Evolutionary Game Analysis of the Agricultural Product Cold Chain Logistics Digital Service Ecosystem in a Digital Context

Juan Yang, Fenghua Xiao and Haorui Liu

Discrete Dynamics in Nature and Society, 2026, vol. 2026, 1-16

Abstract: The development of a digital service ecosystem for agricultural cold chain logistics relies fundamentally on effective coordination among multiple stakeholders. Drawing on service ecosystem theory, this study constructs a tripartite evolutionary game model involving farmers, agricultural digital service platforms, and cold chain logistics enterprises, while incorporating government intervention as an exogenous regulatory mechanism through subsidies, penalties, and reputation constraints. By deriving replicator dynamic equations and conducting stability analysis, this study identifies the evolutionary stability conditions of the system. Furthermore, numerical simulations are performed to examine the dynamic impacts of key parameters on strategic evolution. The results indicate that the system exhibits two distinct types of stable equilibria: a Pareto-inferior equilibrium characterized by platform opportunistic behavior and a Pareto-optimal equilibrium characterized by full cooperation among all agents. The evolutionary outcome is primarily determined by the comparison between the platform’s cooperative returns and its opportunistic gains. Sensitivity analysis further reveals that increases in platform cooperative returns, government penalties, and reputation losses significantly promote cooperative behavior, whereas higher cooperation costs and excess opportunistic gains tend to drive the system toward noncooperative equilibrium. These findings highlight the pivotal role of platform incentives and institutional regulation in shaping the evolution of the digital service ecosystem. Based on the results, this study proposes policy implications, including the implementation of tiered penalty mechanisms, dynamic subsidy schemes, and reputation-based governance, as well as measures to reduce farmers’ participation costs. These policy tools are essential for promoting multiagent collaboration and facilitating the transition toward a Pareto-optimal equilibrium.

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnddns:3367548

DOI: 10.1155/ddns/3367548

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