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<p>Vehicle–Road–Cloud (VRC) integration is a key pathway toward intelligent and connected transportation systems, where data sharing and platform empowerment enable cross-domain collaboration. However, ecological cooperation in VRC ecosystems is often hindered by data security risks, asymmetric cost–benefit structures, and bounded rationality of heterogeneous stakeholders. Existing studies rarely examine how subjective value perception and risk attitudes shape cooperative strategy evolution in such data-driven systems. This study develops a three-party evolutionary game model involving ICV manufacturers, cloud-control platform service providers, and the government. Prospect theory is incorporated to capture behavioral preferences under uncertainty, and a government dynamic subsidy mechanism is introduced to analyze regulatory incentives. Replicator dynamics and numerical simulations are employed to examine the effects of data value conversion efficiency, data sharing intensity, data protection level, and risk costs. The results indicate that dynamic government subsidies can effectively promote ecological cooperation, while higher data value conversion efficiency, stronger data protection, and greater data sharing intensity significantly enhance firms’ willingness to cooperate. In contrast, elevated data-related risk costs substantially inhibit cooperative behavior, with more pronounced effects on ICV manufacturers. This study provides behavioral insights into multi-agent coordination in Vehicle–Road–Cloud integration and offers policy and managerial implications for fostering sustainable cooperation in intelligent transportation ecosystems.</p>

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Data sharing and platform empowerment in vehicle–road–cloud integration: a prospect theory based evolutionary game analysis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月19日

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  • Huiyan Liu,
  • Yiming Chen,
  • Jinhuan Tang,
  • Haiyan Lan,
  • Wenbo Zhang,
  • Zhen Li

摘要

Vehicle–Road–Cloud (VRC) integration is a key pathway toward intelligent and connected transportation systems, where data sharing and platform empowerment enable cross-domain collaboration. However, ecological cooperation in VRC ecosystems is often hindered by data security risks, asymmetric cost–benefit structures, and bounded rationality of heterogeneous stakeholders. Existing studies rarely examine how subjective value perception and risk attitudes shape cooperative strategy evolution in such data-driven systems. This study develops a three-party evolutionary game model involving ICV manufacturers, cloud-control platform service providers, and the government. Prospect theory is incorporated to capture behavioral preferences under uncertainty, and a government dynamic subsidy mechanism is introduced to analyze regulatory incentives. Replicator dynamics and numerical simulations are employed to examine the effects of data value conversion efficiency, data sharing intensity, data protection level, and risk costs. The results indicate that dynamic government subsidies can effectively promote ecological cooperation, while higher data value conversion efficiency, stronger data protection, and greater data sharing intensity significantly enhance firms’ willingness to cooperate. In contrast, elevated data-related risk costs substantially inhibit cooperative behavior, with more pronounced effects on ICV manufacturers. This study provides behavioral insights into multi-agent coordination in Vehicle–Road–Cloud integration and offers policy and managerial implications for fostering sustainable cooperation in intelligent transportation ecosystems.