IDEAS home Printed from https://ideas.repec.org/a/eee/trapol/v146y2024icp59-71.html
   My bibliography  Save this article

How does travel satisfaction affect preference for shared electric vehicles? An empirical study using large-scale monitoring data and online text mining

Author

Listed:
  • Zou, Pengyu
  • Zhang, Bin
  • Yi, Yi
  • Wang, Zhaohua

Abstract

Shared electric vehicles (SEVs) are an emerging mode of transportation that offers advantages in environmental protection. It is unclear what role travel satisfaction plays in operations. User's feedback is an important factor to the future development of SEVs. How to accurately collect user's feedback and predictions is the focus of attention. In this paper, we innovatively used sentiment analysis to construct the travel satisfaction index based on text data from the largest social network platforms in China. In addition, we used a vector autoregression model to analyse and confirm that users' trip satisfaction is an important factor influencing subsequent use of SEVs. A large-scale data set of travel records combined with point of interest information of SEVs that covered 1.64 million records of 3,100 vehicles. The results showed that low rates of satisfaction of SEVs are attributed to the fault rate of vehicles and poor services. Arranging SEV services around restaurants and commercial areas will result in higher user's satisfaction. Moreover, an increase in user's satisfaction will increase the usage frequency of SEVs in future trips. An increase in satisfaction will reduce rental times of returning users in the short term, but it has no effect on travel distance.

Suggested Citation

  • Zou, Pengyu & Zhang, Bin & Yi, Yi & Wang, Zhaohua, 2024. "How does travel satisfaction affect preference for shared electric vehicles? An empirical study using large-scale monitoring data and online text mining," Transport Policy, Elsevier, vol. 146(C), pages 59-71.
    • Handle: RePEc:eee:trapol:v:146:y:2024:i:c:p:59-71
    DOI: 10.1016/j.tranpol.2023.10.027
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0967070X23003013
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tranpol.2023.10.027?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. Meng, Zhiyi & Li, Eldon Y. & Qiu, Rui, 2020. "Environmental sustainability with free-floating carsharing services: An on-demand refueling recommendation system for Car2go in Seattle," Technological Forecasting and Social Change, Elsevier, vol. 152(C).
    2. Shaheen, Susan & Martin, Elliot & Totte, Hannah, 2020. "Zero-emission vehicle exposure within U.S. carsharing fleets and impacts on sentiment toward electric-drive vehicles," Transport Policy, Elsevier, vol. 85(C), pages 23-32.
    3. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    4. Fan, Jing-Li & Wang, Jia-Xing & Zhang, Xian, 2020. "An innovative subsidy model for promoting the sharing of Electric Vehicles in China: A pricing decisions analysis," Energy, Elsevier, vol. 201(C).
    5. Lu, Xiaonong & Zhang, Qiang & Peng, Zhanglin & Shao, Zhen & Song, Hao & Wang, Wanying, 2020. "Charging and relocating optimization for electric vehicle car-sharing: An event-based strategy improvement approach," Energy, Elsevier, vol. 207(C).
    6. Karla Münzel & Wouter Boon & Koen Frenken & Taneli Vaskelainen, 2018. "Carsharing business models in Germany: characteristics, success and future prospects," Information Systems and e-Business Management, Springer, vol. 16(2), pages 271-291, May.
    7. Zhou, Yue & Wen, Ruoxi & Wang, Hewu & Cai, Hua, 2020. "Optimal battery electric vehicles range: A study considering heterogeneous travel patterns, charging behaviors, and access to charging infrastructure," Energy, Elsevier, vol. 197(C).
    8. Shaheen, Susan & Martin, Elliot & Totte, Hannah, 2020. "Zero-emission vehicle exposure within U.S. carsharing fleets and impacts on sentiment toward electric-drive vehicles," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt95j7g71k, Institute of Transportation Studies, UC Berkeley.
    9. Jian, Sisi & Rashidi, Taha Hossein & Dixit, Vinayak, 2017. "An analysis of carsharing vehicle choice and utilization patterns using multiple discrete-continuous extreme value (MDCEV) models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 362-376.
    10. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    11. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    12. Wadud, Zia & Mattioli, Giulio, 2021. "Fully automated vehicles: A cost-based analysis of the share of ownership and mobility services, and its socio-economic determinants," Transportation Research Part A: Policy and Practice, Elsevier, vol. 151(C), pages 228-244.
    13. Lai, Kexing & Chen, Tao & Natarajan, Balasubramaniam, 2020. "Optimal scheduling of electric vehicles car-sharing service with multi-temporal and multi-task operation," Energy, Elsevier, vol. 204(C).
    14. Wang, Wanying & Zhang, Qiang & Peng, Zhanglin & Shao, Zhen & Li, Xuefang, 2020. "An empirical evaluation of different usage pattern between car-sharing battery electric vehicles and private ones," Transportation Research Part A: Policy and Practice, Elsevier, vol. 135(C), pages 115-129.
    15. Soares, João & Borges, Nuno & Fotouhi Ghazvini, Mohammad Ali & Vale, Zita & de Moura Oliveira, P.B., 2016. "Scenario generation for electric vehicles' uncertain behavior in a smart city environment," Energy, Elsevier, vol. 111(C), pages 664-675.
    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. Yvon Fauvel & Alain Paquet & Christian Zimmermann, 1999. "A Survey on Interest Rate Forecasting," Cahiers de recherche CREFE / CREFE Working Papers 87, CREFE, Université du Québec à Montréal.
    2. Marrouch, Walid & Mourad, Jana, 2019. "Effect of gasoline prices on car fuel efficiency: Evidence from Lebanon," Energy Policy, Elsevier, vol. 135(C).
    3. Mehmet Balcilar & Evrim Toren, 2021. "The Time-Varying Effect of Asset Prices on Turkey’s Circular Economy," Sustainability, MDPI, vol. 13(22), pages 1-16, November.
    4. Faisal Abbas & Ulrich Hiemenz, 2013. "What determines public health expenditures in Pakistan? Role of income, urbanization and unemployment," Economic Change and Restructuring, Springer, vol. 46(4), pages 341-362, November.
    5. Panagiotis T. Konstantinou, 2004. "Balancing The Budget Through Revenue Or Spending Adjustments? The Case Of Greece," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 29(2), pages 81-105, December.
    6. Goodness C. Aye & Rangan Gupta & Mampho P. Modise, 2015. "Do Stock Prices Impact Consumption and Interest Rate in South Africa? Evidence from a Time-varying Vector Autoregressive Model," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 14(2), pages 176-196, August.
    7. Ferda Halicioglu, 2012. "Temporal causality and the dynamics of crime in Turkey," International Journal of Social Economics, Emerald Group Publishing Limited, vol. 39(9), pages 704-720, July.
    8. Pami Dua & Nishita Raje & Satyananda Sahoo, 2008. "Forecasting Interest Rates in India," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 2(1), pages 1-41, March.
    9. Manolis G. Kavussanos & Ilias D. Visvikis, 2011. "The Predictability of Non-Overlapping Forecasts: Evidence from a New Market," Multinational Finance Journal, Multinational Finance Journal, vol. 15(1-2), pages 125-156, March - J.
    10. Pershin, Vitaly & Molero, Juan Carlos & de Gracia, Fernando Perez, 2016. "Exploring the oil prices and exchange rates nexus in some African economies," Journal of Policy Modeling, Elsevier, vol. 38(1), pages 166-180.
    11. Guo, Peng & Chen, Zhihua & Yang, Yang & Miao, Rui, 2024. "A multistage simulation-optimization-integrated methodology framework for user-oriented electric vehicle carsharing reallocation under dynamic price subsidy," Energy, Elsevier, vol. 290(C).
    12. Nafeesa Yunus, 2016. "Modelling interactions among the housing market and key US sectors," Journal of Property Research, Taylor & Francis Journals, vol. 33(2), pages 121-146, April.
    13. Vittorio Peretti & Rangan Gupta & Roula Inglesi-Lotz, 2012. "Do House Prices Impact Consumption and Interest Rate in South Africa? Evidence from a Time-Varying Vector Autoregressive Model," Working Papers 201216, University of Pretoria, Department of Economics.
    14. Apergis, Nicholas, 2014. "Can gold prices forecast the Australian dollar movements?," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 75-82.
    15. Claude Diebolt & Magali Jaoul-Grammare & Faustine Perrin, 2020. "Scolarisation de masse des garçons et des filles. Financement public de l’instruction primaire et croissance économique en France au XIXème siècle," Working Papers of BETA 2020-51, Bureau d'Economie Théorique et Appliquée, UDS, Strasbourg.
    16. Singh, Tarlok, 2010. "Does domestic saving cause economic growth? A time-series evidence from India," Journal of Policy Modeling, Elsevier, vol. 32(2), pages 231-253, March.
    17. Ferda HALICIOGLU, 2012. "The Demand for Calories in Turkey," Iktisat Isletme ve Finans, Bilgesel Yayincilik, vol. 27(316), pages 93-108.
    18. Ghassan Dibeh & Ali Fakih & Walid Marrouch, 2020. "Tourism–growth nexus under duress: Lebanon during the Syrian crisis," Tourism Economics, , vol. 26(3), pages 353-370, May.
    19. Singh, Tarlok, 2008. "Testing the Saving-Investment correlations in India: An evidence from single-equation and system estimators," Economic Modelling, Elsevier, vol. 25(5), pages 1064-1079, September.
    20. Ferda Halıcıoğlu & Kasım Eren, 2017. "Testing Twin Deficits and Saving-Investment Nexus in Turkey," Yildiz Social Science Review, Yildiz Technical University, vol. 3(1), pages 35-46.

    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:trapol:v:146:y:2024:i:c:p:59-71. 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/30473/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.