The impact of individual versus group rewards on work group performance and cooperation: A computational social science approach

Purpose To examine the effect of individual versus group evaluation and reward systems on work group behavior and performance under different task conditions. Methodology Uses computational social methods using Agent Based Models to simulate work group interactions as different forms of iterated games. Findings Group based systems outperform individual based and mixed systems, producing more cooperative behavior, the best performing groups and individuals in most types of interaction games. A new role emerges, the self-sacrificer, who plays a critical role in enabling other group members and the group, to perform better at their own expense. Research Implications Suggest opportunities for model development and guidelines for designing real world experiments. Practical Implications Helps firms engineer better performing work groups as well as the design of other business systems. Social Implications Identifies mechanisms by which cooperation can be developed in social systems. Originality/Value Demonstrates the role and value of computational social science methods and agent based models to business research