| 三方博弈视角下的拼车运营协同优化策略 |
| Collaborative optimization strategy for ridepooling operations from a tripartite game perspective |
| 摘要点击 5 全文点击 0 投稿时间：2023-11-06 修订日期：2025-08-03 |
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| 中文关键词 拼车匹配、拼车定价、博弈、协同优化 |
| 英文关键词 Ridepool matching, ridepool pricing, gaming, collaborative optimization |
| 基金项目 |
| 投稿方向 |
| 作者 | 单位 | 邮编 | | 袁鹏程* | 上海理工大学 管理学院 | 200093 | | 李佶霖 | 上海理工大学 管理学院 | | | 张涛 | 中国石油大学（华东） 经济与管理学院 | |
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| 中文摘要 |
| 现有的拼车运营主要依赖于平台的单方决策,~不利于提升拼车成功率.本文将拼车管理平台、司机和乘客的决策纳入拼车运营管理分析过程,通过引入``服务质量'评价指标,拓展了各方的决策空间,提出了三方博弈视角下的协同决策机制,构建了三方博弈视角下的拼车匹配与定价的协同优化模型,并给出相应的求解方法.通过算例对模型及算法的有效性进行了仿真验证.~结果表明,~所构建的模型在无论在平均利润、乘客平均效用、车辆平均匹配率以及乘客平均匹配率等方面均显著优于其他模型,充分展示了基于三方博弈视角的拼车决策机制的优势;不考虑其他拼车参与方决策过程, 各参与方完全独立条件下的拼车决策机制将是一个最差的决策机制. |
| 英文摘要 |
| Current ridepooling operations primarily depend on unilateral decision-making by platforms, which hinders the improvement of matching success rates. This paper incorporates the decision-making processes of ride-sharing platforms, drivers, and passengers into the operational management analysis framework. By introducing a ``service quality' evaluation index, we expand the decision-making scope for all shareholders. Specifically, we propose a collaborative decision-making mechanism from a tripartite game perspective that considers interactions among platforms, drivers, and passengers. Furthermore, we construct a collaborative optimization model for ride matching and pricing under this tripartite framework and develop corresponding solution methodologies. Simulation results demonstrate the proposed model significantly outperforms others in average profit, passenger utility, vehicle-passenger matching rates, highlighting the advantages of the tripartite game perspective. Independent decision-making without considering other participants yields the worst outcomes. |
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