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Modeling spatio-temporal diffusion of carsharing membership in Québec City

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  • Coll, Marie-Hélène
  • Vandersmissen, Marie-Hélène
  • Thériault, Marius

Abstract

During the last few years, car sharing has undergone significant growth, both in Canada and around the world. In this type of service, users share access to a fleet of vehicles, thereby giving them most of the advantages of automobile use, such as its temporal and spatial flexibility, without many of the constraints of ownership. This study analyzes the geographical and socio-economic factors that favour membership of a carsharing service in Québec City. We combined Cervero’s and Kockelman’s 5D model (density, diversity, design, distance to transit, and destination accessibility) with Hägerstrand’s concept of innovation diffusion so as to analyze the evolution of potential car-sharing membership. Zero-inflated negative binomial (ZINB) regression was used to model the spatial diffusion of the number of car-sharing members in Québec City from 1996 (two years after its inauguration) to 2008 at the local scale, with an annual time step. Results indicate that the carsharing distribution did, indeed, follow Hägerstrand’s innovation diffusion model and that, even though some of the 5D model significantly influenced membership, it was socio-economic factors (education, non-motorization, and family structure) that most greatly affected the membership rate in the service area. The model is used to assess and discuss market coverage potential in Québec City.

Suggested Citation

  • Coll, Marie-Hélène & Vandersmissen, Marie-Hélène & Thériault, Marius, 2014. "Modeling spatio-temporal diffusion of carsharing membership in Québec City," Journal of Transport Geography, Elsevier, vol. 38(C), pages 22-37.
    • Handle: RePEc:eee:jotrge:v:38:y:2014:i:c:p:22-37
    DOI: 10.1016/j.jtrangeo.2014.04.017
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    3. Jin, Fanglei & Yao, Enjian & An, Kun, 2020. "Analysis of the potential demand for battery electric vehicle sharing: Mode share and spatiotemporal distribution," Journal of Transport Geography, Elsevier, vol. 82(C).
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    5. Qiuyue Sai & Jun Bi & Dongfan Xie & Wei Guan, 2019. "Identifying and Predicting the Expenditure Level Characteristics of Car-Sharing Users Based on the Empirical Data," Sustainability, MDPI, vol. 11(23), pages 1-21, November.
    6. Coenegrachts, Elnert & Vanelslander, Thierry & Verhetsel, Ann & Beckers, Joris, 2024. "Analyzing shared mobility markets in Europe: A comparative analysis of shared mobility schemes across 311 European cities," Journal of Transport Geography, Elsevier, vol. 118(C).
    7. Felipe F. Dias & Patrícia S. Lavieri & Venu M. Garikapati & Sebastian Astroza & Ram M. Pendyala & Chandra R. Bhat, 2017. "A behavioral choice model of the use of car-sharing and ride-sourcing services," Transportation, Springer, vol. 44(6), pages 1307-1323, November.
    8. Vinayak, Pragun & Dias, Felipe F. & Astroza, Sebastian & Bhat, Chandra R. & Pendyala, Ram M. & Garikapati, Venu M., 2018. "Accounting for multi-dimensional dependencies among decision-makers within a generalized model framework: An application to understanding shared mobility service usage levels," Transport Policy, Elsevier, vol. 72(C), pages 129-137.
    9. Shichao Sun & Yuanqian Liu & Yukun Yao & Zhengyu Duan & Xiaokun Wang, 2021. "The Determinants to Promote College Students’ Use of Car-Sharing: An Empirical Study at Dalian Maritime University, China," Sustainability, MDPI, vol. 13(12), pages 1-12, June.
    10. Cen Zhang & Jan-Dirk Schmöcker & Martin Trépanier, 2022. "Latent stage model for carsharing usage frequency estimation with Montréal case study," Transportation, Springer, vol. 49(1), pages 185-211, February.
    11. Zu, Jinyan & Kong, Hui & Xu, Yang & Zhang, Xiaohu, 2024. "Carsharing in China: Impact of system and urban factors on usage and efficiency," Journal of Transport Geography, Elsevier, vol. 117(C).
    12. Rotaris, Lucia & Danielis, Romeo, 2018. "The role for carsharing in medium to small-sized towns and in less-densely populated rural areas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 115(C), pages 49-62.
    13. Maria Juschten & Timo Ohnmacht & Vu Thi Thao & Regine Gerike & Reinhard Hössinger, 2019. "Carsharing in Switzerland: identifying new markets by predicting membership based on data on supply and demand," Transportation, Springer, vol. 46(4), pages 1171-1194, August.
    14. Zhou, Tianli & Fields, Evan & Osorio, Carolina, 2023. "A data-driven discrete simulation-based optimization algorithm for car-sharing service design," Transportation Research Part B: Methodological, Elsevier, vol. 178(C).
    15. Riccardo Ceccato & Marco Diana, 2021. "Substitution and complementarity patterns between traditional transport means and car sharing: a person and trip level analysis," Transportation, Springer, vol. 48(4), pages 1523-1540, August.
    16. Yoon-Young Chun & Mitsutaka Matsumoto & Kiyotaka Tahara & Kenichiro Chinen & Hideki Endo, 2019. "Exploring Factors Affecting Car Sharing Use Intention in the Southeast-Asia Region: A Case Study in Java, Indonesia," Sustainability, MDPI, vol. 11(18), pages 1-26, September.
    17. Rotaris, Lucia & Danielis, Romeo & Maltese, Ila, 2019. "Carsharing use by college students: The case of Milan and Rome," Transportation Research Part A: Policy and Practice, Elsevier, vol. 120(C), pages 239-251.

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