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Research on Passenger Clustering Based on Shopping Behavior During High-Speed Rail Journeys

Author

Listed:
  • XingYu Su

    (Beijing Jiaotong University)

  • XinSheng Ke

    (Beijing Jiaotong University)

  • Hongquan Ren

    (Beijing-Shanghai High Speed Railway Co., Ltd.)

  • Qiao Li

    (Beijing-Shanghai High Speed Railway Co., Ltd.)

  • Jianqiu Huang

    (Beijing-Shanghai High Speed Railway Co., Ltd.)

  • Yina Li

    (Beijing-Shanghai High Speed Railway Co., Ltd.)

  • Qingrui Meng

    (Beijing Jiaotong University)

  • Ping Yin

    (Beijing Jiaotong University)

Abstract

High-speed rail has become a preferred mode of transportation for many people today, making it crucial to provide targeted shopping services at stations and on board. However, most research on transportation shopping services focuses on airports, with few studies addressing shopping services in the context of high-speed rail. This study employs subspace clustering to segment target populations. The results indicate that the four identified groups differ in high-speed rail shopping intentions, behavior characteristics, and demographic features. Based on hypothesis testing, we analyzed and summarized potential characteristics and patterns influencing passengers’ shopping intentions during high-speed rail journeys. These findings can help high-speed rail operators develop customized marketing strategies for different passenger groups.

Suggested Citation

  • XingYu Su & XinSheng Ke & Hongquan Ren & Qiao Li & Jianqiu Huang & Yina Li & Qingrui Meng & Ping Yin, 2025. "Research on Passenger Clustering Based on Shopping Behavior During High-Speed Rail Journeys," Lecture Notes in Operations Research,, Springer.
    • Handle: RePEc:spr:lnopch:978-981-96-9697-0_39
    DOI: 10.1007/978-981-96-9697-0_39
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