Judgment and Decision Making, Vol. 14, No. 5, September 2019, pp. 535–546
An exploration of the motivational basis of take-some and give-some
games
Tessa Haesevoets∗
Alain Van Hiel†
Jasper Van Assche†
Dries H. Bostyn†
Chris Reinders Folmer‡
Abstract
Surprisingly little research has investigated the particular motives that underlie choice behavior in social dilemma situations.
The main aim of the present research was to ask whether behavior in take-some games (such as the multiple-person Commons
Dilemma Game and the two-person Bandit Game) and give-some games (such as the multiple-person Public Goods Dilemma
Game and the two-person Dictator Game) is differently affected by proself and prosocial motives. Two experimental studies
were conducted. Our first experiment used a trait-based assessment of the motives, whereas in our second experiment the
motives were measured as state variables. The results of both experiments revealed that proself and prosocial motives did
not explain much difference between taking and giving when comparing the Commons Dilemma Game and the Public Goods
Dilemma Game. Yet, our second experiment revealed that these motives did differentiate choices in the Bandit Game and the
Dictator Game. More specifically, prosocial motives are more strongly related to giving behavior in the Dictator Game than
to taking behavior in the Bandit Game. As such, it can be concluded that in dyadic games (but not in multiple-person games)
prosocial motives (but not proself motives) predict choice behavior in a game-specific way.
Keywords: take-some games, give-some games, choice framing, trait and state motivations, interdependence
1
Introduction
Social dilemmas are mixed-motive situations that confront
people with a conflict between individual and collective interests: For each individual it is more profitable to act selfishly, but such behavior harms the collective (Dawes, 1980;
Messick & Brewer, 1983). Weber, Kopelman and Messick
(2004) aptly noted that “social dilemmas are everywhere”
(p. 281). Indeed, it is difficult to imagine an aspect of social life that is not characterized by conflicting interests in
terms of self-versus-other concerns. Typical examples of
mixed-motive situations include the conservation of natural
resources and volunteering behaviors. In order to be able
to investigate social dilemmas empirically, researchers have
modeled mixed-motive situations into a range of different
mixed-motive games. In these games, people must choose
between cooperation and defection, thereby benefiting either
their own interests or those of the collective (for overviews,
see Kollock, 1998; Komorita & Parks, 1995; Van Lange,
This research was supported by the Special Research Fund (BOF) of
Ghent University (Grant number: BOF.PDO.2017.0017.01).
Copyright: © 2019. The authors license this article under the terms of
the Creative Commons Attribution 3.0 License.
∗ Department of Developmental, Personality and Social Psychology,
Ghent University, Henri Dunantlaan 2, B-9000, Ghent, Belgium. E-mail:
Tessa.Haesevoets@UGent.be.
† Ghent University.
‡ Erasmus University Rotterdam.
Joireman, Parks & Van Dijk, 2013).
The two main experimental paradigms used to investigate
choice behavior in mixed-motive situations are the Commons Dilemma Game and the Public Goods Dilemma Game
(Rutte, Wilke & Messick, 1987; Van Dijk & Wilke, 1995,
2000). These two games are usually employed as models
for the study of take-some and give-some dilemmas, respectively. In the Commons Dilemma Game, multiple players
share a limited common resource pool from which everyone
may take as many endowments as he or she wants. The
potential danger is overuse, because the common good is
in limited supply. It is thus in each player’s best interest
to take as much as possible, but if the players collectively
harvest too much, the common resource will be depleted
and eventually get lost. Typical real-life examples of the
Commons Dilemma Game concern the conservation of natural resources like water and clean air. The Public Goods
Dilemma Game concerns a situation in which multiple players must choose between giving resources towards a public
good from which all may benefit, or withholding them for
private use. Players earn the most when they give nothing
and profit from the donations of others (i.e., free riding).
However, if players collectively give too little, the public
good will cease to exist. Collective services provided by the
government through taxation — such as public television,
public roads, and national defense — can be seen as typical
real-life examples of the Public Goods Dilemma Game.
A number of prior studies has examined the differences
535
https://doi.org/10.1017/S1930297500004836 Published online by Cambridge University Press
Judgment and Decision Making, Vol. 14, No. 5, September 2019
between Commons Dilemma Games and Public Goods
Dilemma Games (e.g., Au & Budescu, 1999; De Dreu &
McCusker, 1997; McCarter, Budescu & Scheffran, 2011;
Poppe & Zwikker, 1996; Rutte et al., 1987; Van Dijk &
Wilke, 1995, 2000). Most of this previous work has focused
on when, and how, choice behavior alters if a game with
the same payoff structure is framed as either a take-some
or a give-some game. Yet, surprisingly little research has
investigated how taking or giving impacts the motivational
structure that underlies these games. Do both games capture
the same motivational conflict? Or does the nature of their
decisions alter how influential selfish and prosocial motives
are? To illuminate these questions, the present research examines the motivational differences between take-some and
give-some games.
1.1
Differential Motives Underlying Choice
Behavior in Take-Some and Give-Some
Games
Some prior studies have started to investigate the uniqueness and comparability of different mixed-motive games by
exploring behavioral consistency levels across and within
games. Because all mixed-motive games refer to a similar
conflict in terms of selfish and other-related concerns (Messick & Brewer, 1983; Weber et al., 2004), a certain degree of
behavioral consistency across different mixed-motive games
can be expected. However, previous research has found
rather weak associations between behaviors across games
(e.g., Haesevoets, Reinders Folmer & Van Hiel, 2015), and
these associations were clearly weaker than the relationships
which typically emerge between behaviors in repeated versions of the same game (e.g., Haesevoets, Reinders Folmer,
Bostyn & Van Hiel, 2018). These findings thus suggest
that, although the self-other conflict is at the core of each
mixed-motive game, there may also be considerable differences among mixed-motive games; and these differences
may possibly even overshadow the games’ common ground
(see Pruitt & Kimmel, 1977; Van Lange et al., 2013).
Why might people make more consistent decisions in different versions of the same mixed-motive game than across
different games? In response to this question, we suggest
that games that involve taking and games that involve giving
might be differently affected by proself and prosocial motives, thus undermining behavioral consistency across these
two types of games. More specifically, we argue that, although each mixed-motive game brings the conflict between
selfish interests and concern for others to the fore, the relative weight of these two conflicting motivational dimensions (proself and prosocial) might actually differ across
different games. That is, in some games, behavior might be
more strongly driven by the proself dimension; whereas in
other games, behavior might be more strongly driven by the
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Motivational basis of take-some and give-some games
536
prosocial dimension. This reasoning is in line with the slotmachine model of interpersonal orientation of Van Lange,
De Cremer, Van Vugt and Van Dijk (2007), which assumes
that situational differences can alter the weight that people
assign to their own interests and the interests of others.
Which motivational dimension (proself or prosocial)
might be activated most strongly by games that involve taking
behavior and by games that involve giving behavior? Takesome games concern decisions to harvest resources from a
collectively owned resource pool. In this vein, Fleishman
(1988, p. 176) has argued that “people might view the act
of taking as ethically improper or exploitative.” As such, the
defective behavior of taking many resources can be interpreted as a typical manifestation of a selfish act. Because
of this, we expect that behavior in take-some games will
be most strongly affected by proself motives. Give-some
games, on the other hand, concern decisions to contribute
personally owned resources to a public good. And, it has
been argued that “people may view the act of giving as
inherently positive, as an altruistic, morally desirable act”
(Fleishman, 1988, p. 176). In a giving context, cooperative
behavior (i.e., giving many resources) can be seen as a typical prosocial act. Therefore, we expect that in give-some
games behavior will be most strongly affected by prosocial
motives. Taken together, we thus expect that taking will be
more strongly driven by proself motives, whereas giving will
be more strongly driven by prosocial motives (also see Rutte
et al., 1987; Van Dijk & Wilke, 1995, 2000).
1.2
The Present Studies
To explore these predictions, we examined the association
between proself and prosocial motives and decisions in the
Commons Dilemma Game and the Public Goods Dilemma
Game (Experiment 1), as well as in other games that involve
taking or giving (Experiment 2).
In Experiment 1, motives underlying choice behavior were
measured as trait variables. Doing so removes the need to
solicit them repeatedly, and, moreover, is in line with prior
research that suggests that individuals’ orientation on these
motivations represent enduring personality characteristics
(Kuhlman & Marshello, 1975; Liebrand, 1984; Messick &
McClintock, 1968). In Experiment 2 we shifted towards a
state-based approach, in which the motives were assessed in
relationship with the task itself. That is, after each game,
we asked participants to answer some questions about their
decision. These questions assessed the extent in which each
motive played a role in participants’ decision.
In both experiments, we solicited a wide range of motives
that have been linked to choice behavior in mixed-motive
games in recent theorizing (i.e., the conceptual motivational
model of Thielmann, Böhm & Hilbig, 2015) or research (i.e.,
the empirical study on within-game behavioral consistency
of Haesevoets et al., 2018). Critically, instead of pitting
Judgment and Decision Making, Vol. 14, No. 5, September 2019
these motivations against each other in hypothetical decisions (which has previously been done in measures of Social
Value Orientation; e.g., Murphy, Ackermann & Handgraaf,
2011; Van Lange, 1999), we measured each motive with a
separate questionnaire. As prosocial motives, we included
fairness (which is characterized by the desire to reach equality in outcomes), altruism (which reflects the motivation to
maximize the benefit of others, regardless of the outcome
for oneself), concern for others (which refers to the extent
individuals are concerned with the interests of others), and
social welfare concerns (which comprises the preference for
maximizing the welfare of the collective). As proself motives, we included greed (which mirrors the motivation to
maximize one’s own outcome), competitiveness (which reflects the desire to maximize one’s relative advantage over
the outcome of others), and entitlement (which reflects the
belief that one deserves preferential treatment). In addition
to these prosocial and proself motives, in our first experiment we also included two fear-related motives, namely,
fear (which consists of uncertainty about other people’s intentions) and risk aversion (which reflects a preference for a
guaranteed outcome over a probabilistic one).
2 Experiment 1
2.1
Method
2.1.1
Sample and Procedure
A sample of 225 undergraduate students of a Belgian University participated in this study in exchange for partial fulfillment of course credit for a Social Psychology course (i.e.,
students could earn a total of 20 points for this course; participation in the experiment counted for 1 point). Participants
were invited to the laboratory in groups of 35 to 45 persons.
Participants were seated in a large room, each on a separate desk in front of a computer. During the experimental
session, participants played 16 games. First, they played
eight variants of the Commons Dilemma Game, followed by
eight variants of the Public Goods Dilemma Game.1 We
used such game repetitions to obtain a more stable behavioral index for each game type. Participants were told that
they would interact with each interaction partner only once.
In reality, however, participants were not directly connected
to each other during the study, but were randomly paired
1We also included eight Prisoner’s Dilemma Games in our first experiment. The data of these games are not included in the present manuscript
for two reasons. First, to create eight different versions of the Prisoner’s
Dilemma Game, we could not manipulate the same variables as those manipulated to create the different versions of the Commons Dilemma Game
and Public Goods Dilemma Game. Secondly, the decision that participants
had to make in the Prisoner’s Dilemma Game did not consist of either taking behavior or giving behavior. We plan to use the data of the Prisoner’s
Dilemma Games in another manuscript that deals with real-life prosocial
behavior.
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Motivational basis of take-some and give-some games
537
at the end of the experimental session, and paid according
to the outcome that resulted from each player’s decision in
one randomly selected game variant.2 To avoid that participants’ decisions would be influenced by the choices of the
other players, no feedback on the other players’ decisions
was provided during the experiment. In the week after the
experimental session, participants were asked to complete
an online survey, in which the motivational traits were measured.3 Participants were required to complete both the experimental session and the online survey in order to receive
their course credit. Forty-four participants were excluded
from the analyses because they failed to answer our check
questions correctly, and an additional three participants because they did not complete the online survey.4 As such,
our final sample consisted of 178 participants (19.7% men,
M age = 18.55, SD = 1.97).
2.1.2
Mixed-Motive Games
Commons Dilemma Game. Participants were first presented with the Commons Dilemma Game (Hardin, 1968).
In this game, four players had to simultaneously decide how
many resources they wanted to take from a group resource.
In order to create eight different variants of this take-some
game, the endowment size of the group resource (low vs.
high) and the magnitude of the multiplier (low vs. medium
vs. high vs. very high) were orthogonally manipulated (see
Table 1). In the high endowment condition, the resource
pool from which participants could harvest consisted of double the resources as in the low endowment condition. In the
low multiplier condition, participants were told that the endowments that were not taken by the players would to be
multiplied by factor 1.5. The multiplication factor was 2 in
the medium multiplier condition, 2.5 in the high multiplier
condition, and 3 in the very high multiplier condition. The
participants were informed that the resulting resources (after multiplication) would we divided equally among the four
players, regardless of how many chips they took.
Public Goods Dilemma Game. Next, participants were
presented with the Public Goods Dilemma Game (Allison &
Kerr, 1994; Olson, 1965), in which four players had to simultaneously decide how many of their individually owned
2When the experiment was finished, participants were asked whether
they wanted to keep their earnings or donate their earnings to a noble cause.
Of all participants, 94% indicated that they wanted to donate their money
to a charity.
3This online survey also measured Social Value Orientation, RightWing Authoritarianism, Social Dominance Orientation, and dispositional
trust, but these data are not used in the present paper. We plan to use these
personality data in another manuscript.
4In each part of the study, participants had to answer some check questions. Participants who were unable to answer — in each part of the study
— at least n − 1 (i.e., the number of checks minus one) check questions
correctly were excluded from further analyses. More information on these
check questions is provided on our OSF webpage (https://osf.io/jrqxb).
Judgment and Decision Making, Vol. 14, No. 5, September 2019
538
Motivational basis of take-some and give-some games
Table 1: Overview of the game variants and descriptive statistics of the game behaviors (Experiment 1).
Endowment Multiplication
size
factor
Game variant 1: low endowment
x low multiplication factor
Game variant 2: low endowment
x medium multiplication factor
Game variant 3: low endowment
x high multiplication factor
Game variant 4: low endowment
x very high multiplication factor
Game variant 5: high endowment
x low multiplication factor
Game variant 6: high endowment
x medium multiplication factor
Game variant 7: high endowment
x high multiplication factor
Game variant 8: high endowment
x very high multiplication factor
Total (sum of the eight game
variants)
Commons Dilemma
(taking-behavior)
Public Goods Dilemma
(giving-behavior)
M
SD
M
SD
20
1.5
8.31
7.02
8.22
6.63
20
2
6.39
6.39
9.92
6.17
20
2.5
5.38
5.35
11.46
5.97
20
3
5.30
5.51
12.98
6.11
40
1.5
14.93
13.78
15.72
12.96
40
2
11.84
11.55
20.30
11.89
40
2.5
12.30
12.13
22.24
11.79
40
3
11.84
12.66
24.03
12.52
240
-
76.30
61.68
124.87
65.76
Note. N = 178. The endowment size manipulation reflects how many resources the participants could maximally take (in the
Commons Dilemma Game) or give (in the Public Goods Dilemma Game). The multiplication factor manipulation reflects
with which number the remaining resources (in the Commons Dilemma Game) or the given resources (in the Public Goods
Dilemma Game) were multiplied.
resources they wanted to give to the group resource. Here
too, eight game variants were created by orthogonally manipulating the endowment size and the magnitude of the
multiplier (see Table 1). In the high endowment condition,
participants’ individual resources at the start of the game
were double to that in the low endowment condition. Endowments that were given to the collective good were said
to be multiplied by a multiplication factor of 1.5 (low multiplier), 2 (medium multiplier), 2.5 (high multiplier), or 3
(very high multiplier). The resulting resources (after multiplication) were said to be divided equally among the four
players (regardless of how many chips they gave).
2.1.3
Motivational Traits
The online survey measured individual differences in the
following motivational traits: Fairness, altruism, social welfare concerns, concern for others, greed, competitiveness,
entitlement, fear, and risk aversion. It was administered one
week after the experimental session took place. Table 2
presents an overview of the scales that were employed to
measure these trait motivations; the full item list is included
in Appendix A.
https://doi.org/10.1017/S1930297500004836 Published online by Cambridge University Press
2.2
Results
2.2.1
Game Data
The means and standard deviations of the game behaviors can
be found in Table 1. Across the eight Commons Dilemma
Games, participants took on average 76 resources from the
group resource (and thus left 164 in the common pool).
Across the eight Public Goods Dilemma Games, participants gave on average 125 resources to the group resource
(and thus kept 115 for themselves). These findings indicate
that participants acted more cooperatively in the Commons
Dilemma Game than in the Public Goods Dilemma Game
(i.e., they left more resources in the Commons Dilemma
Games than that they gave in the Public Goods Dilemma
Games).
Manipulation of game features. We subsequently asked
whether our manipulations of the game features affected
choice behavior. To do so, we conducted a 2 (game type:
commons vs. public good) × 2 (endowment size: low vs.
high) × 4 (multiplier: low vs. medium vs. high vs. very high)
repeated measures analysis of variance (ANOVA), with all
Judgment and Decision Making, Vol. 14, No. 5, September 2019
539
Motivational basis of take-some and give-some games
Table 2: Overview of the motivational trait scales (Experiment 1).
Motive
Scale (developed by / based on)
# of items
Fairness
Fairness Attribution Scale (Van Hiel, Vanneste & De Cremer, 2008)
Altruism
MaxOther Scale (Tazelaar, Van Lange & Ouwerkerk, 2004)
Social Welfare Concerns Social Welfare Concerns Scale (Haesevoets, Reinders Folmer, Bostyn
& Van Hiel, 2018)
Concern for Others
Concern for Others Scale (Selenta & Lord, 2005)
Greed
Dispositional Greed Scale (Krekels & Pandelaere, 2015)
Competitiveness
Competitive Scale (Xie, Yu, Chen & Chen, 2006)
Entitlement
Psychological Entitlement Scale (Campbell, Bonacci, Shelton, Exline
& Bushman, 2004)
Fear
Fear Attribution Scale (Van Hiel, Vanneste & De Cremer, 2008)
Risk Aversion
General Risk Aversion Scale (Mandrik & Bao, 2005)
M
SD
α
5
3
4
6.05 0.77 .87
4.27 1.12 .90
5.51 1.02 .92
5
6
10
9
5.98
3.17
3.58
2.23
9
6
3.69 1.32 .93
4.22 0.92 .74
0.67
1.15
1.04
0.88
.79
.88
.86
.85
Note. N = 178. The motivational traits were all measured using seven-point Likert scales ranging from (1) strongly disagree
to (7) strongly agree. The attribution scales were slightly adapted in order to measure individual differences in the relevant
motivational trait.
factors being within-participant. The results of this analysis showed that the three main effects, the three two-way
interactions, and the three-way interaction were all highly
significant (all Fs ≥ 4.98, ps < .003). These findings imply that the game type, the size of the endowments, and
the magnitude of the multiplication factor all have a significant influence on participants’ choices — which indicates
that our manipulations were indeed successful for inducing
variations in choice behavior.
Factor structure of the games. We conducted a factor
analysis (Principal Axis Factoring) to investigate if the two
games load on different underlying factors. Two factors were
extracted from the inter-correlations among the scores on
the 16 game behaviors: The eight Public Goods Dilemma
Games loaded on a first factor (initial eigenvalue = 8.98;
after rotation = 7.57), whereas the eight Commons Dilemma
Games constituted a second factor (initial eigenvalue = 2.73;
after rotation = 6.99). Most importantly, the primary factor
loadings were all larger than .72, while the cross-loadings
were all smaller than |.09|; indicating a clean factor structure.
The results of this factor analysis hence indicate that
choice behavior is particularly contingent on the type of
decision that has to be made (take or give). Accordingly, we
created an index score for choice behavior in either game, by
aggregating participants’ (standardized) scores in the eight
game variants. We reversed the scores of the Commons
Dilemma Game index, so that the two game indices both
pointed in the same direction. We used these created index
scores as our measure of choice behavior in our subsequent
analyses.5
5For both games, the extracted factor score and the created index score
https://doi.org/10.1017/S1930297500004836 Published online by Cambridge University Press
2.2.2
Motivational Data
Reduction of the motivations. Table 3 shows the correlation matrix of the motivational traits. To reduce these
motivations to a limited number of indicators of the underlying motivational conflict, we conducted a factor analysis
(again using the Principal Axis Factoring method) to extract
underlying factors form the inter-correlations among the motivational items. Three motivational factors were extracted;
Appendix B shows their factor loadings after Oblimin rotation. The first extracted factor (initial eigenvalue = 9.86;
after rotation = 7.40) consisted of four of the six greed items,
the ten competiveness items, and the nine entitlement items;
hence, we labeled this the proself motivational factor. The
second factor (initial eigenvalue = 8.03; after rotation = 7.40)
consisted of the nine fear items and five of the six risk aversion items; thus, we labelled it the fearful motivational factor. Finally, the third factor (initial eigenvalue = 4.48; after
rotation = 7.42) included the five fairness items, the three
altruism items, the four social welfare concerns items, and
the five concern for others items; accordingly, it was labeled
the prosocial motivational factor. Note that two greed items
(items 5 and 6) and one risk aversion item (item 5) had their
primarily loadings on the wrong factor and were therefore
discarded from this analysis.
2.2.3
Motivational Differences between the Games
We next explored our prediction that behavior in the Commons Dilemma Game and the Public Goods Dilemma Game
were almost perfectly correlated (Commons Dilemma Game: r = .996 and
Public Goods Dilemma Game: r = .996; both ps < .001). Moreover, the
correlation between the two created index scores was also rather high (r =
.53, p < .001).
Judgment and Decision Making, Vol. 14, No. 5, September 2019
Motivational basis of take-some and give-some games
540
Table 3: Correlation matrix of the motives (Experiment 1).
CDG PGDG
Motivation trait scales
1. Fairness
.09
2. Altruism
.04
3. Social Welfare Concerns
.15
4. Concern for Others
.14
5. Greed
−.16
6. Competitiveness
−.20
7. Entitlement
−.26
8. Fear
.00
9. Risk Aversion
−.02
Extracted motivational factors
10. Proself Factor (factor 1) −.27
11. Fearful Factor (factor 2) −.00
12. Prosocial Factor (factor 3) .16
1.
2.
3.
4.
5.
6.
7.
8.
.19
.12
.15
.09
−.09
−.10
−.19
.01
−.10
.26
.45
.27
.48
.25
.60
−.29 −.04 −.25 −.31
−.12
.07 −.07 −.14
−.35
.02 −.30 −.34
.01
.29
.11
.07
−.02
.14 −.06
.01
.38
.37
.15
.03
.33
.25
.13
.02
.10
.46
−.17
−.01
.20
−.25
−.04
.75
.14 −.16 −.28
.61
.84
.71
.30
.05
.02
.22
.27
.04
.45
.82
.79 −.38 −.01 −.46
9.
10.
11.
.18
.13
.97
.61
.21
.12 −.02 −.22
.06
Note. N = 178. CDG = Commons Dilemma Game. PGDG = Public Goods Dilemma Game. For both games, we used
the created index scores. For the Commons Dilemma Game, the signs of the correlations were reversed. p < .01. for all
correlations of .20 or more; p < .05, for correlations from .16 to .19.
are differently affected by proself and prosocial motives. Towards this end, we computed correlations between the three
extracted motivational factors (proself, fearful, and prosocial) and choice behavior in the two games (using the standardized index scores of the games). This analysis revealed
that decisions in both games correlated significantly with
the proself and the prosocial motivational factors, but not
with the fearful factor. More specifically, the correlation
between the Commons Dilemma Game and the proself factor was r = −.27, while the correlation between the Public
Goods Dilemma Game and the proself factor was r = −.17.
We calculated the difference between these two correlation
coefficients using the cocor package in R (Diedenhofen &
Musch, 2015); this test revealed that the difference between
these two correlation coefficients did not reach statistical significance (Z = 1.41, p = .159). The correlation between the
Public Goods Dilemma Game and the prosocial factor was r
= .20, whereas the Commons Dilemma Game correlated r =
.16 with the prosocial factor. These correlations coefficients
also did not differ significantly in magnitude (Z = 0.56, p =
.577).
Subsidiary canonical correlations. The correlation analyses reported above seem to indicate that there might be
some specificity (i.e., the proself dimension is more influential in the Commons Dilemma Game, while the prosocial
dimension is more influential in the Public Goods Dilemma
Game). To test if this specificity is statistically significant,
we have conducted a canonical correlation analysis between
https://doi.org/10.1017/S1930297500004836 Published online by Cambridge University Press
the two games and the two motivational factors using the
yacca package in R (Butts, 2018). Canonical correlations
are used to identify and measure the associations among two
sets of variables. It determines a set of canonical variates,
orthogonal linear combinations of the variables within each
set that best explain the variability both within and between
sets. The results of this analysis revealed that only the first
(but not the second) canonical correlation was significant
(first canonical correlation: r = .30, χ2 (4) = 18.83, p <
001; second canonical correlation: r = .10, χ2 (1) = 1.92,
p = .166); which indicates that decisions in the Commons
Dilemma Game and the Public Goods Dilemma Game can
both be predicted from the two motivational factors, but not
in a way that is specific to each game.
2.3
Discussion
Based on the findings of Experiment 1, it can be concluded
that choice behavior in the Commons Dilemma Game and the
Public Goods Dilemma Game did not show significantly differing associations to the proself and prosocial motivational
dimensions. A possible explanation for this lack of specificity, however, is that the trait motives that we employed
in Experiment 1 may be only distantly related to choice behavior. To explore this possibility, we conducted a second
experiment in which the motives were measured as states.
Experiment 1 explored how taking and giving impacts
the motivational structure of the Commons Dilemma Game
and the Public Goods Dilemma Game. To further illu-
Judgment and Decision Making, Vol. 14, No. 5, September 2019
minate this question, Experiment 2 expanded our focus to
other mixed-motive games. Specifically, in addition to the
multiple-person Commons Dilemma Game and the Public
Goods Dilemma Game, Experiment 2 also included the Bandit Game and the Dictator Game – which involve taking and
giving in a dyadic setting, without partner dependence (Weber et al., 2004). By doing so, Experiment 2 enables us to
investigate not only motivational differences between taking
and giving in the Commons Dilemma Game and the Public Goods Dilemma Game (Comparison 1), but also whether
such differences may be enhanced in the dyadic Bandit Game
and Dictator Game (Comparison 2). Thus, Experiment 2 enables us to explore two theoretically relevant comparisons.
3 Experiment 2
3.1
Method
3.1.1
Sample and Procedure
A total of 247 US and UK adult participants — recruited
through the online platform Prolific Academic (http://www.
prolific.ac) — participated in the present study for payment
(£1.60). Participants played four games: One Commons
Dilemma Game, one Public Goods Dilemma Game, one
Bandit Game, and one Dictator Game. These four games
were presented in a randomized order. Each game was played
only once. The instructions were identical to Experiment
1. That is, participants were told that, in each game, they
would be connected to one or more fellow participants, and
that they would interact with each partner only once. They
were also informed that they would receive a bonus payment
based on one randomly selected game. In reality, however,
participants were not directly connected to each other during
the study and each participant received a fixed bonus payment
of £0.40. Again, participants received no information on the
other players’ decisions during the experiment. After each
of the four games, we measured the extent to which different
motives played a role in participants’ decision. Eighteen
participants failed to answer our included check questions
correctly, and were therefore excluded from the analyses.6
Our final sample thus consisted of 229 participants (34.1%
men, M age = 33.07, SD = 12.42). When inquired about
their highest educational level, 5.2% reported no degree,
37.6% mentioned a high school diploma; 40.6% reported
a Bachelor’s degree, 14.8% a Master’s degree, and 1.7% a
PhD degree.
6After each of the four game instructions, participants were asked to
answer two comprehension questions. Participants who were unable to
answer six out of eight (n − 2) check questions correctly were excluded
from further analyses (more information on these check questions can be
found on our OSF webpage: https://osf.io/jrqxb).
https://doi.org/10.1017/S1930297500004836 Published online by Cambridge University Press
Motivational basis of take-some and give-some games
3.1.2
541
Mixed-Motive Games
Commons Dilemma Game. In the Commons Dilemma
Game, four players had to simultaneously decide how much
to take from a collective resource that consisted of 160 chips
(each chip being worth £0.01). By means of a slider (beginning at 0 and moving up to 40), participants indicated how
many chips they wanted to take from the group resource.
Participants were told that the chips that were not taken by
the players would to be multiplied by factor 2.5, and that the
resulting number of chips (after multiplication) would then
be divided equally among the four players, regardless of how
many chips they took.7
Public Goods Dilemma Game. In the Public Goods
Dilemma Game, four players had to simultaneously decide
how much of their 40 individually owned chips they wanted
to give to the group resource. Participants were again presented by a slider which started at 0 and moved up to 40.
Participants were informed that the chips that were given by
the players would to be multiplied by factor 2.5, and then
equally divided between the four players.
Bandit Game. The Bandit Game reflects a two-person
take-some game (Eichenberger & Oberholzer-Gee, 1998).
At the start of this game, the participants possessed 0 chips
while the other player possessed 100 chips. By means of
a slider (beginning at 0 and moving up to 100), the participants had to decide how many of the other player’s chips
they wanted to take for themselves. The participants were
informed that the other player has no influence, and thus
must accept their decision.
Dictator Game. The Dictator Game is a two-person givesome game (Kahneman, Knetsch & Thaler, 1986). At the
start of this game, the participants possessed 100 chips while
the other player possessed 0 chips. During the task, the
participants must decide how many of their own chips they
wanted to give to the other player. Again, we presented
participants with a slider which started at 0 and moved up
to 100. Here too, participants were informed that the other
player has no influence on their decision.
3.1.3
Motivational States
In Experiment 2, we adopted a state-based approach to the
motivations. As such, following each of the four games, we
assessed to which extent each motive played a role in participants’ decision. We included the same prosocial (fairness,
altruism, social welfare concerns, and concern for others)
7To represent the Commons Dilemma Game and the Public Goods
Dilemma Game in Experiment 2, we utilized the version that displayed
the highest factor loading in Experiment 1 (i.e., game variant 7).
Judgment and Decision Making, Vol. 14, No. 5, September 2019
Motivational basis of take-some and give-some games
542
Table 4: Descriptive statistics and correlations between the game behaviors (Experiment 2).
1.
2.
3.
4.
Commons Dilemma Game (taking-behavior)
Public Goods Dilemma Game (giving-behavior)
Bandit Game (taking-behavior)
Dictator Game (giving-behavior)
M
SD
Range
1.
2.
3.
11.82
26.45
50.93
41.06
11.72
11.78
24.95
20.89
0-40
0-40
0-100
0-100
.38
.32
.26
.27
.41
.48
Note. N = 229. For the Commons Dilemma Game and the Bandit Game, the signs of the
correlations were reversed (so that all game behaviors point in the same direction). p < .01
for all correlations.
and proself (greed, competitiveness, and entitlement) motives as in the previous study (the fearful motives were no
longer included). To assess these motives as states, we utilized the interpersonal orientation measures of Van Lange
and colleagues (2007; also see Klapwijk & Van Lange, 2009;
Tazelaar, Van Lange & Ouwerkerk, 2004). The items of all
motive scales are listed in Appendix C.
3.2
Results
3.2.1
Game Data
The means, standard deviations, and inter-correlations between the four game behaviors are displayed in Table 4. This
table shows that the four game behaviors were all significantly correlated with each other. In the Commons Dilemma
Game, participants took on average 12 chips from the group
resource (and thus left 28 chips in the group resource). In
Public Goods Dilemma Game, participants gave on average
26 chips to the group resource (and thus kept 14 chips for
themselves). In the Bandit Game, participants took on average 51 chips from the other player (and thus left 49 chips for
the other player). In the Dictator Game, participants gave on
average 41 chips to the other player (and thus kept 59 chips
for themselves). As in Experiment 1, these findings indicate
that participants acted more cooperatively in the take-some
situations than in the equivalent give-some situations.
3.2.2
Motivational Data
Reduction of the motivations. Appendix D shows the correlation matrix of the motivational states, separately for each
of the four mixed-motive games. For each of these four
games, we conducted a factor analysis to extract two motivational factors from the inter-correlations among the motivational items (extraction method: Principal Axis Factoring;
rotation method: Oblimin). For each of the four games, we
were able to extract a prosocial motivational factor (which
consists of the fairness, altruism, social welfare concerns,
and concern for others items) and a proself motivational
factor (which consists of the greed, competitiveness, and entitlement items). Appendix E provides an overview of the
https://doi.org/10.1017/S1930297500004836 Published online by Cambridge University Press
factor loadings of these two factors, separately for each of the
four games. Note that for the Bandit Game, the three altruism items and the first two concern for others items had their
primarily loadings on the wrong factor and were therefore
discarded from the analysis in Model B.
Factor congruence. We subsequently calculated the degree of congruence between the sets of factor loadings reported in Appendix E. More specifically, following Harman’s
(1976) empirical rule, we computed correlations among the
factor loadings that were obtained in each of the four games
(for the Bandit Game, we used the two factors that were
extracted in Model B). The result of this analysis indicates
that the four extracted prosocial factors show high congruence (i.e., the correlations among their factor loadings ranged
from r = .96 to r = .98). Similarly, the four extracted proself
factors were also highly congruent (i.e., correlations among
their factor loadings ranged from r = .96 to r = .99).
3.2.3
Motivational Differences between the Games
As in Experiment 1, we first examined if games that involve taking behavior and games that involve giving behavior are differently affected by proself and prosocial motivations, by comparing the motivational profile of the Commons Dilemma Game with that of the Public Goods Dilemma
Game (Comparison 1). Similar analyses were also conducted
for the Bandit Game versus the Dictator Game comparison
(Comparison 2). Before conducting these analyses, we first
reversed the scores of the two take-some games (Commons
Dilemma Game and Bandit Game), so that the scores of all
four games pointed in the same direction.
Commons Dilemma Game versus Public Goods Dilemma
Game. We first computed correlations between the two
extracted motivational factors (proself and prosocial factor)
and choice behavior in the Commons Dilemma Game and
the Public Goods Dilemma Game. As in Experiment 1,
decisions in both games correlated significantly with both
motivational factors. More precisely, the correlation between the Commons Dilemma Game and the proself fac-
Judgment and Decision Making, Vol. 14, No. 5, September 2019
tor was r = −.38, while the correlation between the Public
Goods Dilemma Game and the proself factor was r = −.27.
We again tested the statistical significance of the difference
between these two correlations. The test showed that the
difference between these two correlation coefficients did not
reach statistical significance (Z = 1.50, p = .135). For the
prosocial factor, we found a correlation r = .45 with behavior
in the Public Goods Dilemma Game, while the Commons
Dilemma Game correlated r = .41. Here too, these two correlation coefficients did not differ significantly (Z = 0.71, p
= .481).
Bandit Game versus Dictator Game. We next computed
correlations between the two extracted motivational factors
and choice behavior in the Bandit Game and the Dictator
Game. Decisions in both of these games showed significant
associations with both the proself and the prosocial factor.
Yet, when comparing the strength of these associations, the
proself factor was not associated more strongly (Z = 1.57, p
= .116) with decisions in the Bandit Game (r = −.71) than
with decisions in the Dictator Game (r = −.63). However, the
prosocial factor did show a significantly stronger association
(Z = 6.25, p < .001) with decisions in the Dictator Game
(r = .67) than with decisions in the Bandit Game (r = .29).
This latter finding seems to indicate that, in line with our
predictions, prosocial motives are more strongly related to
giving behavior in the Dictator Game than to taking behavior
in the Bandit Game.
Subsidiary canonical correlations. The correlation analyses for our first comparison indicate that the proself motivational factor is more strongly related to taking behavior in the Commons Dilemma Game, whereas the prosocial
motivational factor is more strongly associated with giving
behavior in the Public Goods Dilemma Game. To test if
this specificity is statistical significant, we again conducted
canonical correlation analysis. Towards this end, we first created a sum score of the proself factors of the two games as
well as a sum score of the prosocial factors of the two games.
The analysis (using these sum scores) revealed that the first
canonical correlation did reach statistical significance (first
canonical correlation: r = .50, χ2 (4) = 65.37, p < .001), but
the second one did not reach statistical significance (second
canonical correlation: r = .05, χ2 (1) = 0.50, p = .479). As
in Experiment 1, choice behavior in multiple-person games
can be predicted from the two motivational dimensions, but
not in a game-specific way.
For our second comparison, the reported correlations also
seem to indicate that there might be some specificity, as the
proself factor is more influential in the Bandit Game and
the prosocial factor in the Dictator Game. To test the statistical significance of this specificity, we again conducted
a canonical correlation analysis (in which we again used
https://doi.org/10.1017/S1930297500004836 Published online by Cambridge University Press
Motivational basis of take-some and give-some games
543
combinations of the motive factors). The results of this analysis revealed that both resulting canonical correlates were
highly significant (first canonical correlation: r = .74, χ2 (4)
= 203.83, p < .001; second canonical correlation: r = .31,
χ2 (1) = 23.41, p < .001). This finding indicates that taking and giving in the Bandit Game and the Dictator Game
are associated with similar motives, yet considerable differences exist between the strength of the association of these
motives with choice behavior. Or stated differently, the significance of the second canonical correlation reveals that, for
these two games, the motives predict choice behavior in a
game-specific way. When taking a closer look at the raw
correlations (with the motive factors combined over both
games), it is apparent that prosocial motives more strongly
predict giving behavior in the Dictator Game (r = .62) than
taking behavior in the Bandit Game (r = .34), while proself
motives are about equally strongly related to taking and giving in both games (r = −.60 and r = −.65, for respectively
the Bandit Game and the Dictator Game).
3.3
Discussion
In Experiment 2, we employed a state-based approach to
measure the motivations and included two additional mixedmotive games. An interesting observation is that, in the
present study, the correlations between the motives and the
game behaviors were considerably larger than in Experiment
1. Despite these larger correlations, the results of the present
experiment revealed, similar to the prior study, no substantial
motivational differences between the Commons Dilemma
Game and the Public Goods Dilemma Game. When comparing the motivational profile of the Bandit Game with that
of the Dictator Game, we found specificity, but largely for
the prosocial motives — which were more influential in the
Dictator Game than in the Bandit Game.
4 General Discussion
Many conflicts in daily life arise from competing interests in
terms of selfish versus prosocial concerns. In research, various mixed-motive games have been developed to study these
conflicting interests. Although the basis of all mixed-motive
games resides in this self-other conflict, these games also
seem to exhibit unique elements. To gain more insight into
the motivational basis of different mixed-motive games, we
conducted two experimental studies. The main aim of these
studies was to investigate if games that involve taking behavior show differing associations to proself and prosocial
motivations than games that involve giving behavior. We
predicted that taking and giving might modulate the importance of proself and prosocial motives between structurally
equivalent games (as in the “slot-machine model” of interpersonal orientation of Van Lange et al., 2007). Our results
Judgment and Decision Making, Vol. 14, No. 5, September 2019
illustrate that motivational differences between taking and
giving only occur in games that are characterized by lower
interdependence and greater simplicity, that is, in dyadic
games.
4.1
Differential Effects of Proself and Prosocial Motives
In Experiment 1, no significant differences between the Commons Dilemma Game and the Public Goods Dilemma Game
in the association between motives and choice behavior were
observed. However, given that the associations between the
trait motives and the choice behaviors were generally low, we
complemented this study with a second experiment in which
the studied motives were measured as states, and taking and
giving was also examined in dyadic settings.
Experiment 2 revealed stronger associations between the
motives and the choice behaviors. However, when comparing the Commons Dilemma Game to the Public Goods
Dilemma Game, as in the first experiment, no significant motivational differences were observed. Yet, when comparing
taking and giving in the two dyadic games, giving behavior in the Dictator Game was associated more strongly with
prosocial motives than taking behavior in the Bandit Game.
The proself motives were about equally strongly related with
choice behavior in both games. As such, Experiment 2
provides evidence that prosocial motives may be associated
more with giving than with taking; but this evidence for
specificity was observed only in dyadic games.
How can we understand these findings? The results of our
studies suggest that motivational differences between taking
and giving may be observed more readily in situations that
are characterized by lower complexity and interdependence.
In multi-person games, such differences seem to be obscured
by the greater social complexity of decision-making. In
such settings, choice behavior is likely to be shaped by other
factors such as expectations about the other players’ behavior
(see Fleishman, 1988; Van Dijk & Wilke, 2000; Weber et
al., 2004), which may attenuate the impact of the measured
motivations. Indeed, a number of studies has shown that
expectations about how other people will behave strongly
affect people’s choices in social dilemma situations (e.g.,
Dawes, McTavish & Shaklee, 1977; Kelley & Stahelski,
1970; Schroeder, Jensen, Reed, Sullivan & Schwab, 1983).
In this vein, it is possible that our measurements of the
motives might have missed the relevance of expectancies
with respect to the other players’ behavior, which can also
help us explain why no differential effects of the motives were
found when comparing the two multiple-person games with
each other. Note that such considerations about the other
players’ behavior are strongly reduced in our dyadic games,
where participants can decide unilaterally. In this setting,
the impact of our motivational measures seems to be more
https://doi.org/10.1017/S1930297500004836 Published online by Cambridge University Press
Motivational basis of take-some and give-some games
544
pronounced, and some indications for distinct motivational
bases for taking and giving can be observed.
4.2
Limitations and Future Research Suggestions
When moving from Experiment 1 to Experiment 2, two
major changes were implemented. That is, in our second
experiment the motives were measured as states (instead of
traits), and we included two additional mixed-motive games
(i.e., the Bandit Game and the Dictator Game). As a result
of this, it is unclear whether the motivational traits that we
measured in our first experiment also relate to behavior in
the Bandit Game and the Dictator Game. Future research
in this domain is therefore encouraged to investigate if the
motivational differences that we found between these two
dyadic games also hold true with a trait-based assessment of
the motivations.
Another important avenue for future research is to gain
more understanding of the processes that underlie taking
and giving behavior, and the factors that may modulate their
associations to choice behavior. Take-some dilemmas concern decisions to take resources from a collectively owned
resource pool (in case of the Commons Dilemma Game)
or another person (in case of the Bandit Game). Because
childhood socialization practices generally define giving as
“good” and taking form others as “bad” (for a similar argument, see Fleishman, 1988, p. 176), it can be expected that,
in the context of take-some games, people will refrain from
taking a lot of resources (as this is considered bad behavior).
In accordance with this reasoning and the results of Brewer
and Kramer (1986), our experimental studies revealed that
participants indeed displayed greater cooperation when the
games were framed in terms of taking than when they were
framed in terms of giving.
Importantly, in addition to prosocial and proself motives
(on which we focused in the present research), differences
between taking and giving are likely to also be rooted in
other processes, including partner expectations, accountability, perceived norms, and efficacy (Kopelman, Weber
& Messick, 2002; Weber et al., 2004). Furthermore, differences between taking and giving could also be explained by
endowment effects (Kahneman, Knetsch & Thaler, 1991),
such that people feel more entitled to resources that they
regard as their property (Leliveld, Van Dijk & Van Beest,
2008). Future research may build on the present findings to
identify an expanded profile for taking and giving behavior,
as well as its dependence on other structural features (such as
provision point, group size, etc.). By doing so, we may better understand how take-some and give-some games shape
people’s mindset – and discover avenues by which socially
beneficial mindsets may be activated, so that the collective
interest can be promoted.
Judgment and Decision Making, Vol. 14, No. 5, September 2019
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