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What travel scenarios are the opportunities of car sharing?

Author

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  • Yan Xu
  • Xuehong Ji
  • Ziniu Jin

Abstract

In face of high-investment and low-revenue crisis, it is critical for new-born car-sharing companies to focus on niche market. Existing literatures have already discussed the niche market of car sharing based on people’s irregular travel demands and scenarios; however, current research findings are still lack of adequate travel data support. Aiming to solve this problem, we develop a travel scenarios mining method that first define land usage types of travel Origin-Destination (OD) locations using spatial clustering analysis of city’s Points of interests (POI) data, and then discover the most representative travel scenarios using association rules mining method with car-sharing records data. Applying this approach to the car-sharing service case in Beijing, China, we find that: day-time business trips and evening entertainment trips around the city centre, commuting trips in off-peak time, and short-distance city travel for tourism are three travel scenarios suitable for car sharing’s niche in the initial stage of market entering. Furthermore, spatio-temporal consumption profiles and competitive advantages of car sharing in the three travel scenarios are analyzed. Finally, theoretical and managerial implications are discussed. In this study, we address the question of finding niche market and suggest that it is critical for car sharing industry treading through the crisis in the early stage of development.

Suggested Citation

  • Yan Xu & Xuehong Ji & Ziniu Jin, 2021. "What travel scenarios are the opportunities of car sharing?," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-22, December.
  • Handle: RePEc:plo:pone00:0260605
    DOI: 10.1371/journal.pone.0260605
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    References listed on IDEAS

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    1. Hu, Beibei & Sun, Yue & Li, Zixun & Zhang, Yanli & Sun, Huijun & Dong, Xianlei, 2024. "Competitive advantage of car-sharing based on travel costs comparison model: A case study of Beijing, China," Research in Transportation Economics, Elsevier, vol. 103(C).

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