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Impact-Asymmetric Analysis of Bike-Sharing Residents’ Satisfaction: A Case Study of Harbin, China

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  • Lixuan Zhao

    (College of Landscape Architecture, Northeast Forestry University, Harbin 150040, China)

  • Dewei Fang

    (College of Landscape Architecture, Northeast Forestry University, Harbin 150040, China)

  • Yang Cao

    (Academic Affairs Office, Northeast Forestry University, Harbin 150040, China)

  • Shan Sun

    (School of Architecture and Urban Planning, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Liu Han

    (College of Landscape Architecture, Northeast Forestry University, Harbin 150040, China)

  • Yang Xue

    (Society Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511400, China)

  • Qian Zheng

    (CAUPD Beijing Planning and Design Consultants Co., Ltd., Hainan Branch, Haikou 570100, China)

Abstract

Harbin, China, has a large population density and a large number of motor vehicles. To alleviate traffic congestion, based on the survey data of bike-sharing riders in the new and old urban areas of Harbin in May 2022, this paper uses an impact-asymmetric analysis and gradient enhancement decision tree to analyse the asymmetric relationship between bike-sharing travel environment elements and cyclists’ satisfaction, and the optimisation strategy for the bike-sharing riding environment was obtained so that more residents can choose to ride. This research shows that the infrastructure of the motorway in the old urban area had the greatest impact on the overall satisfaction, while the travel quality of the shared bikes in the new urban area had the greatest impact on the overall satisfaction. In addition, due to the differences in urban environments and satisfaction, planning directions are different when satisfying cyclists in the new and old urban areas. The old urban area should emphasise cycling comfort and road coherence to provide a good travel environment; however, the new urban area should focus on the operation of shared bikes to meet the needs of cyclists. Therefore, future research should formulate refined improvement strategies for different regions.

Suggested Citation

  • Lixuan Zhao & Dewei Fang & Yang Cao & Shan Sun & Liu Han & Yang Xue & Qian Zheng, 2023. "Impact-Asymmetric Analysis of Bike-Sharing Residents’ Satisfaction: A Case Study of Harbin, China," Sustainability, MDPI, vol. 15(2), pages 1-19, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:2:p:1670-:d:1036464
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    References listed on IDEAS

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    1. Kurt Matzler & Elmar Sauerwein & Kenneth Heischmidt, 2003. "Importance-performance analysis revisited: the role of the factor structure of customer satisfaction," The Service Industries Journal, Taylor & Francis Journals, vol. 23(2), pages 112-129, March.
    2. Ding, Chuan & Cao, Xinyu (Jason) & Næss, Petter, 2018. "Applying gradient boosting decision trees to examine non-linear effects of the built environment on driving distance in Oslo," Transportation Research Part A: Policy and Practice, Elsevier, vol. 110(C), pages 107-117.
    3. Jiachen Li & Mengqing Ma & Xin Xia & Wenhui Ren, 2021. "The Spatial Effect of Shared Mobility on Urban Traffic Congestion: Evidence from Chinese Cities," Sustainability, MDPI, vol. 13(24), pages 1-19, December.
    4. Tao, Tao & Wang, Jueyu & Cao, Xinyu, 2020. "Exploring the non-linear associations between spatial attributes and walking distance to transit," Journal of Transport Geography, Elsevier, vol. 82(C).
    5. Meghan Winters & Gavin Davidson & Diana Kao & Kay Teschke, 2011. "Motivators and deterrents of bicycling: comparing influences on decisions to ride," Transportation, Springer, vol. 38(1), pages 153-168, January.
    6. Yanyong Guo & Jibiao Zhou & Yao Wu & Zhibin Li, 2017. "Identifying the factors affecting bike-sharing usage and degree of satisfaction in Ningbo, China," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-19, September.
    7. Elżbieta Macioszek & Maria Cieśla, 2022. "External Environmental Analysis for Sustainable Bike-Sharing System Development," Energies, MDPI, vol. 15(3), pages 1-22, January.
    8. Shao, Qifan & Zhang, Wenjia & Cao, Xinyu & Yang, Jiawen & Yin, Jie, 2020. "Threshold and moderating effects of land use on metro ridership in Shenzhen: Implications for TOD planning," Journal of Transport Geography, Elsevier, vol. 89(C).
    9. Ipek Sener & Naveen Eluru & Chandra Bhat, 2009. "An analysis of bicycle route choice preferences in Texas, US," Transportation, Springer, vol. 36(5), pages 511-539, September.
    10. Michael Hardinghaus & Panagiotis Papantoniou, 2020. "Evaluating Cyclists’ Route Preferences with Respect to Infrastructure," Sustainability, MDPI, vol. 12(8), pages 1-18, April.
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    1. Jiayu Bao & Guojun Chen & Zhenghua Liu, 2023. "Exploring the Influence of Parking Penalties on Bike-Sharing System with Willingness Constraints: A Case Study of Beijing, China," Sustainability, MDPI, vol. 15(16), pages 1-19, August.

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