IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v604y2022ics0378437122005544.html
   My bibliography  Save this article

A study on the trip behavior of shared bicycles and shared electric bikes in Chinese universities based on NL model—Henan Polytechnic University as an example

Author

Listed:
  • Jiageng, Niu
  • Lanlan, Zheng
  • Xianghong, Li

Abstract

With the gradual expansion of the university scale, it is extremely inconvenient for students to travel to and from campus and classrooms. Bikeshare and shared electric bike (e-bikeshare) are currently promising solutions for campus travel. Most literature has recently focused on bikeshare and e-bikeshare studies in the urban environment, with little attention on campus. However, campuses are significantly different from urban environments, which hinder the active promotion of campus bikeshare and e-bikeshare use. The subject of this paper is Henan Polytechnic University, which is one of the largest bikeshare and e-bikeshare universities in China. Based on the analysis and summary of travel characteristics of Chinese college travelers, this paper uses RP and SP survey data to construct a Nested Logit model to explore the potential factors influencing the use behavior of bikeshare and e-bikeshare in Chinese college environments. The results show that bikeshare and e-bikeshare are the most sensitive to trip time. The influence of trip purpose and weather conditions on the selection of bikeshare and e-bikeshare is smaller than that of time urgency. According to the estimated trip sharing rate of the model, we find that bikeshare and e-bikeshare are attractive.

Suggested Citation

  • Jiageng, Niu & Lanlan, Zheng & Xianghong, Li, 2022. "A study on the trip behavior of shared bicycles and shared electric bikes in Chinese universities based on NL model—Henan Polytechnic University as an example," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    • Handle: RePEc:eee:phsmap:v:604:y:2022:i:c:s0378437122005544
    DOI: 10.1016/j.physa.2022.127855
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437122005544
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2022.127855?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. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    2. Greene, William H. & Hensher, David A., 2003. "A latent class model for discrete choice analysis: contrasts with mixed logit," Transportation Research Part B: Methodological, Elsevier, vol. 37(8), pages 681-698, September.
    3. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, January.
    4. 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.
    5. 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.
    6. Kutela, Boniphace & Teng, Hualiang, 2019. "The influence of campus characteristics, temporal factors, and weather events on campuses-related daily bike-share trips," Journal of Transport Geography, Elsevier, vol. 78(C), pages 160-169.
    7. Espino, Raquel & de Dios Ortúzar, Juan & Román, Concepción, 2007. "Understanding suburban travel demand: Flexible modelling with revealed and stated choice data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(10), pages 899-912, December.
    8. Wen, Chieh-Hua & Wang, Wei-Chung & Fu, Chiang, 2012. "Latent class nested logit model for analyzing high-speed rail access mode choice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(2), pages 545-554.
    9. Nankervis, Max, 1999. "The effect of weather and climate on bicycle commuting," Transportation Research Part A: Policy and Practice, Elsevier, vol. 33(6), pages 417-431, August.
    10. 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).
    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. Tinessa, Fiore & Marzano, Vittorio & Papola, Andrea, 2020. "Mixing distributions of tastes with a Combination of Nested Logit (CoNL) kernel: Formulation and performance analysis," Transportation Research Part B: Methodological, Elsevier, vol. 141(C), pages 1-23.
    2. Espino, Raquel & Román, Concepción, 2020. "Valuation of transfer for bus users: The case of Gran Canaria," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 131-144.
    3. Paleti, Rajesh, 2018. "Generalized multinomial probit Model: Accommodating constrained random parameters," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 248-262.
    4. Hyungkyoo Kim, 2020. "Seasonal Impacts of Particulate Matter Levels on Bike Sharing in Seoul, South Korea," IJERPH, MDPI, vol. 17(11), pages 1-17, June.
    5. Daniele Pacifico, 2012. "Fitting nonparametric mixed logit models via expectation-maximization algorithm," Stata Journal, StataCorp LP, vol. 12(2), pages 284-298, June.
    6. Stefania Troiano & Daniel Vecchiato & Francesco Marangon & Tiziano Tempesta & Federico Nassivera, 2019. "Households’ Preferences for a New ‘Climate-Friendly’ Heating System: Does Contribution to Reducing Greenhouse Gases Matter?," Energies, MDPI, vol. 12(13), pages 1-19, July.
    7. Alessandro Mengoni & Chiara Seghieri & Sabina Nuti, 2013. "The application of discrete choice experiments in health economics: a systematic review of the literature," Working Papers 201301, Scuola Superiore Sant'Anna of Pisa, Istituto di Management.
    8. Joan L. Walker & Moshe Ben-Akiva, 2011. "Advances in Discrete Choice: Mixture Models," Chapters, in: André de Palma & Robin Lindsey & Emile Quinet & Roger Vickerman (ed.), A Handbook of Transport Economics, chapter 8, Edward Elgar Publishing.
    9. Yang, Chih-Wen & Sung, Yen-Ching, 2010. "Constructing a mixed-logit model with market positioning to analyze the effects of new mode introduction," Journal of Transport Geography, Elsevier, vol. 18(1), pages 175-182.
    10. Eric Ruto & Guy Garrod & Riccardo Scarpa, 2008. "Valuing animal genetic resources: a choice modeling application to indigenous cattle in Kenya," Agricultural Economics, International Association of Agricultural Economists, vol. 38(1), pages 89-98, January.
    11. Houessionon, P. & Fonta, W. M. & Bossa, A. Y. & Sanfo, S. & Thiombiano, N. & Zahonogo, P. & Yameogo, T. B. & Balana, Bedru, "undated". "Economic valuation of ecosystem services from small-scale agricultural management interventions in Burkina Faso: a discrete choice experiment approach," Papers published in Journals (Open Access) H048370, International Water Management Institute.
    12. Bansal, Prateek & Daziano, Ricardo A. & Achtnicht, Martin, 2018. "Comparison of parametric and semiparametric representations of unobserved preference heterogeneity in logit models," Journal of choice modelling, Elsevier, vol. 27(C), pages 97-113.
    13. Sergio Colombo & Nick Hanley & Jordan Louviere, 2009. "Modeling preference heterogeneity in stated choice data: an analysis for public goods generated by agriculture," Agricultural Economics, International Association of Agricultural Economists, vol. 40(3), pages 307-322, May.
    14. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
    15. Haghani, Milad & Sarvi, Majid, 2018. "Hypothetical bias and decision-rule effect in modelling discrete directional choices," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 361-388.
    16. Gutsche, Gunnar & Ziegler, Andreas, 2019. "Which private investors are willing to pay for sustainable investments? Empirical evidence from stated choice experiments," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 193-214.
    17. Hudyeron Rocha & António Lobo & José Pedro Tavares & Sara Ferreira, 2023. "Exploring Modal Choices for Sustainable Urban Mobility: Insights from the Porto Metropolitan Area in Portugal," Sustainability, MDPI, vol. 15(20), pages 1-20, October.
    18. Daniele Pacifico, 2010. "Estimating nonparametric mixed logit models via EM algorithm," Center for the Analysis of Public Policies (CAPP) 0072, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    19. Frith, Michael J., 2019. "Modelling taste heterogeneity regarding offence location choices," Journal of choice modelling, Elsevier, vol. 33(C).
    20. Kermagoret, Charlène & Levrel, Harold & Carlier, Antoine & Dachary-Bernard, Jeanne, 2016. "Individual preferences regarding environmental offset and welfare compensation: a choice experiment application to an offshore wind farm project," Ecological Economics, Elsevier, vol. 129(C), pages 230-240.

    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:phsmap:v:604:y:2022:i:c:s0378437122005544. 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.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.