Programs.

This paper examines the impact of data-driven mechanisms in network freight platforms. The main objective is to understand how these mechanisms can improve operational efficiency and encourage cooperation among key stakeholders, including a risk-neutral shipper, a loss-averse carrier and network freight platform. The study uses evolutionary game theory to model the interactions between these parties. Numerical simulations are conducted to evaluate the effects of initial conditions and important parameters on cooperation. The results show that consistent implementation of data-driven mechanisms fosters stable and honest cooperation. Key factors, such as subsidies, penalties for dishonest behavior, the likelihood of detecting dishonesty, and incentives for honest actions, motivate carriers and shippers to participate in fair transactions. Additionally, specific costs are identified as deterrents to dishonest practices. These findings contribute to our understanding of digital transformation and provide valuable insights for enhancing resilience and collaboration within network freight platforms. The risk appetite can obviously influence the decision of the three parties. The study also highlights important implications for policymakers and industry practitioners, emphasizing the importance of effective data governance and the strategic use of information to shape the future of freight logistics.

本文探讨了网络货运平台（network freight platforms）中数据驱动机制（data-driven mechanisms）的作用效果。本研究的核心目标在于厘清此类机制提升运营效率的路径，以及推动包括风险中性托运人、损失厌恶承运人与网络货运平台在内的核心利益相关方开展协作的方式。研究采用演化博弈论（evolutionary game theory）对上述各方的互动关系进行建模，并通过数值模拟（numerical simulations）评估初始条件与关键参数对合作行为的影响。研究结果表明，持续落地数据驱动机制可促成稳定且诚信的合作格局。补贴、不诚信行为处罚、不诚信行为侦测概率以及诚信行为激励等核心因素，能够驱动承运人与托运人参与公平交易。此外，特定成本可有效抑制不诚信行为的发生。本研究成果有助于深化对数字化转型（digital transformation）的认知，并为提升网络货运平台的抗风险韧性与协作水平提供了极具价值的参考见解。三方的风险偏好显然会对其决策产生显著影响。本研究同时为政策制定者与行业从业者指明了重要实践方向，强调了有效数据治理以及战略性运用信息以塑造货运物流未来的重要性。