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Research on Multicriteria Decision-Making Scheme of High-Speed Railway Express Product Pricing and Slot Allocation under Competitive Conditions

Author

Listed:
  • Yuxuan Fang

    (Department of Logistics Engineering, School of Traffic and Transportation, Beijing Jiaotong University, Shangyuan Cun, Haidian District, Beijing 100044, China)

  • Xiaodong Zhang

    (Department of Logistics Engineering, School of Traffic and Transportation, Beijing Jiaotong University, Shangyuan Cun, Haidian District, Beijing 100044, China)

  • Yueyi Li

    (Department of Logistics Engineering, School of Traffic and Transportation, Beijing Jiaotong University, Shangyuan Cun, Haidian District, Beijing 100044, China)

Abstract

Scientifically and reasonably pricing products and allocating slots are key to improving the profitability and competitiveness of high-speed railway expresses. In this research, we focus on the freight transportation pricing and slot allocation of high-speed railway express companies in a competitive environment. The goals of this research are to make decisions on the pricing and slot allocation schemes of the high-speed railway express between sections through the method of multicriteria decision making, and then to test these changes in reality. This research innovatively takes the high-speed freight Electric Multiple Unit (EMU) train as its research object and innovatively applies the revenue management theory to high-speed railway express research in a competitive environment, proposing a comprehensive decision-making model based on the sharing rate model. The results show that, by adopting the scheme proposed in this research, the income of high-speed railway express companies can be increased by 13.6%. In addition, the method proposed in this research also enriches the current theory on high-speed railway freight transportation, providing strategies for companies to expand their market and increase profit.

Suggested Citation

  • Yuxuan Fang & Xiaodong Zhang & Yueyi Li, 2022. "Research on Multicriteria Decision-Making Scheme of High-Speed Railway Express Product Pricing and Slot Allocation under Competitive Conditions," Mathematics, MDPI, vol. 10(9), pages 1-11, May.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:9:p:1610-:d:811473
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    References listed on IDEAS

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    1. Keaton, Mark H., 1989. "Designing optimal railroad operating plans: Lagrangian relaxation and heuristic approaches," Transportation Research Part B: Methodological, Elsevier, vol. 23(6), pages 415-431, December.
    2. Kyparisis, George J. & Koulamas, Christos, 2018. "Optimal pricing and seat allocation for a two-cabin airline revenue management problem," International Journal of Production Economics, Elsevier, vol. 201(C), pages 18-25.
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