IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v175y2023ics0965856423002094.html
   My bibliography  Save this article

Spatial-temporal heterogeneity and built environment nonlinearity in inconsiderate parking of dockless bike-sharing

Author

Listed:
  • Wang, Yacan
  • Li, Jingjing
  • Su, Duan
  • Zhou, Huiyu

Abstract

Although previous studies have shed light on the travel behaviour of dockless bike-sharing (DBS) users, little research focused on their inconsiderate parking behavior. Unlike the travelling behavior, the choice of parking location is closely linked to the different built environments surrounding the parking locations. Therefore, to improve the efficiency of governance, it is vital to explore the parking patterns and heterogeneous influences of the built environment on inconsiderate parking and formulate targeted measures. This paper measures the coordinates of prohibited parking areas in the field to identify inconsiderate parking. Based on big data from Mobike DBS and data on the built environment, the paper empirically analyzes the heterogeneous spatiotemporal distribution patterns of inconsiderate parking with clustering and decision trees. The influencing factors of inconsiderate parking and their nonlinear effects are further analyzed using random forest and partial dependence plots (PDP). The results show that there is significant spatiotemporal heterogeneity in inconsiderate parking, in which different clusters reflect various characteristics of the built environment. Furthermore, marginal effect analysis finds that influencing factors such as riding distance, catering service places, lifestyle services, sports and leisure places, and hotels and hostels have a strong effect on inconsiderate parking behavior, and show nonlinear effects with optimal allocation intervals. Therefore, targeted strategies should be carried out in terms of dynamic temporal adjustment, precise spatial layout, differential management according to time and zone, and cause-assisted administration. The paper’s results provide important decision-making support for inconsiderate parking.

Suggested Citation

  • Wang, Yacan & Li, Jingjing & Su, Duan & Zhou, Huiyu, 2023. "Spatial-temporal heterogeneity and built environment nonlinearity in inconsiderate parking of dockless bike-sharing," Transportation Research Part A: Policy and Practice, Elsevier, vol. 175(C).
    • Handle: RePEc:eee:transa:v:175:y:2023:i:c:s0965856423002094
    DOI: 10.1016/j.tra.2023.103789
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856423002094
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tra.2023.103789?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Liu, Hung-Chi & Lin, Jen-Jia, 2022. "Associations of built environments with spatiotemporal patterns of shared scooter use: A comparison with shared bike use," Transport Policy, Elsevier, vol. 126(C), pages 107-119.
    2. Wang, Yacan & Yang, Ying & Wang, Jiaping & Douglas, Matthew & Su, Duan, 2021. "Examining the influence of social norms on orderly parking behavior of dockless bike-sharing users," Transportation Research Part A: Policy and Practice, Elsevier, vol. 147(C), pages 284-296.
    3. Faghih-Imani, Ahmadreza & Eluru, Naveen, 2016. "Incorporating the impact of spatio-temporal interactions on bicycle sharing system demand: A case study of New York CitiBike system," Journal of Transport Geography, Elsevier, vol. 54(C), pages 218-227.
    4. 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.
    5. Hou, Lei & Wu, Xingguang & Wu, Zhuang & Wu, Shouzhi, 2020. "Pattern identification and risk prediction of domino effect based on data mining methods for accidents occurred in the tank farm," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    6. Zhou, Xiaoyi & Lu, Pan & Zheng, Zijian & Tolliver, Denver & Keramati, Amin, 2020. "Accident Prediction Accuracy Assessment for Highway-Rail Grade Crossings Using Random Forest Algorithm Compared with Decision Tree," Reliability Engineering and System Safety, Elsevier, vol. 200(C).
    7. Ma, Xinwei & Ji, Yanjie & Yuan, Yufei & Van Oort, Niels & Jin, Yuchuan & Hoogendoorn, Serge, 2020. "A comparison in travel patterns and determinants of user demand between docked and dockless bike-sharing systems using multi-sourced data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 139(C), pages 148-173.
    8. Zhang, Yongping & Mi, Zhifu, 2018. "Environmental benefits of bike sharing: A big data-based analysis," Applied Energy, Elsevier, vol. 220(C), pages 296-301.
    9. Faghih-Imani, Ahmadreza & Eluru, Naveen, 2015. "Analysing bicycle-sharing system user destination choice preferences: Chicago’s Divvy system," Journal of Transport Geography, Elsevier, vol. 44(C), pages 53-64.
    10. Liangpeng Gao & Yanjie Ji & Xingchen Yan & Yao Fan & Weihong Guo, 2021. "Incentive measures to avoid the illegal parking of dockless shared bikes: the relationships among incentive forms, intensity and policy compliance," Transportation, Springer, vol. 48(2), pages 1033-1060, April.
    11. Liu, Hung-Chi & Lin, Jen-Jia, 2019. "Associations of built environments with spatiotemporal patterns of public bicycle use," Journal of Transport Geography, Elsevier, vol. 74(C), pages 299-312.
    12. Yanjie Ji & Xinwei Ma & Mingyuan Yang & Yuchuan Jin & Liangpeng Gao, 2018. "Exploring Spatially Varying Influences on Metro-Bikeshare Transfer: A Geographically Weighted Poisson Regression Approach," Sustainability, MDPI, vol. 10(5), pages 1-23, May.
    13. Li, Weibo & Kamargianni, Maria, 2018. "Providing quantified evidence to policy makers for promoting bike-sharing in heavily air-polluted cities: A mode choice model and policy simulation for Taiyuan-China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 277-291.
    14. Zhitao Li & Yuzhen Shang & Guanwei Zhao & Muzhuang Yang, 2022. "Exploring the Multiscale Relationship between the Built Environment and the Metro-Oriented Dockless Bike-Sharing Usage," IJERPH, MDPI, vol. 19(4), pages 1-21, February.
    15. Su, Duan & Wang, Yacan & Yang, Nan & Wang, Xianghong, 2020. "Promoting considerate parking behavior in dockless bike-sharing: An experimental study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 153-165.
    16. Faghih-Imani, Ahmadreza & Eluru, Naveen, 2016. "Determining the role of bicycle sharing system infrastructure installation decision on usage: Case study of montreal BIXI system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 685-698.
    17. Zhang, Ying & Thomas, Tom & Brussel, Mark & van Maarseveen, Martin, 2017. "Exploring the impact of built environment factors on the use of public bikes at bike stations: Case study in Zhongshan, China," Journal of Transport Geography, Elsevier, vol. 58(C), pages 59-70.
    18. Mateo-Babiano, Iderlina & Bean, Richard & Corcoran, Jonathan & Pojani, Dorina, 2016. "How does our natural and built environment affect the use of bicycle sharing?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 295-307.
    19. Noland, Robert B. & Smart, Michael J. & Guo, Ziye, 2016. "Bikeshare trip generation in New York City," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 164-181.
    20. Faghih-Imani, Ahmadreza & Eluru, Naveen & El-Geneidy, Ahmed M. & Rabbat, Michael & Haq, Usama, 2014. "How land-use and urban form impact bicycle flows: evidence from the bicycle-sharing system (BIXI) in Montreal," Journal of Transport Geography, Elsevier, vol. 41(C), pages 306-314.
    21. Xing, Yingying & Wang, Ke & Lu, Jian John, 2020. "Exploring travel patterns and trip purposes of dockless bike-sharing by analyzing massive bike-sharing data in Shanghai, China," Journal of Transport Geography, Elsevier, vol. 87(C).
    22. Wafic El-Assi & Mohamed Salah Mahmoud & Khandker Nurul Habib, 2017. "Effects of built environment and weather on bike sharing demand: a station level analysis of commercial bike sharing in Toronto," Transportation, Springer, vol. 44(3), pages 589-613, May.
    23. Laa, Barbara & Emberger, Günter, 2020. "Bike sharing: Regulatory options for conflicting interests – Case study Vienna," Transport Policy, Elsevier, vol. 98(C), pages 148-157.
    24. Gu, Tianqi & Kim, Inhi & Currie, Graham, 2019. "To be or not to be dockless: Empirical analysis of dockless bikeshare development in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 122-147.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mix, Richard & Hurtubia, Ricardo & Raveau, Sebastián, 2022. "Optimal location of bike-sharing stations: A built environment and accessibility approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 126-142.
    2. Lidong Zhu & Mujahid Ali & Elżbieta Macioszek & Mahdi Aghaabbasi & Amin Jan, 2022. "Approaching Sustainable Bike-Sharing Development: A Systematic Review of the Influence of Built Environment Features on Bike-Sharing Ridership," Sustainability, MDPI, vol. 14(10), pages 1-17, May.
    3. Kumar Dey, Bibhas & Anowar, Sabreena & Eluru, Naveen, 2021. "A framework for estimating bikeshare origin destination flows using a multiple discrete continuous system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 119-133.
    4. Hu, Songhua & Chen, Mingyang & Jiang, Yuan & Sun, Wei & Xiong, Chenfeng, 2022. "Examining factors associated with bike-and-ride (BnR) activities around metro stations in large-scale dockless bikesharing systems," Journal of Transport Geography, Elsevier, vol. 98(C).
    5. De Zhao & Ghim Ping Ong & Wei Wang & Wei Zhou, 2021. "Estimating Public Bicycle Trip Characteristics with Consideration of Built Environment Data," Sustainability, MDPI, vol. 13(2), pages 1-13, January.
    6. Zhan, Zilin & Guo, Yuanyuan & Noland, Robert B. & He, Sylvia Y. & Wang, Yacan, 2023. "Analysis of links between dockless bikeshare and metro trips in Beijing," Transportation Research Part A: Policy and Practice, Elsevier, vol. 175(C).
    7. Wang, Xudong & Cheng, Zhanhong & Trépanier, Martin & Sun, Lijun, 2021. "Modeling bike-sharing demand using a regression model with spatially varying coefficients," Journal of Transport Geography, Elsevier, vol. 93(C).
    8. Morton, Craig & Kelley, Scott & Monsuur, Fredrik & Hui, Tianwen, 2021. "A spatial analysis of demand patterns on a bicycle sharing scheme: Evidence from London," Journal of Transport Geography, Elsevier, vol. 94(C).
    9. Hu, Beibei & Zhong, Zhenfang & Zhang, Yanli & Sun, Yue & Jiang, Li & Dong, Xianlei & Sun, Huijun, 2022. "Understanding the influencing factors of bicycle-sharing demand based on residents’ trips," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
    10. Wang, Kailai & Chen, Yu-Jen, 2020. "Joint analysis of the impacts of built environment on bikeshare station capacity and trip attractions," Journal of Transport Geography, Elsevier, vol. 82(C).
    11. Ying Ni & Jiaqi Chen, 2020. "Exploring the Effects of the Built Environment on Two Transfer Modes for Metros: Dockless Bike Sharing and Taxis," Sustainability, MDPI, vol. 12(5), pages 1-20, March.
    12. Zijia Wang & Lei Cheng & Yongxing Li & Zhiqiang Li, 2020. "Spatiotemporal Characteristics of Bike-Sharing Usage around Rail Transit Stations: Evidence from Beijing, China," Sustainability, MDPI, vol. 12(4), pages 1-19, February.
    13. Liu, Hung-Chi & Lin, Jen-Jia, 2019. "Associations of built environments with spatiotemporal patterns of public bicycle use," Journal of Transport Geography, Elsevier, vol. 74(C), pages 299-312.
    14. Wang, Ruoxuan & Wu, Jianping & Qi, Geqi, 2022. "Exploring regional sustainable commuting patterns based on dockless bike-sharing data and POI data," Journal of Transport Geography, Elsevier, vol. 102(C).
    15. Wang, Kailai & Akar, Gulsah, 2019. "Gender gap generators for bike share ridership: Evidence from Citi Bike system in New York City," Journal of Transport Geography, Elsevier, vol. 76(C), pages 1-9.
    16. Zhao, De & Ong, Ghim Ping & Wang, Wei & Hu, Xiao Jian, 2019. "Effect of built environment on shared bicycle reallocation: A case study on Nanjing, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 128(C), pages 73-88.
    17. Caigang, Zhuang & Shaoying, Li & Zhangzhi, Tan & Feng, Gao & Zhifeng, Wu, 2022. "Nonlinear and threshold effects of traffic condition and built environment on dockless bike sharing at street level," Journal of Transport Geography, Elsevier, vol. 102(C).
    18. Wang, Kailai & Akar, Gulsah & Chen, Yu-Jen, 2018. "Bike sharing differences among Millennials, Gen Xers, and Baby Boomers: Lessons learnt from New York City’s bike share," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 1-14.
    19. Hyland, Michael & Hong, Zihan & Pinto, Helen Karla Ramalho de Farias & Chen, Ying, 2018. "Hybrid cluster-regression approach to model bikeshare station usage," Transportation Research Part A: Policy and Practice, Elsevier, vol. 115(C), pages 71-89.
    20. Tianjian Yang & Ye Li & Simin Zhou & Yu Zhang, 2019. "Dynamic Feedback Analysis of Influencing Factors and Challenges of Dockless Bike-Sharing Sustainability in China," Sustainability, MDPI, vol. 11(17), pages 1-17, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transa:v:175:y:2023:i:c:s0965856423002094. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.