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How does dockless bike sharing serve users in Nanjing, China? User surveys vs. trip records

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Abstract
Dockless bike sharing (DBS), as an emerging bike sharing scheme, effectively promotes active travel and improves the mobility of users. Travel behavior analysis of DBS users is a key basis of service improvement, and the data sources include user surveys and trip records. User surveys are widely applied but have the drawback of perceptual errors. Thus, there is a compelling need for exploring travel behavior using automatically-collected trip records. This study examines DBS users' travel frequency and purpose with five semi-annual user surveys and trip record data in Nanjing, China. User surveys reflect user perception of travel behavior, while trip records can be used to calculate actual travel frequency and infer travel purpose. The results show that perceptual travel frequency based on user surveys has a central tendency, and actual travel frequency based on trip records follows a heavy-tailed distribution. Older people tend to underestimate their travel frequency, but other age groups tend to overestimate their frequency. In addition, a dockless bike sharing's travel purpose inferring (DBS-TPI) model is proposed to infer the travel purpose based on trip record data and points of interest data. The DBS-TPI model is reliable and transferable under different scenarios, which could complement user surveys. This study provides insights into improving data collection for better understanding of travel behaviors among DBS users.
Keywords
Tourism, Leisure and Hospitality Management, Management Science and Operations Research, Strategy and Management, Business and International Management, General Decision Sciences, Economics, Econometrics and Finance (miscellaneous), Transportation

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MLA
Hua, Mingzhuang, et al. “How Does Dockless Bike Sharing Serve Users in Nanjing, China? User Surveys vs. Trip Records.” RESEARCH IN TRANSPORTATION BUSINESS AND MANAGEMENT, vol. 43, 2022, doi:10.1016/j.rtbm.2021.100701.
APA
Hua, M., Chen, X., Chen, J., Cheng, L., & Lei, D. (2022). How does dockless bike sharing serve users in Nanjing, China? User surveys vs. trip records. RESEARCH IN TRANSPORTATION BUSINESS AND MANAGEMENT, 43. https://doi.org/10.1016/j.rtbm.2021.100701
Chicago author-date
Hua, Mingzhuang, Xuewu Chen, Jingxu Chen, Long Cheng, and Da Lei. 2022. “How Does Dockless Bike Sharing Serve Users in Nanjing, China? User Surveys vs. Trip Records.” RESEARCH IN TRANSPORTATION BUSINESS AND MANAGEMENT 43. https://doi.org/10.1016/j.rtbm.2021.100701.
Chicago author-date (all authors)
Hua, Mingzhuang, Xuewu Chen, Jingxu Chen, Long Cheng, and Da Lei. 2022. “How Does Dockless Bike Sharing Serve Users in Nanjing, China? User Surveys vs. Trip Records.” RESEARCH IN TRANSPORTATION BUSINESS AND MANAGEMENT 43. doi:10.1016/j.rtbm.2021.100701.
Vancouver
1.
Hua M, Chen X, Chen J, Cheng L, Lei D. How does dockless bike sharing serve users in Nanjing, China? User surveys vs. trip records. RESEARCH IN TRANSPORTATION BUSINESS AND MANAGEMENT. 2022;43.
IEEE
[1]
M. Hua, X. Chen, J. Chen, L. Cheng, and D. Lei, “How does dockless bike sharing serve users in Nanjing, China? User surveys vs. trip records,” RESEARCH IN TRANSPORTATION BUSINESS AND MANAGEMENT, vol. 43, 2022.
@article{8717155,
  abstract     = {{Dockless bike sharing (DBS), as an emerging bike sharing scheme, effectively promotes active travel and improves the mobility of users. Travel behavior analysis of DBS users is a key basis of service improvement, and the data sources include user surveys and trip records. User surveys are widely applied but have the drawback of perceptual errors. Thus, there is a compelling need for exploring travel behavior using automatically-collected trip records. This study examines DBS users' travel frequency and purpose with five semi-annual user surveys and trip record data in Nanjing, China. User surveys reflect user perception of travel behavior, while trip records can be used to calculate actual travel frequency and infer travel purpose. The results show that perceptual travel frequency based on user surveys has a central tendency, and actual travel frequency based on trip records follows a heavy-tailed distribution. Older people tend to underestimate their travel frequency, but other age groups tend to overestimate their frequency. In addition, a dockless bike sharing's travel purpose inferring (DBS-TPI) model is proposed to infer the travel purpose based on trip record data and points of interest data. The DBS-TPI model is reliable and transferable under different scenarios, which could complement user surveys. This study provides insights into improving data collection for better understanding of travel behaviors among DBS users.}},
  articleno    = {{100701}},
  author       = {{Hua, Mingzhuang and Chen, Xuewu and Chen, Jingxu and Cheng, Long and Lei, Da}},
  issn         = {{2210-5395}},
  journal      = {{RESEARCH IN TRANSPORTATION BUSINESS AND MANAGEMENT}},
  keywords     = {{Tourism,Leisure and Hospitality Management,Management Science and Operations Research,Strategy and Management,Business and International Management,General Decision Sciences,Economics,Econometrics and Finance (miscellaneous),Transportation}},
  language     = {{eng}},
  pages        = {{10}},
  title        = {{How does dockless bike sharing serve users in Nanjing, China? User surveys vs. trip records}},
  url          = {{http://dx.doi.org/10.1016/j.rtbm.2021.100701}},
  volume       = {{43}},
  year         = {{2022}},
}

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