ISSN 0253-2778

CN 34-1054/N

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Open AccessOpen Access JUSTC Management Article

Matching consumers and stage-stations on community group buying platforms: An approach with hierarchy algorithms

Cite this: JUSTC, 2024, 54(11): 1105
https://doi.org/10.52396/JUSTC-2023-0026
CSTR: 32290.14.JUSTC-2023-0026
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  • Author Bio:

    Liyuan Lin received his M.S. degree from the University of Science and Technology of China in 2024. His research mainly focuses on two-sided markets and opaque selling

  • Corresponding author:

    Liyuan Lin, E-mail: xpdilin@mail.ustc.edu.cn

  • Received Date: February 26, 2023
  • Accepted Date: January 16, 2024
  • Motivated by the business model called “community group buying” (CGB), which has emerged in China and some countries in Southeast Asia, such as Singapore and Indonesia, we develop algorithms that could help CGB platforms match consumers with stage-stations (the picking up center under the CGB mode). By altering the fundamental design of the existing hierarchy algorithms, improvements are achieved. It is proven that our method has a faster running speed and greater space efficiency. Our algorithms avoid traversal and compress the time complexities of matching a consumer with a stage-station and updating the storage information to O(logM) and O(MlogG), where M is the number of stage-stations and G is that of the platform’s stock-keeping units. Simulation comparisons of our algorithms with the current methods of CGB platforms show that our approaches can effectively reduce delivery costs. An interesting observation of the simulations is worthy of note: Increasing G may incur higher costs since it makes inventories more dispersed and delivery problems more complicated.

    The fundamental processes of a community group buying platform.

    • We develop algorithms to help community group buying platforms compress the time complexities of matching a consumer with a stage-stations and updating the storage information.
    • With simulations, we make comparisons between our algorithms and the currently usual methods of community group buying platforms and find that our approaches can effectively reduce delivery costs.
    • With more stock keeping uinits, a community group buying platform may bear higher delivery costs.

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    Figure  1.   The closest station being not optimal.

    Figure  2.   The core idea of hierarchy algorithm.

    Figure  3.   The hierarchy of regions.

    Figure  4.   The cubes in the deepest level for M=600.

    Figure  5.   The hierarchy process of G=6.

    Figure  6.   Delivery routes of Warehouses 1 and 2.

    Figure  7.   Delivery routes of Warehouses 3 and 4.

    Figure  8.   The average cost of different pairs of (M, G).

    Figure  9.   Average travel cost under different methods.

    Figure  10.   The new sequence of events.

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