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.