Tag Archives: Cooperation

Greed and Fear in Network Reciprocity: Implications for Cooperation among Organizations

This paper depicts the evolution of cooperation on regular lattices, with strategies propagating locally by relative fitness. The underlying dilemma arises from two distinct dimensions—the gains for exploiting cooperative partners (Greed) and the cost of cooperating with exploitative partners (Fear). This paper uses computational experiments to show that embedding interaction in networks generally leads Greed and Fear to have divergent, interactive, and highly nonlinear effects on cooperation at the macro level, even when individuals respond identically to Greed and Fear. We then replicate our experiments on inter-organizational network data derived from links through shared directors among 2,400 large US corporations.

Kitts, James A., Leal, Diego F., Jones, Thomas M., Felps, Will, and Shawn L. Berman. “Greed and Fear in Network Reciprocity: Implications for Cooperation among Organizations” PLoS ONE 11(2), 2016.

Cultural Evolution of the Structure of Human Groups

Small-scale human societies are a leap in size and complexity from those of our primate ancestors. We propose that the behavioral predispositions which allowed the evolution of small-scale societies were also those that allowed the cultural evolution of large-scale sociality, in the form of multiple transitions to large-scale societies. Although sufficient, the cultural evolutionary processes that acted on these predispositions also needed a unique set of niche parameters, including ecological factors, guiding norms, and technologies of social control and coordination. Identifying the regularities and patterns in these factors will be the empirical challenge for the future.

Carel van Schaik, Pieter Francois, Herbert Gintis, Daniel Haun, Daniel J. Hruschka, Marco A. Janssen, James A. Kitts, Laurent Lehmann, Sarah Mathew, Peter J. Richerson, Peter Turchin, Polly Wiessner. “Cultural Evolution of the Structure of Human Groups” Cultural Evolution. Cambridge, MIT Press, 2014.

Trust and Privacy in Distributed Work Groups

Trust plays an important role in both group cooperation and economic exchange. As new technologies emerge for communication and exchange, established mechanisms of trust are disrupted or distorted, which can lead to the breakdown of cooperation or to increasing fraud in exchange. This paper examines whether and how personal privacy information about members of distributed work groups influences individuals’ cooperation and privacy behavior in the group. Specifically, we examine whether people use others’ privacy settings as signals of trustworthiness that affect group cooperation. In addition, we examine how individual privacy preferences relate to trustworthy behavior. Understanding how people interact with others in online settings, in particular when they have limited information, has important implications for geographically distributed groups enabled through new information technologies. In addition, understanding how people might use information gleaned from technology usage, such as personal privacy settings, particularly in the absence of other information, has implications for understanding many potential situations that arise in pervasive computing environments.

Anthony, Denise, Kitts, James, Masone, Christopher, and Sean W. Smith. “Trust and Privacy in Distributed Work Groups.” In Social Computing and Behavioral Modeling. Edited by Dominika Latusek and Andrea Gerbasi. IGI Global, 2009.

Norms

Norms Kitts, James A. and Yen-Sheng Chiang. Encyclopedia of Social Problems, Sage Publications, May 2008.

Prestige

Prestige Kitts, James A. and Blaine G. Robins. Encyclopedia of Social Problems, Sage Publications, May 2008.

Social Influence and the Emergence of Norms Amid Ties of Amity and Enmity

This paper explores the coevolution of social networks and behavioral norms. Previous research has investigated the long-term behavior of feedback systems of attraction and influence, particularly the tendency toward homogenization in arbitrary cultural fields. This paper extends those models by allowing that norms diffuse not only by simple contagion but through intentional sanctioning behavior among peers. Further, the model allows for negative relations, where actors differentiate themselves from enemies while seeking to align themselves with friends. Sociometric maps reveal nontrivial system dynamics – structural bifurcation, discrimination between factions, and cycles of deviance and solidarity – emerging from a few elementary agent-level assumptions.

View online appendix here.

Kitts, James A. “Social Influence and the Emergence of Norms Amid Ties of Amity and Enmity.” Simulation Modelling Practice and Theory, 14(3): 407-422, March 2006.

Structural Learning: Attraction and Conformity in Task-Oriented Groups

This study extends previous research that showed how informal social sanctions can backfire when members prefer friendship over enforcement of group norms. We use a type of neural network to model the coordination of informal social control in a small group of adaptive agents confronted with a social dilemma. This model incorporates two mechanisms of social influence, informal sanctions and imitation. Both mechanisms vary with the strength of the social tie between source and target. Previous research focused on the effects of social sanctions. Here, we demonstrate a curvilinear effect of imitation – or “mimetic influence” – on compliance with prosocial norms. Moderate doses of mimetic influence reduce the coordination complexity of self-organized collective action and help the network achieve satisfactory levels of cooperation. High doses, however, undermine the learning required to find cooperative solutions. Increasing group size also diminishes compliance due to increased complexity, with larger groups requiring more imitation to overcome the coordination problem.

Kitts, James A., Macy, Michael W., and Andreas Flache. “Structural Learning: Attraction and Conformity in Task-Oriented Groups.” Computational and Mathematical Organization Theory, 5:129-145, 1999.