Differences in Cooperation 1 Individual Differences in Cooperation in a Circular Public Goods Game

Research using the public goods game to examine behaviour in the context of social dilemmas has repeatedly shown substantial individual differences in patterns of contributions to the public good. We present here a new method specifically designed to capture this heterogeneity in play and classify participants into broad categories or types. Players in groups of four made initial, simultaneous contributions to the public good. Subsequently, players were sequentially told the current aggregate contribution to the public good and allowed to change their decision based on this information. The game continued, with players updating their contribution decision until the game ended at an unknown point. By looking at the relationship between players’ contributions and the aggregate value they observed, we were able to cleanly classify 82% of our players into three types: Strong Free Riders (28%), Conditional Cooperators or Reciprocators (29%), and Strong Cooperators (25%). We also found that scores on some of the personality dimensions we investigated (self-monitoring, self esteem, neuroticism, and conscientiousness) correlated with player type. Finally, males were found to be more likely to be Strong Cooperators than females. Differences in Cooperation 3 Individual Differences in Cooperation in a Circular Public Goods Game Over the last three decades, as in other areas of experimental research, individual differences have taken on greater importance in the context of group cooperation games. Whereas it used to be thought that players’ “dispositional qualities” would have only negligible effects in these environments (Pruitt & Kimmel, 1977), subsequent work among psychologists and economists began to take seriously the idea that individual differences among participants might be important in understanding and modeling behavior in experimental games (e.g, Liebrand, 1984; Yamagishi, 1986). More recently, Rapoport and Suleiman (1993), suggested that researchers might do well "to shift the focus of future research to identifying personality and attitude variables that allow the classification of subjects into different 'types' whose decision behavior in social dilemmas may be described by alternative models" (p. 193). Our research is an attempt to shed light on the way individual differences impact play in social dilemmas, situations in which individually selfish behavior leads to outcomes that are worse, in aggregate, for group members than if everyone had behaved cooperatively. A standard way to create social dilemmas in the experimental laboratory, and the one that forms the basis of our own experiments, is the Public Goods game. In this environment, players are given an endowment of tokens and must allocate them between a Private Account and a Group Account. Tokens in the Private Account yield a higher monetary return to the participant than tokens in the Group Account, but tokens in the Group Account improve the group’s aggregate outcome. (For recent reviews, see Komorita & Parks, 1995; Kurzban, 1998; Ledyard, 1995.) This structure provides a relatively clean way to investigate how individuals trade off their own interests against those of a group. Differences in Cooperation 4 The study of individual differences is becoming increasingly important in group-based games because of the emerging emphasis on the importance of reciprocity or “conditional cooperation” in social dilemmas. Briefly, it has been suggested that many players in repeated social dilemma games condition their contributions (level of cooperation) on the play of others, contributing a greater fraction of their endowment as a positive function of their beliefs about others’ contributions. Indeed, a consistent finding is that players’ contribution decisions are correlated, sometimes very strongly, with players’ expectations of others’ contributions (Bornstein & Ben-Yossef, 1994; Croson, 1998; Dawes, McTavish, & Shaklee, 1977; Komorita, Parks, & Hulbert, 1992; Kurzban, McCabe, Smith, & Wilson, 2000; Messick et al., 1983; Wit & Wilke, 1992; Yamagishi & Sato, 1986). This suggests that group dynamics might be strongly influenced by the composition of groups in terms of player types. If some players use reciprocal strategies, matching others’ contributions, then the presence of other players who contribute little or nothing to the public good (free riders) will lead to decreasing aggregate contributions over time as reciprocators match free riders’ small contributions. Hence, in repeated or sequential games, a feedback system is created that is sensitive to the proportion of each strategy type within the group and, moreover, determines the extent to which a group is able to sustain cooperation. Thus, individual strategies that group members pursue ripple through the group over time. This feedback loop can lead to strikingly varied dynamics. In a recent series of experiments by Kurzban, McCabe, Smith, and Wilson (2000), participants interacted in a real time linear public goods environment in which players were able to change their contributions as they received information about what other members in their group were contributing. In a condition in which group members could only increase their contribution during the round and Differences in Cooperation 5 knew only the lowest current contribution to the group account, many players kept their contribution to the public good slightly above the observed lowest value. This generated a kind of ratchet effect, enabling some groups to sustain high, occasionally perfect, levels of public good provisioning. However, in this particular environment, the presence of a singe free rider seems to have completely altered play dynamics. Some participants chose to keep their contribution at zero in this condition. Possibly because other (reciprocal) players observed that the lowest value never moved from zero, these groups generated almost no public good provisioning. What is odd about this result is that in this game, if all but one player in a group were using a strategy of maintaining his or her contribution slightly above the current lowest contribution, the last player, the would-be strong free rider, would do better for himself or herself by following the same strategy instead of free riding. The persistence of free riding behavior even when it was not a best response is puzzling, and the current investigation was in part motivated by this odd result. Our goals in the current experiment were two-fold. The first was to develop a method that could cleanly distinguish different types of players in the public goods environment. A related but ancillary objective was to try to observe how the type distribution within groups affects play dynamics. Second, we were interested in correlating the different types of individual play observed in the public goods game with personality variables that might be correlated with cooperative behavior. Much of the research on individual differences and cooperation is in the context of two-person games, and this experiment provided the opportunity to investigate variables that might be linked to cooperative play in group environments. Differences in Cooperation 6 Individual Differences in Cooperation in Groups Types. The game theoretical concept of a “type,” meaning differences in agents' information, beliefs, and preferences, is loosely analogous to the psychological concept of personality type. In both domains, the concept captures ways in which individuals systematically differ from one another. In economics, this is within the scope of a particular game theoretical environment, while in psychology the concept is designed to capture important ways in which people differ in their behavior in consistent ways in social settings. Results from public goods games have repeatedly shown that there is a great deal of variation in the strategies that participants use, and a number of classification schemes designed to capture this variation have been suggested. Suleiman and Rapoport (1992), for example, suggested that there were three types of players: those who are concerned with equity, those who tried to maximize their utility, and those whose play defied easy categorization. Weimann (1994) proposed a scheme dividing players into cooperative types, strong free riders, who contribute zero to the public good in every round of play, and weak free riders, who contribute a positive amount to the public good, but not their entire endowment. More recently, Fischbacher, Gächter, & Fehr (1999) suggested a four-part scheme in which players were classified as “Conditional Cooperators,” “Free Riders,” “Hump-shaped,” and “Others. ” A consistent feature of these disparate classification schemes is that some, but not all, participants are classified as strong free riders. In addition, it looks as though at least some players are reciprocators, contributing as a positive function of their beliefs about others’ contributions. However, to date, while there seems to be agreement that players use strategies that differ in systematical and discernable ways, there is no consensus on the correct classification scheme. Differences in Cooperation 7 With the exception of Fishbacher et al. (1999) the descriptive schemes were not the result of a specific attempt to distinguish among types. Fischbacher et al. (1999) asked participants to indicate what their contribution would be given a set of hypothetical contributions from the participant’s fellow group members. For most subjects, his or her answers to these hypothetical questions had no impact on their actual payment. Concerned that decoupling participants’ decisions and their outcomes might compromise the reliability of participants’ behavior, we developed a new method for distinguishing player types. Distinguishing types. To distinguish types of players in the public goods game, we designed an environment in which we could observe a large number of contribution decision