Suchergebnisse

Abstract
This paper addresses theoretically the question how virtual communication may affect cooperation in work teams. The degree of team virtualization, i.e. the extent to which interaction between team members occurs online, is related to parameters of the exchange. First, it is assumed that in online interaction task uncertainties are higher than in face-to-face contacts. Second, the gratifying value of peer rewards is assumed to be lower in online contacts. Thirdly, it is assumed that teams are different in the extent to which members depend on their peers for positive affections, operationalized by the extent to which team members are interested in social relationships for their own sake, independently from their work interactions. Simulation results suggest both positive and negative effects of team virtualization on work-cooperation.

Samenvatting

Explanations of opinion bi-polarization hinge on the assumption of negative influence, individuals' striving to amplify differences to disliked others. However, empirical evidence for negative influence is inconclusive, which motivated us to search for an alternative explanation. Here, we demonstrate that bi-polarization can be explained without negative influence, drawing on theories that emphasize the communication of arguments as central mechanism of influence. Due to homophily, actors interact mainly with others whose arguments will intensify existing tendencies for or against the issue at stake. We develop an agent-based model of this theory and compare its implications to those of existing social-influence models, deriving testable hypotheses about the conditions of bi-polarization. Hypotheses were tested with a group-discussion experiment (N = 96). Results demonstrate that argument exchange can entail bi-polarization even when there is no negative influence.

Abstract
In this paper we compare two micro foundations for modelling human behaviour and decision making. We focus on perfect strategic rationality on the one hand and a simple reinforcement mechanism on the other hand. Iterated prisoner's dilemmas serve as the play ground for the comparison. The main lesson of our analysis is that in the space of all possible 2 × 2 PDs different micro foundations do matter. This suggests that researchers can not safely rely on the assumption that implementing simple models of decision making will yield the same results that may be obtained when more sophisticated decision rules are built into the agents.

How can minority cultures resist assimilation into a global monolith in an increasingly "small world"? Paradoxically, Axelrod found that local convergence can actually preserve global diversity if cultural influence is combined with homophily, the principle that "likes attract." However, follow-up studies showed that this diversity collapses under random cultural perturbation. The authors discovered a new source of this fragility—the assumption in Axelrod's model that cultural influence is interpersonal (dyadic). The authors replicated previous models but with the more empirically plausible assumption that influence is social—people can be simultaneously influenced by several network neighbors. Computational experiments show that cultural diversity then becomes much more robust than in Axelrod's original model or in published variations that included either social influence or homophily but not both. The authors conclude that global diversity may be sustained not by cultural experimentation and innovation but by the ability of cultural groups to discourage those activities.

Concerns about models of cultural adaptation as analogs of genetic selection have led cognitive game theorists to explore learning-theoretic specifications. Two prominent examples, the Bush-Mosteller stochastic learning model and the Roth-Erev payoff-matching model, are aligned and integrated as special cases of a general reinforcement learning model. Both models predict stochastic collusion as a backward-looking solution to the problem of cooperation in social dilemmas based on a random walk into a self-reinforcing cooperative equilibrium. The integration uncovers hidden assumptions that constrain the generality of the theoretical derivations. Specifically, Roth and Erev assume a "power law of learning"—the curious but plausible tendency for learning to diminish with success and intensify with failure. Computer simulation is used to explore the effects on stochastic collusion in three social dilemma games. The analysis shows how the integration of alternative models can uncover underlying principles and lead to a more general theory.