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Finding Factors that Influence Carsharing Usage: Case Study in Seoul

Author

Listed:
  • Junhee Kang

    (Department of Urban Design and Planning, Hongik University, 94 Wausan-ro, Mapo-gu, Seoul 121–791, Korea)

  • Keeyeon Hwang

    (Department of Urban Design and Planning, Hongik University, 94 Wausan-ro, Mapo-gu, Seoul 121–791, Korea)

  • Sungjin Park

    (Department of Urban Design and Planning, Hongik University, 94 Wausan-ro, Mapo-gu, Seoul 121–791, Korea)

Abstract

The goal of this research is to investigate the factors that affect carsharing demand. As a proxy for carsharing demand, the number of (booking) transactions made by carsharing users is counted based on the data from one of the two major carsharing operators in Seoul, Korea. In order to identify the factors influencing station-based carsharing usage, multiple linear regression modeling was performed with the number of carsharing transactions as a dependent variable and with the three groups of independent variables: Built environment, demographic, and transportation variables. Instead of using the locations of the pods, this study uses the residential locations of carsharing users who made transactions, and the final result analyzing 420 districts shows that six variables significantly influence carsharing usage. Carsharing demand is high in an area where a higher proportion of building floor area is used for business, and which has a higher proportion of young residents in their 20s and 30s. It can also be predicted that the area with more registered cars and less subway entrances will show higher carsharing demand. The analysis result also suggests that providing additional carsharing pods, especially pods that utilize city owned public parking facilities, will help promote carsharing usage. This research establishes a basis for future research efforts to forecast carsharing demand and to identify areas with high potential, especially in major Asian cities.

Suggested Citation

  • Junhee Kang & Keeyeon Hwang & Sungjin Park, 2016. "Finding Factors that Influence Carsharing Usage: Case Study in Seoul," Sustainability, MDPI, vol. 8(8), pages 1-12, July.
  • Handle: RePEc:gam:jsusta:v:8:y:2016:i:8:p:709-:d:74691
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    References listed on IDEAS

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    Cited by:

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    2. Johannes Müller & Gonçalo Homem de Almeida Correia & Klaus Bogenberger, 2017. "An Explanatory Model Approach for the Spatial Distribution of Free-Floating Carsharing Bookings: A Case-Study of German Cities," Sustainability, MDPI, vol. 9(7), pages 1-17, July.
    3. Helena Dall Pizzol & Stefânia Ordovás de Almeida & Mauren Do Couto Soares, 2017. "Collaborative Consumption: A Proposed Scale for Measuring the Construct Applied to a Carsharing Setting," Sustainability, MDPI, vol. 9(5), pages 1-16, April.
    4. Guowei Zhu & Hongshan Li & Li Zhou, 2018. "Enhancing the development of sharing economy to mitigate the carbon emission: a case study of online ride-hailing development in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 91(2), pages 611-633, March.
    5. Jingjing Jia & Shujie Ma & Yixi Xue & Deyang Kong, 2020. "Life-Cycle Break-Even Analysis of Electric Carsharing: A Comparative Study in China," Sustainability, MDPI, vol. 12(16), pages 1-29, August.
    6. Haitao Yu & Zhong-Ren Peng, 2020. "The impacts of built environment on ridesourcing demand: A neighbourhood level analysis in Austin, Texas," Urban Studies, Urban Studies Journal Limited, vol. 57(1), pages 152-175, January.
    7. Repoux, Martin & Kaspi, Mor & Boyacı, Burak & Geroliminis, Nikolas, 2019. "Dynamic prediction-based relocation policies in one-way station-based carsharing systems with complete journey reservations," Transportation Research Part B: Methodological, Elsevier, vol. 130(C), pages 82-104.
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