An agent based model approach to study prosocial behavior in organizations

Riccardo Sartori, Andrea Ceschi, Dorina Hysenbelli, Xiuzhi Sang


Using a simulation named Agent Based Model (ABM) (Bonabeau, 2002; Epstein, 2006) we explore the effect of some prosocial behavior variables in a virtual environment, such as: Motivation to help, Warm- Glow feelings associated with helping (Andreoni, 1990), and the Pseudo-inefficacy effect. The Pseudoinefficacy effect found by Västfjäll & Slovic (2011), describes how the anticipated warm glow related to the satisfaction associated with helping, and the resultant motivation to help, decreases when we learn that there are some people who cannot receive help. Based on empirical data, in the present ABM simulation present two types of agents that help: Pseudo-inefficacy helping agents (PI) and rational helping agents (R) not affected by Pseudo-inefficacy, and two types of agents that need help: agents that can be helped, and agents that cannot be helped. The study shows the value of ABM modeling by replicating previous laboratory results and then illustrating how these results might be affected particularly for the presence of agents ratios. With all the limitations of the present model, the research provides a clear representation of what might happen in organizations and in social environment where prosocial behavior plays a key role.

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