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Data-driven mechanisms for network freight platforms: An evolutionary game perspective.

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  • 1Business School, Shanghai Dianji University, Pudong, Shanghai, China.

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This summary is machine-generated.

Data-driven mechanisms in freight platforms promote honest cooperation between shippers and carriers. Consistent implementation, supported by incentives and penalties, enhances operational efficiency and platform resilience.

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Area of Science:

  • Logistics and Supply Chain Management
  • Operations Research
  • Behavioral Economics

Background:

  • Network freight platforms face challenges in coordinating diverse stakeholders.
  • Operational efficiency and cooperation are crucial for platform success.
  • Digital transformation offers opportunities for improved logistics.

Purpose of the Study:

  • To analyze the impact of data-driven mechanisms on cooperation in freight platforms.
  • To understand how these mechanisms improve operational efficiency.
  • To identify factors influencing stakeholder behavior (shipper, carrier, platform).

Main Methods:

  • Evolutionary game theory modeling.
  • Numerical simulations to test various parameters.
  • Analysis of risk-neutral and loss-averse behaviors.

Main Results:

  • Consistent data-driven mechanisms lead to stable, honest cooperation.
  • Subsidies, penalties, detection likelihood, and incentives are key motivators.
  • Specific costs deter dishonest practices.
  • Risk appetite significantly influences stakeholder decisions.

Conclusions:

  • Data-driven mechanisms are vital for fostering trust and collaboration in freight logistics.
  • Effective data governance and strategic information use are essential for platform resilience.
  • Findings offer practical insights for policymakers and industry practitioners.