Experiment 2

advertisement
The effect of out-group competition on individual behavior
and out-group perception in the
Intergroup Prisoner’s Dilemma (IPD) gamei
Harel Goren
The Hebrew University of Jerusalem
Center for Rationality and Interactive Decision Theory
and the Department of Psychology
Biographical note: The author received his Ph.D. in social psychology from The
Hebrew University of Jerusalem and has recently finished a one year post-doctoral visit
to The Department of Management and Policy at The University of Arizona.
Abstract
Hebrew University of Jerusalem students participated in two experiments of
repeated play of the Intergroup Prisoners’ Dilemma (IPD) game, which involves
conflict of interests between two groups and, simultaneously, within each group. The
experiments manipulated the level of competition exhibited by the out-group members
(i.e., their level of contribution to their group’s effort in the conflict). Consistent with
the hypothesis that participants use strategies of reciprocal cooperation between groups,
higher levels of out-group competition caused participants to increase their contribution
and lower levels caused them to decrease it. In addition, participants had accurate recall
of the contribution levels of out-group members, and they attributed motivations to
out-group members in a manner that reflected their level of contribution. The nature of
reciprocation with the out-group is discussed in light of both behavioral and cognitive
data.
Key words: Intergroup conflict, Team games, Prisoner’s dilemma, reciprocal
strategies, Intergroup perception.
2
Introduction
What motives govern individual behavior in intergroup conflicts? The answer
to this question depends to a large extent on how the conflict is conceptualized. Social
scientists have often modeled intergroup conflict as a two-person game (Allison, 1971;
Axelrod, 1984; Brams, 1975; Snidal, 1986), necessarily assuming that the interest of
the individual is identical to that of his group. Thus, if it is rational for the group to
compete it must also be rational for the individual group member to do so. Other
researchers recognized that what is best for the group is not necessarily best for the
individual group member. Most notably, Campbell (1972) observed that contribution to
the collective group effort is not rational from the perspective of the individual since
“Group-level territoriality has always required that the soldier abandon for extensive
periods of time the protecting of his own wife, children and home” (p. 24).
The conflict between individual interest and group interest referred to by
Campbell (1972) is a problem of public goods provision (Rapoport and Bornstein,
1987; Bornstein, 1992). It stems from two facts. First, the payoffs associated with the
outcomes of inter-group conflicts (e.g., territory, political influence, higher wages) are
equally available to all the members of a group, regardless of their contribution to the
group’s effort. Second, although the size of these public goods increase the more group
members contribute, the individual’s contribution to the group’s effort is typically too
costly (in terms of money, time, effort or risk taking) to be justified on a rational basis.
Therefore, self-interested rational group members are expected to free ride on the
contribution of others. Of course, if everyone else free ride as well, the group would
lose the competition and the public goods.
To capture the intra-group and inter-group levels of conflict, Bornstein (1992)
devised the Intergroup Prisoner’s Dilemma (IPD) Game. The game as operationalized
3
in the present study involved a competition between two teams with three players in
each team. Each player received an endowment of 2 points and had to decide whether or
not to contribute his endowment towards the group’s effort. After decisions were made,
a bonus was paid to each player according to following scheme: if all players in Team A
contributed, while no players in Team B contributed, each player in A received a bonus
of 6 points and each players in B received 0 points. If there were 2 more contributors in
Team A than in Team B, each player in A received 5 points and each player in B
received one point. If there was one more contributor in Team A than in Team B, each
player in A received 4 points, whereas each player in B received 2. Finally, in case of an
equal number of contributors in both teams, each player in both Teams received a
3-point bonus. In addition to the bonus, a player who decided not to contribute kept the
2-point endowment. The payoffs to a member of Team A as a function of his decision to
contribute (C) or not to contribute (NC), the number of in-group contributors (mA) and
the number of out-group contributors (mB), appears in Figure 1.
The payoff parameters of the IPD game were such that: First, withholding
contribution was the dominant individual strategy; that is, regardless of what the
in-group and out-group members did, the individual earned an extra point by not
contributing. Second, the dominant strategy for each team was to have all of its
members contribute, regardless of what the out-group did. In the present experiment,
each team player earned 1 more point if all group members (including him) contributed
than if they all did not. Third, all members of both teams were better off if they all
withheld contribution than if they all contributed. When no one contributed (a 0:0 tie)
each player earned 5 points whereas if all contributed (a 3:3 tie), each player earned
only 3 points. No-contribution was, in fact, the collectively (i.e., Pareto) efficient
outcome of the game, the one which maximize the earnings of all six participants.
4
Figure 1. Payoff to a member in team A as a function of the decision to contribute (C)
or not to contribute (NC), the number of in-group contributors (mA) and the
number of out-group contributors (mB).
The first and second properties of the IPD game define the intra-group payoff structure
as a three-person PD game or a social dilemma (Dawes, 1980). Although the in-group’s
payoffs decrease the more out-group players contribute, the structure of the intra-group
dilemma remains constant regardless of the number of out-group contributors.ii As can
be seen in Figure 1, in all four intra-group PD games (corresponding to 0, 1, 2 and 3
out-group contributors in the IPD game) the cost of contribution for the individual and
the benefit (i.e., externality) it produces for the team are the same.
Therefore, if one assumes that individual behavior is motivated solely by self-interest -the assumption of narrow rationality -- one should expect no contribution in the
one-shot IPD game, irrespective of the out-group’s behavior. Similarly, if one assumes
that individuals are motivated only by a concern for the collective in-group interest, one
should expect full contribution, regardless of what the out-group does. Of course, in
5
reality, participants are likely to be concerned with both self-interest and common
group interest to various degrees. Nonetheless, any fixed combination of self-interest
and group interest should lead to a constant contribution rate, irrespective of the number
of out-group contributors.
What if participants are predisposed to maximize the relative difference in
payoffs between the in-group and the out-group? The assumption that people are
motivated to achieve positive self esteem by making the in-group positively distinct
from the out-group, is central to social identity theory (Hogg & Abrams, 1988; Tajfel
and Turner, 1986). This competitive inter-group motivation was demonstrated in
numerous laboratory experiments using the minimal group paradigm (for reviews see
Brewer, 1979; Diehl, 1990; Messick & Mackie, 1989; Tajfel, 1982). However, in the
IPD game individual behavior, even if governed by a motivation to maximize the
groups’ payoff difference, should not be affected by the behavior of out-group
members. This is so, because in the IPD, individual contribution increases the
in-group’s payoff by 3 points and reduces the out-group’s payoffs by 3 points,
regardless of the out-group behavior. Therefore, no matter what the out-group does,
individuals who wish to maximize the payoff difference between their team and the
other team should always contribute.
Participants’ decisions are expected to be affected by out-group behavior in the
one-shot IPD only to extent that they are motivated to “win” or at least not “lose” the
game. That is, if it is important to them that their group earns more than the out-group
(by any margin) or that it earns not less than the out-group. The notion that participants
are motivated to get at least as much as out-group members do (i.e. – motivated not to
“lose” the game) is supported by studies done in the minimal group paradigm, which
showed that equity considerations affect participants’ decisions (Diehl, 1989; Ng,
6
1981). These studies suggest that part of the reason for biased allocations in the
minimal group paradigm is that participants expect biased allocations by out-group
members. In trying to achieve an equitable allocation participants discriminate against
out-group members themselves. In the IPD game, which has a symmetric payoff
structure, equity considerations dictate that participants would contribute at the level
they expect out-group players to contribute.iii
Repeated interaction in the IPD game: The repeated IPD game is different
from the one-shot game in two important ways: First, in an on-going interaction
behavior can be dependent on the earlier choices of other players, whereas in a one-shot
game this is not possible. This opens the possibility for using strategies of reciprocal
cooperation in light of which contribution is seen as a rational strategic move. Second,
an iterated environment provides players with an opportunity to learn the structure of
the strategic situation and adapt their behavior accordingly -- an opportunity that they
do not have in a one-shot game.
Several experiments that examined the dynamics of contribution in the iterated
IPD game (Bornstein, Erev & Goren, 1994; Bornstein, Winter & Goren, 1996; Goren &
Bornstein, 1999) show that, when communication among players is prohibited (both
within and between teams), contribution decreases steadily as the game progresses.
These works maintain that the gradual decrease in contribution levels is most readily
accounted for by individual rationality (i.e., selfishness). To explain this finding all one
needs to assume is that players adapt their choice behavior as they become more
experienced, so that choices that have led to good outcomes in the past are more likely
to be repeated in the future (Harley, 1981; Maynard-Smith, 1984; Selten, 1991). Since
withholding contribution is the unconditionally best individual strategy in the IPD
game, this simple principle of reinforcement learning, known as the law of effect
7
(Thorndike, 1898), would inevitably move players in the direction of no contribution.
This interpretation receives substantial support from computer simulations which,
using Roth and Erev’s (1995) quantification of the law of effect, closely reproduce the
experimental results.
However, in addition to being the selfish (narrowly rational) individual strategy,
withholding contribution is also the cooperative strategy vis-a-vis the other group, since
it always increases the total out-group payoff by 3 points (1 point for each individual
out-group player). Therefore, low contribution levels could, in principle, reflect an
evolution of cooperation between the two teams.
Research on the two-person prisoner’s dilemma game has shown that mutual
cooperation evolves over time (Radlow, 1965; Rapoport, Am. & Mowshowitz, 1966;
Rapoport, An. & Cammah, 1965). Further studies have shown that strategies of
reciprocal cooperation, like TIT-FOR-TAT (Axelrod, 1984), are influential in bringing
mutual cooperation (Oskamp, 1971; Komorita, Hilty, & Parks, 1991; Wilson, 1971).
Reciprocity is defined as a norm that “prescribes that we should help those who have
help us in the past and retaliate against those who have injured us” (Komorita, Parks &
Hullbert, 1992, p. 608). Gouldner (1960) viewed the reciprocity norm as universal and
contributing to the stability of social structure.
It is possible that such tendencies for reciprocation are generalized to intergroup
contexts (Patchen, 1987). Rabbie (1998), for instance, explains the typical finding in
the Group-Individual Discontinuity paradigm (see review in Insko & Schopler, 1998)
as a reciprocity effect. According to Rabbie, it is possible that the increase in
competitive choices of groups (in comparison to individuals) results from the fact that
groups tend to reciprocate exploitative choices more than individuals.
8
Using between-team reciprocation in the IPD can help bring about the Pareto
efficient outcome of no contribution. By reacting to out-group contribution in kind
players can deter such behavior of out-group members. This is so, because their
contribution would reduce the out-group earnings in the round that follows. Reacting to
out-group contribution in kind is also consistent with the notion that people employ
equity considerations in inter-group interactions. Even though equity and reciprocity
are not identical, the use of reciprocal strategies can reduce the difference between the
final outcomes of the two teams.
In an attempt to differentiate between the process of learning and that of
between-team reciprocation in intergroup interaction, Goren and Bornstein (1999)
conducted an experiment in which the IPD game was played repeatedly under different
matching protocols. Their ‘Matching protocol’ manipulations related to changes in the
composition and matching of groups from one round to the other during the repeated
IPD experiment. In the fixed-matching condition, team composition and matching
between teams was constant throughout the entire game. This condition mimics a
naturally occurring intergroup interaction, in which people belong to the same distinct
group and two groups repeatedly interact with each other. In the mixed-matching
condition, the participants were randomly assigned to teams, which were randomly
paired for an IPD game at the beginning of each round of the experiment. Both
matching protocols provided participants with the opportunity to learn the structure of
the one-shot IPD game. But, whereas the fixed protocol enables them to use
between-team reciprocal strategies, the mixed protocol hinders any form of effective
reciprocation. The results showed no effect of matching condition on contribution, nor
an interaction of condition with time, thus failing to support between-group
reciprocation.
9
The experiment by Goren and Bornstein (1999) constituted a weak test for the
between-group-reciprocation hypothesis. In their “natural” experimental setting it is
quite difficult to disentangle the effect of between-team reciprocation from that of
learning. If all participants are learning the same thing, namely the dominant strategy of
withholding contribution, it is difficult to detect those players who (potentially) make
their decision contingent on the behavior of out-group players. Reciprocation in this
case (to the extent that it occurred in the fixed-matching condition) can possibly alter
the speed of the dynamic process but not reverse its direction.
Given the problem in interpreting the results of Goren and Bornstein (1999), the
present experiment used a more direct approach to examine between-group
reciprocation. Instead of using “real” out-group players, this study used simulated ones.
Using virtual players, whose behavior is predetermined, enables assessment of the
extent to which individuals react to the out-group. The virtual out-group players in this
study displayed different levels of contribution at different periods of the game. Based
on the principal of between-group reciprocation it was hypothesized that the
contribution levels of the participants’ would be affected by those of the virtual
out-group players. Specifically, participants were expected to contribute more
following high levels of out-group contribution, and less following low levels of
out-group contribution.
It is important to note that, although learning and reciprocation lead to the same
outcome, the two processes assume fundamentally different strategic aims. The
learning explanation simply maintains that, since it is the individual’s short-term
interest not to contribute, people will eventually learn to free ride. The fact that this
results in an outcome that is best for all players of both groups, is just a by-product of
this simple process of individual adaptation. Hypothesizing that players reciprocate
10
with out-group members, on the other hand, presupposes that people consciously
condition their behavior on that of the out-group, in a calculated attempt to bring about
a more beneficial outcome.
The hypothesis that participants employ between-team reciprocal strategies
requires that they would be attentive to the behavior of the out-group. This conjecture
was tested by examining how well the participants remember the contribution behavior
of out-group members during the game.
The motivations attributed to out-group members were also assessed in an
attempt to find out whether these motivational attributions reflect the pattern of
out-group behavior. Recent research indicates that people tend to reciprocate the
motivation they perceive others to have. Van Dijk and Wilke (1999) found that when
participants attributed the behavior of another player to self interest they contributed
more when their own contribution was necessary for the attainment of a public good
and less when it was not necessary for public good attainment. This is consistent with
the participants’ own self-interest since the public good was worth more then the
participants’ endowments (i.e., participants reciprocated selfishness by acting selfishly
themselves). The same effect was not obtained when participants interpreted the other
player’s actions as resulting from a motivation for fairness.
If the perception of motivations is involved in between-group reciprocation one
should expect participants of the current study to attribute different motivations to
out-group players who show different levels of contribution. Specifically, participants
should attribute competitive motivations to out-group members who contribute a lot,
and benign motivations to out-group members who refrain from contribution.
Furthermore, studying the motivations that participants attribute to out-group members
11
can help clarify the reasons that participants have for reciprocation with it. (This point
will be further developed in experiment 2.)
Below I report two experiments that tested these hypotheses. The first
experiment was designed to look mainly at the behavioral aspects of between-team
reciprocation, while the second focused more on the perception of out-group
motivations in the repeated IPD game.
Experiment 1
This experiment contrasted two conditions, involving different contribution
patterns by the out-group. In the High-to-Low (HTL) treatment, the virtual out-group
players started with a medium level of contribution, then contribution increased to a
very high steady level, decreased to a steady low level, and finally ended with a
medium level again. In the Low-to-High (LTH) treatment the pattern of contribution by
the virtual out-group members was the exact mirror image of the pattern in the HTL
treatment. Out-group players in the LTH condition contributed at a medium level, then
decreased contribution to a low level, increased it to a high level and then contributed at
a medium level again toward the end. The proportions of contribution by the virtual
out-group players in conditions HTL and LTH appear in Figure 2 (computed over 12
blocks of 5 rounds each).
To have a sufficiently powerful manipulation, the levels of contribution by the
virtual out-group members (in the ‘high’ periods) were higher than those usually found
in the repeated IPD game. In addition, the reason for contrasting these two conditions is
that the usual finding in the repeated (fixed) IPD game is a gradual decrease in
contribution levels. This pattern loosely fits the HTL condition and therefore it is
important to confirm that this pattern can reverse itself in the LTH condition, where the
out-group members first display a low level of contribution and only later increase it. If
12
such a reverse pattern is found this will serve as a clear confirmation for the use of
between-team reciprocation. It should be noted that since the overall levels of
contribution in the two virtual out-groups were identical (50% overall contribution by
each out-group member in both conditions) there was no point in assessing the
attribution of different motivations to the two different virtual out-groups in this
experiment.iv
Procedure
The participants were 60 undergraduate students at the Hebrew University of
Jerusalem (30 in each condition), with no previous experience with the task.
Participants participated in experimental sessions of 12 people each. When they arrived
at the laboratory the participants were seated in separate cubicles facing a personal
computer, and were given verbal and written instructions concerning the rules and
payoffs of the game. The instructions were phrased in terms of the individual's payoffs
as a function of his or her own decision (to contribute or not) and the decisions made by
the other players. The payoffs were summarized in a table, which was available to the
participants throughout the experiment. Participants were not instructed to maximize
their earnings, and no reference to cooperation or defection was made. Participants
were given a quiz to test their understanding of the game, and the instructions were
repeated until the experimenter was convinced that all the participants understood the
payoff rules. Participants were also told that to ensure the confidentiality of their
decisions they would receive their payment in sealed envelopes and leave the
laboratory one at a time with no opportunity to meet the other participants.
Participants played 60 rounds of the IPD game with the payoff parameters
described earlier. The 12 participants were divided into four three-person teams, and
were told that the same two teams would compete against each other throughout the
13
entire game. However, each team actually played against a virtual out-group under one
of the two the conditions described above (HTL or LTH).
Following each round, each participant received detailed feedback concerning
the decision made by every other in-group and out-group member in that round. In
addition, the participants received information about the total number of in-group
contributors, the total number of out-group contributors, their own earnings (in points)
in the last round, and their cumulative earnings.
The number of rounds to be played was not made known.v Following the last
round, the points were added up by the computer and cashed in at the rate of IS 1 for 8
points (1 Israeli Shekel was equal to $0.29 at the time the experiment took place, and
the average participant earned IS 36.6, or about $10.5). Participants then filled out a
questionnaire that included questions about the level of contribution by out-group
members in the first and last 20 rounds. They were then debriefed on the rationale and
purpose of the study, and were paid and dismissed individually.
Results
Contribution rates: The 60 rounds were divided into 12 blocks of five rounds
each, and the mean proportion of contributions per block was calculated. These means
appear in Figure 2. The issue of the possible dependency among players of the same
team was addressed by averaging the contribution proportions of all three team
members and using this team mean as the unit for analysis. Thus a 2 (experimental
condition) by 12 (blocks) mixed factorial design was used in the analysis.
The results of the ANOVA show a significant interaction effect of condition by
block (F(11,198)=5.15, p<0.05). The pattern of this interaction show that the participants
generally followed the levels of contribution displayed by the different virtual
out-groups. The participants tended to contribute more when the level of contribution
14
by out-group members was high, and less when it was low. The graphs of actual
contribution in the two conditions cross and alternate at about the same points in time as
those of the two virtual out-groups. Participants in the HTL condition contributed more
in the first part of the game than in the second part, while participants in the LTH
condition showed the exact opposite pattern.
The main effects for condition and block were non-significant (F(1,18)=0.21,
p=0.65; F(11,198)=0.46, p=0.93, respectively). Note that if individuals use between-team
reciprocal strategies, this is exactly the pattern of results one would expect. This is
because the total contribution rate by the virtual out-group players was identical in the
two conditions, and the contribution rate averaged across the two conditions is about
50% in each block..
Figure 2: Experiment I - Virtual out-group members’ behavior and observed behavior
(proportion of contribution) by block in the two experimental conditions.
15
Dependency of contribution on out-group behavior: If participants were making
their contribution decisions contingent on out-group behavior, then their decisions
should be correlated with the number of out-group contributors in previous rounds.
Table 1 shows the percent of contribution in round t (2 to 60) as a function of the
number of out-group contributors in round t-1 (1 to 59) in the two experimental
conditions. The frequencies shown in the table are computed over the decisions of all
participants in each condition. The table shows that in both conditions the proportion of
contribution increased as the number of out-group contributors in the previous round
increased from 0 to 3. In the HTL condition, contribution is about 29% when the
number of out-group contributors in the previous round is 0 or 1. Contribution increases
to a little over 40% when the number of out-group contributors is 2 or 3. In the LTH
condition, contribution is about 28% when the number of out-group contributors in the
previous round is 0 and it increases almost linearly up to 52% when the number of
out-group contributors in the previous round is 3.
Table 1: Experiment I - Percent of contribution (at round t) following 0, 1, 2 or 3
out-group contributors (at round t-1) in the two experimental conditions.*
# of out-group
contributors, t-1
condition
High to Low
Low to High
0
1
2
3
29.2
(17)
28.5
(16)
28.5
(11)
36.0
(15)
41.6
(15)
42.1
(11)
44.4
(16)
52.2
(17)
* Numbers in parentheses present the frequencies of each level of out-group
contribution in rounds 1 to 59 (t-1).
16
To have an adequate and unconfounded assessment of the correlation between
the individual’s contribution and the number of out-group contributors in the previous
round a separate logistic regression model was estimated for each participant. The
participant’s decisions were predicted by the number of out-group contributors and by
the number of other in-group contributors in the previous round. The regression
coefficient for the first predictor reflect changes in the individual’s contribution due to
out-group behavior, which can not be attributed to any concomitant tendency for
reciprocating in-group members’ behavior.
In the HTL condition the average logistic regression coefficient for the number
of out-group contributors in the previous round was 0.49 and in the LTH condition it
was 1.07. Both of these averages are significantly different from zero (t(29)=3.88,
p<0.001; t(28)=2.23, p<0.05 - respectively) providing yet another proof for the use of
between-team reciprocal strategies. (The positive logistic regression coefficients attest
to a positive correlation between the predicted event - contribution, and the predictor
variable - number of out-group contributors.)
The corresponding average logistic regression coefficients for the number of
in-group contributors in the previous round were smaller: 0.23 in the HTL condition
(t(29)=1.59, p=0.12) and 0.46 in the LTH condition (t(28)=2.29, p<0.05).
Memory of out-group contribution levels: Participants were asked to recall the
number of contributions made by each participant in the out-group in the first 20 rounds
and last 20 rounds of the game. The average level of contribution recalled (across the
three out-group members) was computed and analyzed in a 2 (condition) by 2 (first
20/last 20 rounds) mixed design ANOVA. Figure 3 shows the averages of recalled
contribution levels of the out-group in the first and last 20 rounds of the game in the two
conditions. (The average numbers of contributions actually made by virtual out-group
17
members in the first and last 20 rounds were 15 and 5 (respectively) in the HTL
condition, and 5 and 15 (respectively) in the LTH condition.)
Figure 3: Experiment I - Average recalled number of out-group contributions in the
first and last 20 rounds of the game in the two experimental conditions.
The analysis shows that, as expected, participants were quite attentive to the level of
contribution by the virtual out-group players. This fact is manifested in a significant
interaction effect between experimental condition (HTL or LTH) and the game period
(first or last 20 rounds) that participants were asked to recall (F(1,58)=52.7; p<0.01). The
main effects were non-significant. Since there was no difference between the two
experimental conditions with regard to the overall level of contribution by the
out-group, there was no reason to expect main effects of condition or of game period.
Nevertheless, as shown in figure 3 participants clearly over-estimated the
out-group’s contribution when it was at a low level, and under-estimated the
out-group’s contribution, when it was at a high level. This “regression to the mean” is
statistically significant. When out-group players contributed at a high level (15
contributions per player, on average, in 20 rounds), participants recalled a significantly
18
lower level of contribution. This was true both for the HTL condition were participants
recalled on average 12.72 in the first 20 rounds (t(29)=4.37, p<0.01), and the LTH
condition where they recalled 12.64 contributions in the last 20 rounds (t(29)=3.66,
p<0.01). Similarly, when out-group contribution was low (5 contributions per player,
on average, in 20 rounds), participants remembered it as significantly higher. (M=7.8,
t(29)=3.75, p<0.01, in the HTL condition, and M=8.89, t(29)=6.31, p<0.01 in the LTH
condition).
Discussion
The results of experiment 1 clearly demonstrate that individual behavior in the
repeated IPD game is affected by the behavior of out-group members. Generally
speaking, participants increased their own contribution when the competition by the
out-group was intense and decreased it when the out-group competition declined. As a
result, there was a significant correlation between participants’ decision to contribute
and the number of out-group contributors in the previous round. Participants also had a
fairly good recollection of the dynamics of out-group behavior. These results are
consistent with the hypothesis that individuals are using strategies of between-team
reciprocation in a continuous interaction with the same out-group.
The current results are inconsistent with explaining the gradual decline in
contribution in previous IPD experiments as resulting only from individual learning.
Especially, individual learning models would not predict an increase in contribution in
later rounds of the game as was demonstrated in the LTH condition.
As an illustration, a simulation was run in which the simulated players used
Roth and Erev’s (1995) learning algorithm and were confronted by each of the two
virtual out-group contribution patterns. Fifty “groups” of simulated players were run in
each of the two conditions. The results appear in figure 4. As can be easily seen in the
19
figure, there was no interaction between time and the two virtual out-groups
contribution patterns (F(11,1078)=1.03, p=0.42, using the same ANOVA as the one used
on the actual participants’ data). The simulation results show only a decline in
contribution over time without any responsiveness to the virtual out-groups’ behavior
(F(11,1078)=8.60, p=0.0001, for the block effect). This pattern was contradicted by the
results of the actual participants in the experiment who responded to the level of
out-group contribution.
Figure 4: Experiment I - Simulated data of “players” using Roth and Erev’s (1995)
learning model and confronted by the two virtual out-groups.
It is important to note that the contribution level of the (actual) participants was
on average considerably lower than that of the (virtual) out-group members. This lower
contribution level clearly rules out the possibility that participants use strict
between-team reciprocal strategies that respond to every contribution by the out-group
with a contribution of their own.
The most plausible explanation for the above results is that some mixture of
between-team reciprocation and individual learning was taking place. In other words,
20
while participants changed their contribution behavior in reaction to that of the
out-group, they also gradually learned that, regardless of what the out-group does, they
are better off holding on to their endowments. This possibility will be discussed further,
in light of the results of experiment 2.
Experiment 2
The focus of experiment 2 is on whether the contribution levels by out-group
members affect the way they are being perceived by in-group members. As mentioned
in the introduction, it is likely that the perception of other participants’ motivations is
involved in the reciprocation process. Since experiment 1 supported the hypothesis of
between-team reciprocation, the aim of experiment 2 was to find whether participants
would attribute different motivations to out-group members according to their different
levels of contribution.
Bornstein and Ben-Yossef (1994) argued that a high contribution level in the
IPD game may reflect either competitive (maximizing-relative-difference) motivation,
or an increase in “patriotism” (maximizing-ingroup-gain), or both. Comparing the IPD
game with a parallel single-group PD game Bornstein and Ben-Yossef found
contribution twice as high in the IPD game. Participants also rated in-group and
out-group members on several motivation scales. Consistent with the high contribution
in the IPD condition participants there rated both in-group and out-group members as
more competitive, more “patriotic” and less motivated by self-gain than in the
single-group PD.
In the current experiment participants were asked to rate out-group members on
four motivation scales: self-gain interest (maximizing individual gains), “patriotism”
(maximizing in-group gains), competitiveness (maximizing relative gain difference)
and intergroup cooperation (maximizing the joint gain of both teams). It seemed
21
reasonable to measure attributions on the ‘max-joint’ motivation scale since
between-team reciprocation can bring about an outcome that is good for both teams.
The expectation was that higher levels of contribution by out-group members would
lead participants to perceive them as more competitive and “patriotic”, and that lower
contribution levels would lead to perceiving them as more cooperative vis-a-vis the
in-group.vi
Measuring the motivations that participants attribute to out-group members can
help clarify the reasons behind the use of between-team reciprocation. For instance, the
predictions just mentioned assume that participants are equally focused on the two
aspects of reciprocal strategies – reciprocating cooperative choices and retaliating
against competitive choices. However, participants may be more focused on one aspect
of reciprocation than the other. In that case, the manipulation of out-group contribution
level may affect the ratings of some motivations but not of other. This is especially
likely if participants engage in reciprocation because they are motivated to get as much
as the out-group (motivated not to “lose” the game). If this is the case, participants may
be more concerned with the out-group’s competitive motivation than with its
cooperative motivation, and the manipulation of out-group contribution will affect
ratings on the competitive (max-rel) scale more than on the cooperative (max-joint)
scale.
Experiment 2 addressed the issue of out-group perception by manipulating the
variability in contribution behavior of individual players within the out-group, in
addition to manipulating their average contribution level. The literature on inter-group
perception has documented a tendency to view out-group members as more similar to
each other than in-group members. This perceptual bias termed “the out-group
homogeneity effect” (Linville & Fisher, 1998; Quattrone, 1986) should be accentuated
22
when there is conflict of interests between the groups (Judd & Park, 1988). It is
therefore interesting to test whether, in the IPD game, participants pay attention to the
behavior of individual out-group members, and, consequently, attribute different
motivations to different out-group members depending on their individual conduct.vii
Therefore, experiment 2 entailed a two-factor design. One factor involved the
average contribution level of the virtual out-group that was either high (70%
contribution throughout the 40-period game) or low (30% contribution). The high
contribution (Hi-Cont) and low contribution (Low-Cont) conditions were crossed with
two levels of out-group variability, a low variability level (Low-Var) and a high
variability level (Hi-Var). In the Low-Var conditions the three out-group players
contributed at almost the same rate. In the Hi-Var conditions the virtual out-group
players contributed at different rates.
It was hypothesized that contribution levels would increase over time in the
‘Hi-Cont’ conditions (where out-group contribution was high) and that contribution
would decrease with time in the ‘Low-Cont’ conditions (where out-group contribution
was low). In other words, it was hypothesized that there will be an interaction effect of
time with the ‘Average contribution’ factor. In addition, in line with between-team
reciprocation, a positive lagged correlation between participants’ decisions and those of
the out-group was expected. (If between-team reciprocation is strong enough, then one
can also predict a main effect of the ‘Average contribution’ factor, with more
contribution by participants in the Hi-Cont conditions then in the Low-Cont conditions.
However, this effect can be greatly influenced by the initial levels of contribution in the
different conditions. The speed with which participants react to the level of contribution
of the virtual out-group can also influence the likelihood of attaining a main effect for
the ‘Average contribution’ factor.)
23
Following experiment 1, one can expect participants to have good recollection
of out-group contribution behavior. To the extent that participants differentiate between
out-group members who contribute a lot and those that contribute at a low rate, one can
also expect the participants to attribute different motivations to out-group members
according to their contribution levels (as discussed earlier). This effect should manifest
itself in main-effect differences between the Hi-Cont and Low-Cont conditions. To the
extent that participants pay attention to the behavior of individual out-group members,
this effect should also manifest itself in differences between motivation ratings for
indivudual out-group members.
Experimental Design and Procedure
The participants were 96 undergraduate students at the Hebrew University of
Jerusalem (24 in each condition), with no previous experience with the task.
Participants played 40 rounds of the IPD game. Each three-person team played against
a virtual out-group of one of the four kinds described above (Hi-Cont/Hi-Var,
Hi-Cont/Low-Var, Low-Cont/Hi-Var or Low-Cont/Low-Var). The exact numbers of
contributions by each out-group player during the entire 40 rounds were as follows:
Hi-Cont/Low-Var condition: 29, 28 and 27 contributions; Hi-Cont/Hi-Var condition:
36, 30 and 18 contributions; Low-Cont/Low-Var condition: 13, 12 and 11 contributions;
Low-Cont/Hi-Var condition: 22, 10 and 4 contributions. In all conditions the initial
levels of contribution of the virtual out-groups were medium. This means that the
differences between the level of contribution of the high contributing virtual out-groups
and of the low contributing virtual out-groups increased as the game progressed.viii
Following the last round, the points were added up by the computer and cashed
in at the rate of IS 1 for 7 points (the average participant earned IS 25.8, or about $7.5).
Participants filed out a post-experimental questionnaire in which they were inquired
24
about the number of contributions made by the out-group players during the 40-round
game, and their perceptions of the out-group players’ motivations. Participants were
told that they would be rewarded for being accurate in recalling contribution levels.ix
In all other details the experimental procedure was identical to that used in
experiment 1.
Results
Contribution rates: The 40 rounds of play were divided into 8 blocks of five
rounds each, and the mean proportion of contributions per block was calculated. These
means appear in Figure 5. Again, the unit of analysis was the average proportion of
contribution by the three members of the same team.
These average proportions were analyzed by a 2 (‘Average contribution’:
‘Hi-Cont’ vs. ‘Low-Cont’) by 2 (‘Variability’: ‘Hi-Var’ vs. ‘Low-Var’) by 8 (block)
mixed design ANOVA. This analysis revealed a significant main effect of ‘Variability’
(F(1,28)=4.10, p=0.053) and a significant interaction between the ‘Average contribution’
and ‘Variability’ factors (F(1,28)=4.51, p<0.05). The main effect for ‘Average
contribution’ was not significant.
Both the main effect for variability and the interaction effect were not predicted
by the hypotheses. Comparing the mean levels of contribution in the 4 experimental
conditions reveal that as expected these means were relatively high in the Hi-Cont
conditions (Hi-Cont/Low-Var - 36.7%; Hi-Cont/Hi-Var - 36.3%) and low in the
Low-Cont/Low-Var condition (22.3%). However, for some reason, participants in the
Low-Cont/Hi-Var condition contributed at a high rate of 40.1% (similar to those in the
Hi-Cont conditions). This resulted in the significant effects above.
It is possible that the explanation for this result is sampling error. The
proportions of contribution in the very first round, which could not have been affected
25
by the experimental manipulation, were 37.5% in the ‘Hi-Cont/Low-Var’ condition,
50.0% in the ‘Hi-Cont/Low-Var’ condition, 41.7% in the ‘Low-Cont/Low-Var’
condition, and 66.7% in the ‘Low-Cont/Hi-Var’ condition. (In the first block of 5
rounds the proportion of contribution was 38.3% in the ‘Low-Cont/Low-Var’ condition,
and 54.2% in the ‘Low-Cont/Hi-Var’ condition. Again, this difference could not have
resulted from the experimental manipulation since the feedback about out-group
behavior in rounds 1 to 4 was identical in these two conditions.) It seems that by chance
there were more participants with a high propensity for contribution in the
‘Low-Cont/Hi-Var’ condition.
This interpretation is supported by an analysis of covariance (ANCOVA) of the
contribution proportions in blocks 2 through 8 using the number of contributors in a
team in the first round as a covariate (and all other factors as in the first ANOVA).
Regarding the overall levels of contribution the ANCOVA showed a significant
main effect of ‘Average Contribution’ (F(1,27)=5.39, p<0.05), a significant interaction
between the ‘Average contribution’ and ‘Variability’ factors (F(1,27)=4.44, p<0.05) and
a significant effect of the covariate (F(1,27)=6.06, p<0.05). These results show that when
considering the initial levels of contribution in the teams (levels which can only be
affected by random factors) the unpredictable ‘Variability’ effect vanishes, the
predicted effect of ‘Average Contribution’ is held and the unexpected interaction
between the two factors remains.
26
Figure 5: Experiment 2 - Observed proportion of contribution by block in the four
experimental conditions.
More relevant to the a priori hypotheses, is the analysis involving the effect of block
(time) on contribution. This analysis shows a significant effect of block (F(7,196)=3.0,
p<0.01) and a significant interaction of block and ‘Average (out-group) contribution’
(F(7,196)=4.21, p<0.01). Overall, contribution decreased with time (block). However,
this trend was qualified by the following interaction effect: in the Low-Cont conditions,
contribution of the actual participants decreased over time, whereas in the Hi-cont
conditions it remained constant. Linear contrasts involving the proportions of
contribution in the 8 blocks show that, indeed, the decrease in contribution level in the
Low-Cont conditions was significant (t(7)=5.71, p<0.01 in the ‘Low-Cont/Hi-Var’
condition and t(7)=2.03, p=0.08 in the ‘Low-Cont/Low-Var’ condition), whereas that in
the Hi-cont conditions was not.
Regarding the contribution time trend, the above mentioned ANCOVA showed
only a significant interaction of time (block) with the ‘Average Contribution’ factor
27
(F(6,162)=2.33, p<0.05). This was the only predicted effect involving the time factor.
Thus, the ANCOVA supported the predicted pattern of results to a greater extent than
the original ANOVA.
Dependency of contribution on out-group behavior: Table 2 shows the percent
of contribution in round t (2 to 40) as a function of the number of out-group contributors
in round t-1 (1 to 39) in the four experimental conditions. The frequencies shown in the
table are computed over the decisions of all participants in each condition.
Table 2: Experiment 2 - Percent of contribution (at round t) following 0, 1, 2 or 3
out-group contributors (at round t-1) in the four experimental conditions.*
# of out-group
contributors, t-1
condition
Hi-Cont/Low-Var
Hi-Cont/Hi-Var
Low-Cont/Low-Var
Low-Cont/Hi-Var
0
1
2
3
25.0%
(1)
20.8%
(1)
13.3%
(10)
38.2%
(12)
40.8%
(5)
31.3%
(6)
21.0%
(23)
40.0%
(20)
34.6%
(23)
35.8%
(20)
35.8%
(5)
36.8%
(6)
40.4%
(10)
39.6%
(12)
54.2%
(1)
58.3%
(1)
* Numbers in parentheses present the frequencies of each level of out-group
contribution in rounds 1 to 39 (t-1).
As can be seen in the Table the overall proportion of contribution increased as a
function of the number of out-group contributors in the previous round. However, the
statistical analysis of each participant’s decision dependency on the behavior of the
other players showed weak results. As in experiment 1, the contribution decisions of
each participant in round t (2 to 40) were predicted by a logit regression model with the
number of out-group contributors and the number of in-group contributors in the
previous round (1 to 39) as predictors.
28
The average coefficients for the number of out-group contributors were: 0.250
(t(22)=1.64, p=0.12) in the ‘Hi-Cont/Hi-Var’ condition; 0.216 (t(23)=1.22, p=0.24) in the
‘Hi-Cont/Low-Var’ condition; -0.306 (t(21)=0.65, p=0.52) in the ‘Low-Cont/Hi-Var’
condition and 0.836 (t(21)=4.85, p<0.01) in the ‘Low-Cont/Low-Var’ condition. Thus
only in the ‘Low-Cont/Low-Var’ condition there was clear evidence that participants
made their decisions contingent on the contribution of the out-group in the previous
round.
The average coefficients for the number of in-group contributors were generally
smaller and non-significant in all four conditions (0.189, t(22)=1.10, p=0.28; 0.246,
t(23)=1.50, p=0.15; 0.279, t(21)=0.42, p=0.68 and 0.095, t(21)=0.20, p=0.84, in the same
conditions, respectively).
Recall of out-group behavior: Participants were asked to recall the number of
contributions made by each out-group member during the 40 rounds of the game.
The mean level of contribution recalled (averaged across the three out-group members)
was computed and analyzed with a 2 (‘Average contribution’) by 2 (‘Variability’)
between subject ANOVA. Figure 6 shows the recalled contribution level in the four
conditions. (The actual average levels of contribution by the virtual out-groups were 28
in the ‘Hi-Cont’ conditions and 12 in the ‘Low-Cont’ conditions.)
Figure 6: Experiment 2 - Average recalled number of out-group contributions in the
four experimental conditions.
29
Not surprisingly, participants recalled a higher level of out-group contribution in the
Hi-Cont conditions (26.6 contributions out of 40, averaged across the 2 Variability
conditions) as compared with the Low-Cont conditions (14.9 across the two Variability
conditions). This difference was significant (F(1,90)=133.5, p<0.01). The effect of the
‘Variability’ factor and the interaction effect were non-significant.
Recalled contribution of individual out-group players: As mentioned earlier,
participants were asked to recall the number of contributions made by each of the three
out-group members during the game. To test whether participants differentiated
between the individual out-group players, a repeated measures ANOVA on the recalled
contribution level of each of the three out-group players was conducted separately in
each condition. In the ‘Hi-Var’ conditions, where out-group members contributed at
very different rates, this effect was significant (F(2,46)=18.4, p<0.01 in the
‘Hi-Cont/Hi-Var’ condition; F(2,44)=11.3, p<0.01 in the ‘Low-cont/Hi-Var’ condition).
In the ‘Low-Var’ conditions, where there was almost no difference between the
contribution rates of the three out-group members, this effect was non-significant. (In
all four conditions the means of recalled contribution of the three out-group players
were perfectly ordered according to the level of contribution they showed throughout
the game.)
Ratings of out-group members’ motivations: Participants were also asked to
estimate the extent to which out-group members were motivated to maximize their
self-interest (max-self), their narrow group interest (max-ingroup), the collective
payoffs of both teams (max-joint), and the difference between the in-group and the
out-group payoffs (max-rel).
30
Average ratings of out-group motivations: The average rating for the three
out-group players was computed, for each of these four scales. Table 3 shows the
average ratings in the four conditions.
Table 3: Experiment 2 - Average ratings of out-group motivations in the four
experimental condition (standard deviations in parentheses).
Condition:
Motivation
Max-self
Max-ingroup
Max-joint
Max-rel
Hi-Cont/
Low-Var
Hi-Cont/
Hi-Var
Low-Cont/
Low-Var
Low-Cont/
Hi-Var
8.11
(1.85)
6.79
(2.41)
2.90
(2.72)
6.81
(2.69)
7.43
(1.90)
7.22
(2.17)
3.56
(2.19)
7.57
(1.70)
7.38
(1.72)
5.78
(2.47)
3.40
(2.68)
5.44
(2.54)
7.78
(1.63)
4.33
(2.30)
2.38
(1.77)
3.97
(2.40)
The average ratings on each motivation scale were analyzed using a 2 (‘Average
contribution’ factor) by 2 (‘Variability’ factor) between subject ANOVA. Participants
in all conditions rated out-group players as similarly motivated by their self-gain and as
similarly motivated to maximize the collective (max-joint) payoffs (a motivation that
was overall rated as quite low). As a result, the effects of the experimental conditions on
these two scales were not significant.
As predicted, the average ratings of out-group members on the max-ingroup
scale and the max-rel scale were greatly affected by the experimental manipulation.
Participants in the high out-group contribution conditions rated out-group members as
more motivated on both scales (F(1,92)=16.65, p<0.01 for the ‘Average contribution’
factor in the max-ingroup scale; F(1,92)=26.29, p<0.01 for the same factor in the max-rel
scale).
In addition, there was a significant interaction in the ratings of these motivations
(F(1,92)=3.84, p=0.053 in the max-ingroup scale; F(1,92)=5.31, p<0.05 in the max-rel
31
scale). The pattern of the interaction show that the differences between ratings in ‘High’
and ‘Low’ out-group contribution conditions are larger under the ‘High-Variability’
manipulation than under the ‘Low-Variability’ manipulation (see table 3).
Motivational attributions to individual out-group members: To find out whether
participants perceived individual out-group members differently depending on their
individual contribution behavior, a one-way repeated measures ANOVA on each rating
scale was conducted within each condition. As expected, significant differences were
found in the ‘High-Variability’ conditions concerning ratings on the max-self scale (in
‘Hi-Cont/Hi-Var’ condition F(2,46)=3.06, p=0.057; in ‘Low-Cont/Hi-Var’ condition
F(2,46)=3.66, p<0.05). Similar differences were found on the max-ingroup scale, in
‘Low-Cont/Hi-Var’ condition (F(2,44)=8.37, p<0.01), and on the max-rel scale, in the
‘Hi-Cont/Hi-Var’ condition (F(2,46)=6.81, p<0.01). Although no general significant
effect was found on the max-rel scale in the ‘Low-Cont/Hi-Var’ condition (in rating
individual out-group members), a contrast between the ratings for the out-group player
with the highest contribution rate and the one with lowest rate, was significant
(t(22)=1.954, p<0.05, one tailed).
In all these cases the perception of individual out-group players motivations
corresponded perfectly to their level of contribution during the game. Out-group
players who contributed more were rated higher on the max in-group and max-rel
scales. These high contributors were also perceived as less motivated to maximize their
self-gain.
Discussion
The main behavioral findings of experiment 2 can be summarized as follows:
When the level of out-group contribution was low, in-group players decreased their
contribution as the game progressed. When out-group players contributed at a high rate,
32
the in-group’s level of contribution remained constant throughout the game. In
comparison to experiment 1, the high rate of out-group contribution used in this
experiment (70%) was not high enough to cause participants to increase their
contribution above its initial level.
One unexpected aspect of the results was the interaction between the ‘Average
Contribution’ factor and the ‘Variability’ factor in their effect on the total levels of
actual contribution. The interaction resulted from a high level of contribution in the
Low-Cont/Hi-Var condition. This phenomenon persisted even when the initial levels of
contribution were statistically controlled. This statistical control was employed in order
to ‘even out’ the participants pre-existing tendencies for contribution in the game. Of
course, the contribution level in only one round (the first) is an insensitive way for
measuring such tendencies. It is possible that using a more sensitive measure (if such
existed) would have eliminated the unexpected interaction effect.
An alternative explanation for the interaction between the ‘Average
Contribution’ and the ‘Variability’ factors is that participants were willing to react only
to a consensual decrease of contribution, a decrease showed by all out-group members.x
According to this explanation a persistent and relatively high contribution level shown
by any one of the out-group players causes the participants to maintain a relatively high
level of contribution themselves. This explanation seems in line with the fact that only
in the Low-Cont/Low-Var condition the correlation between the participants’ decisions
and the number of out-group contributors in the previous round was statistically
significantly.
However, this explanation can not account for some other aspects of the results.
First, the contribution trend in the Low-Cont/Hi-Var condition is clearly decreasing.
The overall high contribution there is influenced by the very high initial levels and not
33
from a flat contribution trend. Second, even though significant lagged correlations were
not found in all of the conditions one can not claim that participants there did not react
to out-group behavior. In the ‘Hi-Cont’ conditions, for instance, contribution level
remained the same throughout the entire game. This pattern is distinctly different from
the pattern of contribution in all previous experiments that did not involve manipulation
of out-group contribution (Bornstein, Erev & Goren, 1994; Bornstein, Winter & Goren,
1996; Goren & Bornstein, 1999; Goren & Bornstein, 2000) and must have resulted
from reacting to out-group behavior.
A possible explanation for the low lagged correlations is that the virtual
out-group behavior in the present experiment (in both the Hi- and Low-Cont
conditions) was considerably less variable than in experiment 1. In particular,
participants in the Hi-Cont conditions almost did not experience zero out-group
contribution and participants in the Low-Cont conditions almost did not experience full
out-group contribution (see table 2 for details). It is possible that this ‘range-truncation’
attenuated the lagged correlations between participants’ decisions and out-group
behavior in previous rounds.
In sum, the observed contribution patterns in experiment 2 gave partial support
to the a priori predictions, which were based on the between-team reciprocation
hypothesis. The interaction effect which was not predicted resulted from high
contribution in the ‘Low-Cont’/Hi-Var’ condition. The question raised by these results
is whether individuals lower contribution only in response to a similar behavior by all
out-group members.
As mentioned earlier, the focus of experiment 2 was not on individuals’ use of
between-team reciprocation, but rather on testing whether the perception of out-group
34
members’ motivation is based on their observed behavior. Indeed the results here are
clearer.
As in experiment1, participants were very attentive to the out-group’s behavior.
Participants recalled well the mean contribution level of the out-group. In addition to
the results of experiment 1, experiment 2 shows that participants accurately remember
the contribution behavior of each individual out-group player.
Experiment 2 also shows that the motivations attributed to out-group members
correspond quite well to their actual behavior. Out-group members who contributed
more were rated as more competitive and as more “patriotic” then those who
contributed less. This was found on the aggregate level, i.e.- in the mean attributions for
all three out-group members, and in the attributions for individual out-group members.
However, the perception of the cooperative motivation (maximizing joint gains
of both teams) was totally uninfluenced by the experimental manipulations. No
differences were observed in attributing this motivation to out-group members - not at
the aggregate level nor at the individual level. In line with the hypothesis of
between-team reciprocation low contribution levels of the out-group led to a decrease
in contribution by the participants. It was reasonable to expect that this reciprocation of
no- contribution would be accompanied by attributing a cooperative motivation to
out-group members. That this was not the case suggests that participants were focused
more on retaliating high levels of out-group contribution than on reciprocating the
cooperative choice of no contribution by the out-group.
In sum, experiment 2 shows, that participants’ perception of out-group behavior
is quite accurate and that they attribute corresponding motivations to the members of
the out-group both at the aggregate and the individual levels. The perception of
35
out-group members’ motivation, however, focused more on competitiveness than on
intergroup cooperative motivations.
The results place some boundary conditions on the notion that intergroup
conflict should increase the tendency to see out-group members as similar to one
another. Indeed, the Judd and Park (1988) study that tried to address this question gave
mixed results: lower judgments of out-group variability at the group level (in the
competition condition) but better recall for individuating information about out-group
members. The current data shows that out-group perception can be accurate and varied,
at least in aspects that are important to decision making within the intergroup conflict.
As Messick and Mackie (1989) note, even in situations of extreme intergroup conflict
(i.e., war) there might be an incentive to differentiate between out-group members (p.
58).
General Discussion
The approach taken by this study is different from that which typifies the
stereotyping literature. Instead of focusing on in-group/out-group biases in situations of
“minimal” interdependence (e.g., Platow, Mclintock & Liebrand, 1990; Sherman et al.
1998), it studies how the behavior of the out-group, in the context of a “realistic”
on-going conflict, affects the behavior of the in-group and its perception of the
out-group. In terms of Wilder and Simon’s (1998) classification, the focus here is on
dynamic groups, groups in interaction, rather then on groups as mere social categories.
The IPD team game, employed in this study as a model of intergroup conflict,
entails conflict of interests within the competing groups as well. The intragroup conflict
is conceptualized as an n-person PD game, or a social dilemma. This conceptualization,
which distinguishes between the collective group interest and the interest of the
individual group member, implies two qualitatively different processes of conflict
36
resolution, one which involves reciprocal cooperation at the intergroup level, and
another that relies on narrow-rationality, or selfishness at the individual level.
Previous results in iterated play of the IPD (without communication) provided
no evidence for between-group reciprocation. When players cannot communicate, a
decline in contribution was observed as the game progressed (Bornstein, Erev & Goren,
1994; Bornstein, Winter & Goren, 1996). This pattern is consistent with the notion that
individuals gradually learn that, personally, they are better off withholding
contribution, regardless of what the other (in-group and out-group) players do.
In the two experiments reported here it was found, through direct manipulation
of out-group contribution level, that individuals are affected by the out-group’s
behavior. In other words, some form of between-team reciprocation is taking place,
even when group members cannot coordinate their actions. This reciprocation,
however, is only partial, in the sense that the level of out-group contribution is not quite
matched. In particular, when there were no out-group contributors on round t, there was
typically some in-group contribution in round t+1, and when out-group contribution
was larger than zero, in-group contribution was typically less than full.
These data should be contrasted with recent results of IPD play with
communication (Goren & Bornstein, 2000). When group members can communicate
and coordinate their action, groups often use reciprocation strategies. The reciprocation
strategy which seems the most effective in bringing about a “peaceful” resolution to the
conflict, is a strict between-team TIT-FOR-TAT strategy, where cooperative
(no-contribution) behavior by the out-group is reciprocated in kind, but any positive
level of contribution is retaliated against with full force (Goren & Bornstein, 2000).
Obviously, without communication (as in the current study) group members are unable
to coordinate on a strict between-team reciprocal strategy.
37
If participants were not fully reciprocating with the out-group, what else
explains their behavior in the game? The results are consistent with the interpretation of
participants’ behavior as a mixture of reciprocation and learning. When out-group
contribution is low enough participants do not react to small variations in it, and the
main process governing their behavior is the one of gradual adaptive learning. Hence
the decrease in contribution over time in the Low-Cont conditions of experiment 2.
When out-group contribution is high participants react by increasing their own
contribution. This tendency can prevent the usual trend of a decrease in contribution
over time (the Hi-Cont conditions of experiment 2) of even reverse it (experiment 1).
The data about the perception of out-group motivations is also consistent with this
“dual process” model.
Generally speaking, the results show that participants are highly aware of what
the out-group does. They recall the out-group’s behavior accurately both at the
out-group’s aggregate level and at the individual level. Participants also attributed
higher levels of intergroup competitiveness (max-rel) and “patriotism” (max-ingroup)
to out-group members with high levels of contribution than to those with low levels.
These attributions are certainly correct within the context of the IPD game structure (as
discussed in the introduction).
However, participants did not distinguish between high-contributing and
low-contributing out-groups on the max-joint scale. Clearly, participants did not
interpret low levels of out-group contribution as a cooperative move intended to
maximize the outcome of both teams (i.e., max-joint). At the same time they regarded
high level of out-group contribution as a sign of competitive and “patriotic”
motivations. Thus, when encountering a competitive out-group (one with high
contribution), participants reacted by increasing their own contribution. However,
38
when encountering a low contributing out-group, they did not see it necessarily as
cooperative, which perhaps can explain why in-group contribution level in this case
was higher than that of the out-group.
In comparison, teams in the Goren and Bornstein (2000) study, which involved
within-team communication, had the insight to signal and reciprocate cooperative
intents by entirely eliminating contribution on their part. In these cases, group members
also attributed high cooperative motivation to out-group members. It seems that in the
current study the reciprocation strategy that participants employed focused more on
retaliating high levels of out-group competition than on reciprocating low levels of
out-group contribution (levels which could have been construed as attempts for mutual
cooperation between the teams).
Much research has shown that groups are highly competitive -- much more so
than individuals under the same structural conditions (Insko &Schopler, 1998). Insko et
al. (1998) show that this “discontinuity” or group-competitiveness effect can be
reduced if groups use long-term considerations. Insko et al. introduced such
considerations as part of their experimental manipulations. The present experiments, as
well as the experiment by Goren & Bornstein (2000), demonstrate that groups, and to a
lesser extent individual group members, are capable of using long-term considerations
(or repeated-game strategies) without outside intervention.
Rabbie (1998) made a similar argument. Using a paradigm close to that of Insko
and his associates, he shows that groups employ reciprocity considerations more often
then individuals. Rabbie attributes the use of reciprocal strategies by groups to
intragroup discussion. He maintains that during discussion group members gain a better
understanding of game’s reward structure and, as a result, “groups … are more likely
than individuals to follow a long-term cooperative tit-for-tat strategy” (p. 485).
39
The results of Goren and Bornstein’s (2000) experiment on the effect of
within-group communication in the IPD game are clearly in agreement with Rabbie’s
argument. The current study suggests that, while intragroup communication is
necessary for strict between-group reciprocation, people respond to out-group behavior
even without being able to communicate.
The current line of research on repeated play of the IPD game opens many
possibilities for additional study on the conditions that promote cooperation between
groups. The Goren and Bornstein (2000) study and the different reaction to the two
Low-contribution conditions in experiment 2 (the one with high variability and the one
with low variability) suggest that people are more likely to reciprocate attempts of
cooperation that all out-group members adhere to. The data certainly shows that people
are perceptive of behavioral differences between out-group members. This question
certainly merits additional research and points to a functional relation between
intergroup reciprocation behavior and the perception of out-group variability.
One of the problems in analyzing the data of experiment 2 was that apparently
there were great individual differences in the willingness to contribute. This aspect of
interaction in the IPD game was studied by Probst, Carnevale and Triandis (1999).
They found that individuals who strongly endorsed values of vertical individualism
(characterized by viewing the self as autonomous and accepting social inequality) were
also very likely to contribute in the IPD game. Individuals who strongly endorsed
values of vertical collectivism (characterized by viewing the self as an aspect of the
group while accepting inequality) indicated a very low willingness to contribute in the
IPD.
Studying such individual differences can explain initial levels of contribution in
the repeated IPD game and help explain more variance of behavior in the game. It can
40
probably do more than just that. A recent study of van Lange (1999) found that
individuals who show a pro-social value orientation also show the strongest tendency
for reciprocation with another player in a two-person PD game. Similarly, it is possible
that individual differences in the IPD game will be related to repeated game strategies
and not only to the initial contribution levels.
In conclusion, using the repeated IPD game can further our understanding about
the relationships between individual tendencies, reciprocation strategies and out-group
perception in the context of ongoing intergroup conflicts.
41
References
Abbink, K., & Sadrieh, A. (1995). RatImage: Research assistance toolbox for
computer-aided human behavior experiments. University of Bonn, Discussion
paper No. B-325.
Allison, G. (1971). Essence of decision: Explaining the Cuban missile crisis. Boston:
Little, Brown.
Axelrod, R. (1984) The Evolution of cooperation. New York: Basic Books.
Bornstein, G. (1992). The free rider problem in intergroup conflicts over step-level and
continuous public goods. Journal of Personality and Social Psychology, 62,
597-606.
Bornstein, G., & Ben-Yossef, M. (1994). Cooperation in intergroup and single-group
social dilemmas. Journal of Experimental Social Psychology, 30, 52-67.
Bornstein, G., Erev, I., & Goren, H. (1994). The effects of repeated play in the IPG
and IPD team games. Journal of Conflict Resolution, 38, 690- 707.
Bornstein, G., Winter, E., & Goren, H. (1996). Experimental study of repeated team
games. European Journal of Political Economy, 12, 629-639.
Brams, S. (1975). Game theory and politics: International relations games. New York:
Free Press.
Brewer, M. B. (1979). In-group bias in the minimal intergroup situation: A
cognitive-motivational analysis. Psychological Bulletin, 86, 307-323.
Campbell, D. T. (1972). On the genetics of altruism and the counter-hedonic
components in human culture. Journal of Social Issues, 28, 21-37.
Dawes, R. M. (1980). Social dilemmas. Annual Review of Psychology, 31, 169193.
42
Diehl, M. (1989). Justice and discrimination between minimal groups: The limits of
equity. British Journal of Social Psychology, 28, 227-238.
Diehl, M. (1990). The minimal group paradigm: Theoretical explanations and empirical
findings. In W. Stroebe & M. Hewstone (Eds.) European Review of Social
Psychology. (Vol. 1, pp. 263-292). Chichester, Englend: Wiley.
Goren, H., & Bornstein, G. (1999). Reciprocation and learning in the Intergroup
Prisoner’s Dilemma game. In D. Budescu, I. Erev, & R. Zwick (Eds.) Games and
Human Behavior: Essays in Honor of Amnon Rapoport. Hillsdale, NJ: Erlbaum.
Goren, H., & Bornstein, G. (2000). The Effects of Intra-group Communication on
Intergroup Cooperation in the Repeated Intergroup Prisoner's Dilemma (IPD)
Game. Journal of Conflict Resolution, 44, 700-719.
Gouldner, A. W. (1960). The norm of reciprocity: A preliminary statement. American
Sociological Review, 25, 161-178.
Harley, C. B. (1981). Learning the evolutionary stable strategy. Journal of Theoretical
Biology, 89, 611-633.
Hogg, M., & Abrams, D. (1988). Social Identifications. London: Routledge.
Insko, C. A., & Schopler, J. (1998). Differential distrust of group and individuals. In C.
Sedikides, J. Schopler & C. A. Insko (Eds.) Intergroup Cognition and Intergroup
Behavior. Mahwah, NJ: Lawrence Erlbaum.
Insko, C. A., Schopler, J., Pemberton, M. B., Wieselquist, J., McIlraith, S. A., Currey,
D. P., & Gaertner., L. (1998). Long-term outcome maximization and the reduction
of interindividual-intergroup discontinuity. Journal of Personality and Social
Psychology, 75, 695-711.
43
Judd, C. M., & Park, B. (1988). Out-group homogeneity: Judgments of variability at the
individual and group levels. Journal of Personality and Social Psychology, 54,
778-788.
Komorita, S. S., Hilty, J. H., & Parks, C. D. (1991). Reciprocity and cooperation in
social dilemmas. Journal of Conflict Resolution, 35, 494-518.
Komorita, S. S., Parks, C. D., & Hulbert, L. G. (1992). Reciprocity and the induction of
cooperation in social dilemmas. Journal of Personality and Social Psychology, 62,
607-617.
Linville, P. W., & Fisher, G. W. (1998). Group variability and covariation: Effects on
intergroup judgment and behavior. In C. Sedikides, J. Schopler & C. A. Insko
(Eds.) Intergroup Cognition and Intergroup Behavior. Mahwah, NJ: Lawrence
Erlbaum.
Maynard-Smith, J. (1984). Game theory and evolution of behavior. Behavioral and
Brain Sciences, 7, 95-125.
Messick, D. M., & Mackie, D. M. (1989). Intergroup relations. Annual review of
psychology, 40, 45-81.
Ng, S. H. (1981). Equity theory and the allocation of rewards between groups.
European Journal of Social Psychology, 11, 439-444.
Oskamp, S. (1971). Effects of programmed strategies on cooperation in the prisoner’s
dilemma and other mixed-motive strategies. Journal of Conflict Resolution, 15,
225-259.
Patchen, M. (1987). Strategies for eliciting cooperation from an adversary: Laboratory
and internation findings. Journal of Conflict Resolution, 31, 164-185.
44
Platow, M. J., McClintock, C. G., & Liebrand, W. B. (1990). Predicting intergroup
fairness and ingroup bias in the minimal group paradigm. European Journal of
Social Psychology, 20, 221-239.
Probst, T. M., Carnevale, P. J., & Triandis, H. C. (1999). Cultural values in intergroup
and single-group social dilemmas. Organizational Behavior and Human Decision
Processes, 77, 171-191.
Quattrone, G. A. (1986). On the perception of a group’s variability. In S. Worchel & W.
G. Austin (Eds.) The Psychology of Intergroup Relations. Chicago: Nelson-Hall.
Rabbie, J. (1998). Is there a discontinuity or a reciprocity effect in cooperation and
competition between individuals and groups? European Journal of Social
Psychology, 28, 483-507.
Radlow, R. (1965). An experimental study of cooperation in the Prisoner's Dilemma
game. Journal of Conflict Resolution, 9, 221-227.
Rapoport, Am., & Bornstein, G. (1987). Intergroup competition for the provision of
binary public goods. Psychological Review, 94, 291-299.
Rapoport, Am., & Mowshowitz, A. (1966). Experimental studies of stochastic models
for the prisoner dilemma. Behavioral Science, 11, 444-458.
Rapoport, An., & Chammah, A. M. (1965). Prisoner's dilemma: A study in conflict and
cooperation. Ann Arbor: University of Michigan Press.
Roth, A. E., & Erev, I. (1995). Learning in extensive-form games: Experimental data
and simple dynamic models in the intermediate term. Games and Economic
Behavior, 8, 164-212.
Selten, R. (1991). Evolution, learning, and economic behavior. Games and Economic
Behavior, 3, 3-24.
45
Sherman, J. W., Klein, S. B., Laskey, A., & Wyer, N. A. (1998). Intergroup bias in
group judgment processes: The role of behavioral memories. Journal of
Experimental Social Psychology, 34, 51-65.
Snidal, D. (1986) The game theory of international politics. In Kenneth Oye (ed.),
Cooperation under anarchy. Princeton: Princeton University Press.
Tajfel, H. (1982). Social psychology of intergroup relations. Annual Review of
Psychology, 33, 1-39.
Tajfel, H., & Turner, J. C. (1986). The social identity theory of intergroup behavior. In
S. Worchel & W. G. Austin (Eds.) The Psychology of Intergroup Relations.
Chicago: Nelson-Hall.
Thorndike, E. L. (1898). Animal intelligence: An experimental study of the associative
processes in animals. Psychological Monographs, 2.
van Dijk, E., & Wilke, H. (1999). Conditional contributions and public good provision:
Perceptions, motives, and behavioral reactions. Group Processes and Intergroup
Relations, 2, 245-258.
van Lange, P. A. (1999). The pursuit of joint outcomes and equality in outcomes: An
integrative model of social value orientation. Journal of Personality and Social
Psychology, 77, 337-349.
Wilder, D., & Simon, A. F. (1998). Categorical and dynamic groups: Implications for
social perception and intergroup behavior. In C. Sedikides, J. Schopler & C. A.
Insko (Eds.) Intergroup Cognition and Intergroup Behavior. Mahwah, NJ:
Lawrence Erlbaum.
Wilson, W. (1971). Reciprocation and other techniques for inducing cooperation in the
prisoner’s dilemma. Journal of Conflict Resolution, 15, 167-196.
46
Footnotes
i
This research was supported by a doctoral research grant from the Israel Foundations Trustees
(1997-1998) and was done as part of the requirements for my doctoral thesis. Additional support was
given by the Joseph Trink Fellowship Endowment Fund (France). I thank Professor Gary Bornstein and
three anonymous reviewers for many valuable comments on an earlier version of this paper. I also wish
to thank Zohar Gilula and Alexey Valenco, of RatioLab (the Laboratory for Interactive Decision Theory
at the Hebrew University of Jerusalem), for their help in data collection and in programming the software
for the experiments. Please address correspondence to Harel Goren, RatioLab - Laboratory for
Interactive Decision Theory, Faculty of Social Sciences, The Hebrew University of Jerusalem, Mt.
Scopus, Jerusalem 91905, ISRAEL. E-mail: [email protected]
ii
The absolute level of the payoffs to in-group members decreases, following out-group contribution,
because the game between the two teams (considering each team a unitary player) is a 2-person
prisoner’s dilemma game as defined by the second and third properties above.
iii
Of course, in the IPD model and in the classical minimal group paradigm all participants are symmetric
- they have equal choices to make with equal power over allocations. Therefore it is impossible to
distinguish equity considerations from equality considerations in these two paradigms.
iv
Also note the following: A- each virtual out-group member contributed exactly 30 times in 60 rounds
(50%). Therefore, there is zero variability between individual out-group members in their level of
contribution and there is no point in assessing differences in the attribution of motivations to specific
virtual out-group members. B- the exact pattern of contribution over time of the three virtual out-group
players within the same condition followed the same pattern (HTL or LTH).
v
Participants’ decisions and all feedback information were handled by a computer program that used the
RatImage toolbox (Abbink & Sadrieh, 1995).
vi
The prediction for the self-gain motivation is less clear. Low levels of contribution are consistent with
self gain. However, in the context of the repeated game, high levels of contribution can also be motivated
by self gain if they are intended to promote long run cooperation within the group.
vii
Because this experiment did not control the behavior of in-group members it is hard to determine
whether there exist tendencies to view out-group members’ motivations as more negative and/or as more
similar to each other than in-group motivations. The main thrust of this experiment was to test the extent
to which observed out-group behavior affects the perception of out-group members’ motivations and to
relate these perceptions to the notion of between-team reciprocation.
viii
In the Low Variability conditions all three virtual out-group players showed the same pattern of
contribution over time (increase in the High Contribution condition and decrease in the Low
Contribution condition). In the High Variability conditions 2 virtual out-group members showed the
corresponding contribution pattern (increase in the Hi-Cont condition and decrease in the Low-Cont
condition) while the third virtual player showed a slight opposite trend.
ix
The absolute deviations of the recalled contribution rates from the actual rates of contribution by the
different players were calculated for each participant. The three participants with the highest accuracy
scores (i.e., with the lowest sum of absolute deviations) were contacted and paid the amount of 35 NIS
each.
x
I am in debt to one of the anonymous reviewers for suggesting this idea.
47
Download