Collective action and spontaneity cycles: Cascading dynamics under Bayesian games

TL;DR

This paper introduces a Bayesian game-based model incorporating social network dynamics and exogenous cycles to explain the formation and cyclical nature of collective action, supported by theoretical proofs and empirical simulations.

Contribution

It presents a novel action model combining Bayesian games and social network dynamics, proving spontaneous action and cycle theorems for collective action.

Findings

Confirmed the role of risk incentives and social ties in cycle formation.

Validated the theoretical model through numerical simulations.

Proposed a comprehensive theory explaining collective action cycles.

Abstract

The formation mechanisms and cyclical conditions of collective action have become open issues in research involving public choice, social movements, and more. For this reason, on the basis of rational decision-making and social assimilation, this paper proposes an action model that combines Bayesian game and social network dynamics, and incorporates exogenous cycles into it. For this model, this paper proves the spontaneous action theorem and action cycle theorem of collective action, and based on numerical simulation and empirical calibration, further confirms the theoretical mechanism involving elements such as risk/risk-free incentives and the number of social ties. Based on such conclusions and evidence, this paper proposes a theory of spontaneous cycles as an integrative answer to the open question of collective action formation/cycles.