Supply chain data sharing in the era of trusted data spaces: A four-party evolutionary game analysis

With the rapid development of the digital economy, Trusted Data Spaces (TDS) have emerged as a critical infrastructure for enabling secure data circulation and realizing data value co-creation across multi-actor ecosystems. However, due to heterogeneous incentives, high coordination costs, and uncertainty in value distribution, achieving stable and efficient multi-party participation remains a key challenge. This study develops a four-party evolutionary game model involving the TDS operator, data service provider, data provider, and data user to analyze the dynamic evolution of strategic interactions and the conditions under which stable equilibria emerge. Differing from existing literature that mainly focuses on bilateral or tripartite frameworks, this study constructs a comprehensive multi-actor evolutionary system that incorporates government incentives, platform governance mechanisms, supply chain collaboration benefits, supply chain finance enhancement effects, and value co-creation mechanisms. The results show that: (1) The TDS operator plays a foundational role in system stabilization, and its sustainable operation depends on whether institutional incentives and governance-related benefits can offset the costs of trusted infrastructure construction; (2) The data service provider primarily affects the convergence speed of the system by enhancing data governance, standardization, and secure circulation capabilities, rather than altering the final equilibrium outcome; (3) The coordinated participation of data providers and data users is the core driver of value realization, and their strategic choices are jointly influenced by government incentives, platform governance, risk exposure, and value co-creation returns; (4) The system exhibits multiple equilibrium states and strong path dependence, while value co-creation benefits gradually evolve into an endogenous mechanism driving long-term stability; (5) Sensitivity analysis further indicates that increasing value co-creation benefits significantly accelerates convergence toward the ideal equilibrium, whereas incentive distribution mainly affects evolutionary speed rather than equilibrium structure. Overall, the findings provide a systematic understanding of multi-actor behavioral dynamics in TDS and offer theoretical and practical insights for designing sustainable governance mechanisms that promote secure data sharing and value co-creation in the digital economy.