FROM THE PRINCIPLED PRINCIPAL TO THE SOCIAL TRAP: REINTERPRETING SYSTEMIC CORRUPTION IN LIGHT OF COLLECTIVE ACTION THEORY

This study addresses the problem of systemic corruption, moving beyond traditional explanations that confine the phenomenon to the agent's deviation from the principal's directives. The paper proceeds from the premise that the failure of anti-corruption policies stems from their reliance on the principal–agent model, whereas the reality in corruption-afflicted environments indicates that corruption constitutes a social trap and a collective-action dilemma in which corruption becomes a rational choice for individuals in the absence of mutual trust. The study adopts an analytical approach that deconstructs the intellectual structure of Mancur Olson's logic of collective action and shows how free-riding undermines integrity. It also puts forward a forward-looking vision for escaping this negative equilibrium by integrating advanced technological solutions. The paper's contribution lies in demonstrating how artificial intelligence and big-data algorithms can be employed to reshape individuals' rational calculations—by increasing the probability of automatic detection—thereby transforming corruption from a profitable opportunity into an uncalculated risk, and ultimately building participatory governance that strengthens trust and cooperation among economic and social actors.