one that is closer to your own feelings and
beliefs. Indicate your answer by circling the letter "A" or "B" to the left of each item. Please do
not skip any items.
1.

A I have a natural talent for influencing people.
B I am not good at influencing people.
65

2.

A Modesty doesn't become me.
B I am essentially a modest person.

3.

A I would do almost anything on a dare.
B I tend to be a fairly cautious person.

4.

A When people compliment me I sometimes get embarrassed.
B I know that I am good because everybody keeps telling me so.

5.

A The thought of ruling the world frightens the hell out of me.
B If I ruled the world it would be a much better place.

6.

A I can usually talk my way out of anything.
B I try to accept the consequences of my behavior.

7.

A I prefer to blend in with the crowd.
B I like to be the center of attention.

8.

A I will be a success.
B I am not too concerned about success.

9.

A I am no better or no worse than most people.
B I think I am a special person.

10.

A I am not sure if I would make a good leader.
B I see myself as a good leader.

11.

A I am assertive.
B I wish I were more assertive.

12.

A I like having authority over people.
B I don't mind following orders.

13.

A I find it easy to manipulate people.
B I don't like it when I find myself manipulating people.

14.

A I insist upon getting the respect that is due me.
B I usually get the respect that I deserve.

15.

A I don't particularly like to show off my body.
B I like to display my body.

16.

A I can read people like a book.
B People are sometimes hard to understand.

66

17.

A If I feel competent I am willing to take responsibility for making decisions.
B I like to take responsibility for making decisions.

18.

A I just want to be reasonably happy.
B I want to amount to something in the eyes of the world.

19.

A My body is nothing special.
B I like to look at my body.

20.

A I try not to be a show off.
B I am apt to show off if I get the chance.

21.

A I always know what I am doing.
B Sometimes I am not sure of what I am doing.

22.

A I sometimes depend on people to get things done.
B I rarely depend on anyone else to get things done.

23.

A Sometimes I tell good stories.
B Everybody likes to hear my stories.

24.

A I expect a great deal from other people.
B I like to do things for other people.

25.

A I will never be satisfied until I get all that I deserve.
B I take my satisfactions as they come.

26.

A Compliments embarrass me.
B I like to be complimented.

27.

A I have a strong will to power.
B Power for its own sake doesn't interest me.

28.

A I don't very much care about new fads and fashions.
B I like to start new fads and fashions.

29.

A I like to look at myself in the mirror.
B I am not particularly interested in looking at myself in the mirror.

30.

A I really like to be the center of attention.
B It makes me uncomfortable to be the center of attention.

31.

A I can live my life in any way I want to.
B People can't always live their lives in terms of what they want.

32.

A Being an authority doesn't mean that much to me.
67

B People always seem to recognize my authority.
33.

A I would prefer to be a leader.
B It makes little difference to me whether I am a leader or not.

34.

A I am going to be a great person.
B I hope I am going to be successful.

35.

A People sometimes believe what I tell them.
B I can make anybody believe anything I want them to.

36.

A I am a born leader.
B Leadership is a quality that takes a long time to develop.

37.

A I wish somebody would someday write my biography.
B I don't like people to pry into my life for any reason.

38.

A I get upset when people don't notice how I look when I go out in public.
B I don't mind blending into the crowd when I go out in public.

39.

A I am more capable than other people.
B There is a lot that I can learn from other people.

40.

A I am much like everybody else.
B I am an extraordinary person.

Subscales from Raskin
Authority = 33r, 10, 8r, 32, 1r, 11r, 12r, 36r
Self sufficiency = 22, 17, 39r, 31r, 21r, 34r
Superiority = 40, 4, 26, 9, 37r
Exhibitionism = 20, 2r, 38r, 7, 3r, 30r, 28
Exploitative = 16r, 35, 13r, 6r, 23
Vanity = 19, 15, 29r
Entitlement = 25r, 24r, 18, 27r, 14r, 5
Psychological Entitlement Scale (Campbell et al., 2004)
1.
I honestly feel I'm just more deserving than others.
2.
Great things should come to me.
3.
If I were on the Titanic, I would deserve to be on the first lifeboat!
4.
I demand the best because I'm worth it.
5.
I do not necessarily deserve special treatment.
6.
I deserve more things in my life.
7.
People like me deserve an extra break now and then.
8.
Things should go my way.
9.
I feel entitled to more of everything.
68

SRP III – R12 (Paulhus, D.L., Hemphill, J.D., & Hare, R.D. (in press). Manual for
the Self-Report Psychopathy scale. Toronto: Multi-Health Systems. )
Please rate the degree to which you agree with the following statements about you. You can
be honest because your name will be detached from the answers as soon as they are submitted.
1
Disagree
Strongly

2
Disagree

3
Neutral

1. I’m a rebellious person.
2. I’m more tough-minded than other people.
3. I think I could "beat" a lie detector.
4. I have taken illegal drugs (e.g., marijuana, ectasy).
5. I have never been involved in delinquent gang activity.
6. I have never stolen a truck, car or motorcycle.
7. Most people are wimps.
8. I purposely flatter people to get them on my side.
9. I’ve often done something dangerous just for the thrill of it.
10. I have tricked someone into giving me money.
11. It tortures me to see an injured animal.
12. I have assaulted a law enforcement official or social worker.
13. I have pretended to be someone else in order to get something.
14. I always plan out my weekly activities.
15. I like to see fist-fights.
16. I’m not tricky or sly.
17. I’d be good at a dangerous job because I make fast decisions.
18. I have never tried to force someone to have sex.
19. My friends would say that I am a warm person.
20. I would get a kick out of ‘scamming’ someone.
21. I have never attacked someone with the idea of injuring them.
22. I never miss appointments.

69

4
Agree

5
Agree
Strongly

23. I avoid horror movies.
24. I trust other people to be honest.
25. I hate high speed driving.
26. I feel so sorry when I see a homeless person.
27. It's fun to see how far you can push people before they get upset.
28. I enjoy doing wild things.
29. I have broken into a building or vehicle in order to steal something or vandalize.
30. I don’t bother to keep in touch with my family any more.
31. I find it difficult to manipulate people.
32. I rarely follow the rules.
33. I never cry at movies.
34. I have never been arrested.
35. You should take advantage of other people before they do it to you.
36. I don’t enjoy gambling for real money.
37. People sometimes say that I’m cold-hearted.
38. People can usually tell if I am lying.
39. I like to have sex with people I barely know.
40. I love violent sports and movies.
41. Sometimes you have to pretend you like people to get something out of them.
42. I am an impulsive person.
43. I have taken hard drugs (e.g., heroin, cocaine).
44. I'm a soft-hearted person.
45. I can talk people into anything.
46. I never shoplifted from a store.
47. I don’t enjoy taking risks.
48. People are too sensitive when I tell them the truth about themselves.
49. I was convicted of a serious crime.
50. Most people tell lies everyday.
51. I keep getting in trouble for the same things over and over.
52. Every now and then I carry a weapon (knife or gun) for protection.
53. People cry way too much at funerals.
70

54. You can get what you want by telling people what they want to hear.
55. I easily get bored.
56. I never feel guilty over hurting others.
57. I have threatened people into giving me money, clothes, or makeup.
58. A lot of people are “suckers” and can easily be fooled.
59. I admit that I often “mouth off” without thinking.
60. I sometimes dump friends that I don’t need any more.
61. I would never step on others to get what I want.
62. I have close friends who served time in prison.
63. I purposely tried to hit someone with the vehicle I was driving.
64. I have violated my probation from prison.

International Personality Item Pool Items (IPIP; Goldberg, 1999; FD and IA scales by Witt et al.,
2009)
Fearless Dominance
I worry about things.*
1
7
I love large parties.
12
I take charge.
I find it difficult to approach others.*
16
22
I love excitement.
32
I feel comfortable around people.
37
I talk to a lot of different people at parties.
I try to lead others.
42
46
I am afraid to draw attention to myself.*
52
I seek adventure.
54
I think highly of myself.
I have a lot of fun.
57
72
I take control of things.
76
I only feel comfortable with friends*
91
I get stressed out easily.*
I avoid crowds.*
97
102
I wait for others to lead the way.*
106
I am not bothered by difficult social situations.
116
I remain calm under pressure.
I look at the bright side of life.
117
Impulsive Antisociality
71

9
19
30
39
60
69
75
79
80
82
85
89
90
99
104
105
109
110
114
120

I use others for my own ends.
I love a good fight.
I jump into things without thinking.
I cheat to get ahead.
I make rash decisions.
I take advantage of others.
I break rules.
I insult people.
I do just enough work to get by.
I enjoy being reckless.
I waste my time.
I am not interested in other people's problems.
I rush into things.
I obstruct others' plans.
I take no time for others.
I break my promises.
I get back at others.
I put little time and effort into my work.
I boast about my virtues.
I act without thinking.

Items followed by an asterisk are reverse-keyed

72

REFERENCES

73

REFERENCES

Ackerman, R. A., Witt, E. A., Donnellan, M. B., Trznesniewski, K. H., Robins, R. W., & Kashy,
D. A. (2011). What does the narcissistic personality inventory really measure?
Assessment, 18, 67-87.
Allport, G. W. (1931). What is a trait of personality? Journal of Abnormal and Social
Psychology, 25, 368-372.
Ashton, M. C., & Lee, K. (2008). The HEXACO model of personality structure and the
importance of the H factor. Social and Personality Psychology Compass, 2, 1952-1962.
Bolton, G. E., & Rami, Z. (1995). Anonymity versus punishment in Ultimatum bargaining.
Games and Economic Behavior, 10(1), 95-121.
Cain, N.M., Pincus, A.L., & Ansell, E.B. (2008). Narcissism at the crossroads: Phenotypic
description of pathological Narcissism across clinical theory, social/personality
psychology, and psychiatric diagnosis. Clinical Psychology Review, 28, 638-656.
Camerer, C. F. (2003). Behavioral game theory: Experiments in strategic interaction.
Campbell, W. K., Bonacci, A. M., Shelton, J., Exline, J. J., & Bushman, B. J. (2004)
Psychological entitlement: Interpersonal consequences and validation of a self-report
measure. Journal of Personality Assessment, 83, 29-45
Carnahan, T., & McFarland, S. (2007). Revisiting the Stanford prison experiment: Could
participant self-selection have led to cruelty? Personality and Social Psychology Bulletin,
33(5), 603-614.
Christie, R., & Geis, F.L. (1970).Studies in Machiavellianism. New York: Academic Press.
Cosmides, L. & Tooby, J. (1992). Cognitive adaptations for social exchange. In J. Barkow, L.
Cosmides, & J. Tooby (Eds.), The adapted mind: Evolutionary psychology and the
generation of culture. New York: Oxford University Press.
Dahling, J. J., Whitaker, B. G., Levy, P. E. (2009). The development and validation of a new
Machiavellianism scale. Journal of Management, 35(2), 219-257.
de Waal, F. (1989).Food sharing and reciprocal obligations among chimpanzees. Journal of
Human Evolution, 18, 433–459.
Deutsch, M. (1985). Distributive Justice: A Social Psychological Perspective. New Haven: Yale
University Press.
Deutsch, M. (2006). Justice and Conflict. In Deutsch, M., Coleman, P. T., and Marcus, E. C.
74

(Eds.), The Handbook of Conflict Resolution: Theory and Practice (2nd Ed, pp. 41-64).
Jossey-Bass.
Eckel, C. C., & Grossman, P. J. (2001). Chivalry and solidarity in ultimatum games. Economic
Inquiry, 39, 171-188.
Forsythe, R., Horowitz, J. L., Savin, N. E., & Sefton, M. (1994). Fairness in simple bargaining
experiments. Games and Economic Behavior, 6(3), 347-369.
Gunnthorsdottir, A., McCabe, K., & Smith, V. (2002). Using the Machiavellianism instrument to
predict trustworthiness in a bargaining game. Journal of Economic Psychology, 23, 4966.
Guth, W., Schmittberger, R., &Schwarze, B. (1982). An experimental analysis of Ultimatum
bargaining. Journal of Economic Behavior and Organization, 3, 367-388.
Hack, A., & Lammers, F. (2009). Gender as a moderator of the fair process effect. Social
Psychology, 40(4), 202-211.
Henrich, J., Heine, S. J., & Norenzayan, A. (2010). The weirdest people in the world?
Behavioral and Brain Sciences, 33, 61-83.
Hilbig, B. E., & Zettler, I. (2009). Pillars of cooperation: Honesty-Humility, social value
orientations, and economic behavior. Journal of Research in Personality, 43, 516-519.
Hoffman, E., McCabe, K. A., & Smith, V. L. (1996). On expectations and the monetary stakes in
Ultimatum games. International Journal of Game Theory, 25, 289-301.
Hunter, J. E., Gerbing, D. W., & Boster, F. J. (1982). Machiavellian beliefs and personality:
Construct invalidity of the Machiavellianism dimension. Journal of Personality and
Social Psychology, 43(6), 1293-1305.
Jones, D. N., & Paulhus, D. L. (2009). Machiavellianism. In: M. R. Leary & R. H. Hoyle (Eds.),
Handbook of individual differences in social behavior (pp. 109–128). New York, NY:
The Guilford Press.
Kahneman, D., Knetsch, J. L., & Thaler, R. H. (1986). Fairness and the assumptions of
economics. The Journal of Business, 59, S285-S300.
Koenigs, M. Kruepke, M., & Newman, J. P. (2010). Economic decision-making in psychopathy:
A comparison with ventromedial prefrontal lesion patients. Neuropsychologica, 48, 21982204.
Lieberman, J. D., Solomon, S., Greenberg, J., & McGregor, H. A. (1999). A hot new way to
measure aggression: Hot sauce allocation. Aggressive Behavior, 25, 331–348.

75

Lilienfeld, S. O., & Andrews, B. P. (1996). Development and preliminary validation of a selfreport measure of psychopathic personality traits in non-criminal populations. Journal of
Personality Assessment, 66, 488-524.
List, J. A., & Cherry, T. L. (2000). Learning to accept in Ultimatum games: Evidence from an
experimental design that generates low offers. Experimental Economics, 3(1), 11-29.
Machiavelli, N. (1966). The Prince. New York, NY: Bantam Books. (Original work published
1513).
McHoskey, J. W., Worzel, W., & Szyarto, C. (1998). Machiavellianism and psychopathy.
Journal of Personality and Social Psychology, 74(1), 192-210.
Meyer, H. (1992). Norms and self-interest in Ultimatum bargaining: The prince’s prudence.
Journal of Economic Psychology, 13, 215-232.
Milgram, S. (1963). Behavioral study of obedience. Journal of Abnormal and Social Psychology,
67(4), 371-378.
Osumi, T., & Ohira, H. (in press). The positive side of psychopathy: Emotional detachment in
psychopathy and rational decision-making in the Ultimatum game. Personality and
Individual Differences.
Patrick, C. J., & Bernat, E. M. (2009). Neurobiology of psychopathy: A two-process theory. In:
G. G. Berntson & J. T. Cacioppo (Eds.), Handbook of neuroscience for the behavioral
sciences (pp. 1110–1131). New York, NY: Wiley.
Paulhus, D. L., Hemphill, J. D., & Hare, R. D. (2007). Manual for the Self-Report Psychopathy
scale. Unpublished Manuscript, University of British Columbia, Vancouver, British
Columbia, Canada.
Paulhus, D. L., Williams, K. M. (2002). The dark triad of personality: Narcissism,
Machiavellianism and psychopathy. Journal of Research in Personality, 36, 556–563.
Raskin, R., & Hall, C. S. (1979). A narcissistic personality inventory. Psychological Reports, 45,
590.
Raskin, R., & Terry, H. (1988).A principal-components analysis of the Narcissistic Personality
Inventory and further evidence of its construct validity. Journal of Personality and Social
Psychology, 54, 890-902.
Roth, A. E. (1995). Bargaining experiments. In Kagel, J. H., Roth, A. E. (Eds.) The Handbook of
Experimental Economics (pp. 253-348). Princeton, NJ: Princeton University Press.
Sakalaki, M., Kanellaki, S., & Richardson, C. (2009). Is a manipulator’s externality paradoxical?
The relationship between Machiavellianism, economic opportunism, and economic locus
76

of control. Journal of Applied Social Psychology, 39(11), 2591-2603.
Sakalaki, M., Richardson, C., & Thepaut, Y. (2007). Machiavellianism and economic
opportunism. Journal of Applied Social Psychology, 37(6), 1181-1190.
Sears, D. O. (1986). College sophomores in the laboratory: Influences of a narrow data base on
psychology’s view of human nature. Journal of Personality and Social Psychology, 51,
515-530
Thaler, R. H. (1988). Anomalies: The Ultimatum game. Journal of Economic Perspectives, 2(4),
195-206.
Wallace, B., Cesarini, D., Lichtenstein, P., & Johannesson, M. (2003). Heritability of Ultimatum
game responder behavior. Proceedings of the National Academy of Sciences, 140(40),
15631-15634.
Witt, E. A., & Donnellan, M. B. (2008). Furthering the case for the MPQ-based measures of
psychopathy. Personality and Individual Differences, 45, 219–225.
Witt, E. A., Donnellan, M. B., & Blonigen, D. M. (2009). Using existing self-report inventories
to measure the psychopathic personality traits of fearless dominance and impulsive
antisociality. Journal of Research in Personality, 43, 1006–1016.
Witt, E. A., Donnellan, M. B., Blonigen, D. M., Krueger, R. F., & Conger, R. D. (2009).
Assessment of fearless dominance and impulsive antisociality via normal personality
measures: Convergent validity, criterion validity, and developmental change. Journal of
Personality Assessment, 91, 265–276.

77