The problem of free-riding arises when individuals benefit from a shared resource, service, or public good without contributing proportionately to its provision. This conduct often leads to a collective action problem, as individuals pursue personal gains while relying on the contributions of others. In this study, we present a Bayesian inference model to elucidate the behavior of participants in a public goods game, a conceptual framework that captures the essence of the free-riding problem. Here, individuals possess information on the distribution of group donations to the public good. Our model is grounded in the premise that individuals strive to harmonise their actions with the group's donation patterns. Our model is able to replicate behavioral patterns that resemble those observed in experiments with midsized groups (100 people), but fails to replicate those for larger scales (1000 people). Our results suggest that, in these scenarios, humans prefer imitation and convergence behaviors over profit optimization. These insights contribute to understanding how cooperation is achieved through alignment with group behavior.
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