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On-Demand Meal Delivery Platforms: Operational Level Data and Research Opportunities

Author

Listed:
  • Wenzheng Mao

    (Advanced Institute of Business, Tongji University, Shanghai 200082, China)

  • Liu Ming

    (School of Management and Economics, The Chinese University of Hong Kong, Shenzhen 518172, China)

  • Ying Rong

    (Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai 200030, China)

  • Christopher S. Tang

    (Anderson School of Management, University of California, Los Angeles, Los Angeles, California 90095)

  • Huan Zheng

    (Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai 200030, China)

Abstract

This paper describes the operations of most on-demand meal delivery platforms and discusses how empirical research can improve the operational performance of these platforms. To support and encourage more studies on the operations of on-demand delivery platforms, we provide a unique data set obtained from a meal delivery platform in China. This data set contains operational level data sampled from July 1 to August 31, 2015, in Hangzhou, China. The data set includes information about order placements, order deliveries, restaurants, drivers, weather and traffic conditions, and so on. We also review recent studies on meal delivery platforms and suggest research opportunities for improving delivery performance.

Suggested Citation

  • Wenzheng Mao & Liu Ming & Ying Rong & Christopher S. Tang & Huan Zheng, 2022. "On-Demand Meal Delivery Platforms: Operational Level Data and Research Opportunities," Manufacturing & Service Operations Management, INFORMS, vol. 24(5), pages 2535-2542, September.
    • Handle: RePEc:inm:ormsom:v:24:y:2022:i:5:p:2535-2542
    DOI: 10.1287/msom.2022.1112
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