Analysis of dynamic reward and penalty mechanisms in closed-loop supply chain for power batteries based on evolutionary game theory

Purpose With the rapid and explosive development of the new energy vehicle industry, power battery recycling has evolved into a vital component in fulfilling resource circulation and the “dual carbon” goals. The current industry faces challenges, including poor coordination between market entities and unbalanced profit distribution. This research aims to improve recycling efficiency through optimised reward mechanisms. Design/methodology/approach This study presents a tripartite evolutionary game model. Manufacturers, third-party recyclers and cascade utilisation enterprises are the key participants. It takes government subsidies and reward-penalty mechanisms within the supply chain into account. It examines the evolutionary rules of strategy selection for each participant, along with the stability of the system. Then it carries out simulation validation. Findings Static reward-penalty mechanism results in cyclical fluctuation within the system and impedes stable cooperation. Linear dynamic reward and penalty mechanisms provide some motivation for manufacturers and cascade utilisation enterprises but fail to impose effective incentives or constraints on third-party recyclers. The nonlinear dynamic reward-penalty mechanism, by dynamically linking reward and penalty intensity to strategy selection, more effectively guides third-party recyclers to improve their processing standards while significantly enhancing manufacturers' recycling willingness, thereby achieving relatively ideal system equilibrium. Originality/value The research incorporates a nonlinear dynamic reward and penalty mechanism within supply chain incentives. The method modulates the severity of penalties based on participants' strategic decisions, promoting stable collaborative partnerships among them.