IDEAS home Printed from https://ideas.repec.org/a/eee/trapol/v149y2024icp177-197.html
   My bibliography  Save this article

Preferences for public electric vehicle charging infrastructure locations: A discrete choice analysis

Author

Listed:
  • Bhat, Furqan A.
  • Tiwari, Gaurav Yash
  • Verma, Ashish

Abstract

Electric vehicles are finding it difficult to make faster inroads into the markets, and one of the most cited barriers to the faster adoption of electric vehicles in the academic literature is the lack of charging infrastructure and the associated range anxiety. However, densifying the charging infrastructure network is cost-intensive and should be meticulously planned. This study estimates discrete choice models with workplace, leisure place and highway as the location choice alternatives to investigate the electric vehicle public charging location preferences of the potential electric vehicle buyers. Mixed multinomial logit models and integrated choice and latent variable models are developed based on the attributes of the charging stations, viz. charging time, waiting time, charging cost, distance to the nearest charging station, emissions, and the characteristics of the individuals such as age, gender, income, and daily travel distance. This study finds significant negative utility associated with higher values of charging times, waiting times, charging costs, distance to the nearest charging station, and emissions. The results also indicate that the marginal disutility related to waiting time is higher than that of charging time. In terms of socio-demographics, females and higher income groups are found to prefer the workplace as their place of charging. However, as the age increases, the inclination towards highway charging stations increases. This study also discusses some important policy implications that can help decision-makers and stakeholders better plan electric vehicle charging infrastructure.

Suggested Citation

  • Bhat, Furqan A. & Tiwari, Gaurav Yash & Verma, Ashish, 2024. "Preferences for public electric vehicle charging infrastructure locations: A discrete choice analysis," Transport Policy, Elsevier, vol. 149(C), pages 177-197.
  • Handle: RePEc:eee:trapol:v:149:y:2024:i:c:p:177-197
    DOI: 10.1016/j.tranpol.2024.02.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0967070X24000398
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tranpol.2024.02.004?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. Plötz, Patrick & Funke, Simon & Jochem, Patrick, 2015. "Real-world fuel economy and CO2 emissions of plug-in hybrid electric vehicles," Working Papers "Sustainability and Innovation" S1/2015, Fraunhofer Institute for Systems and Innovation Research (ISI).
    2. Prateek Bansal & Rajeev Ranjan Kumar & Alok Raj & Subodh Dubey & Daniel J. Graham, 2021. "Willingness to Pay and Attitudinal Preferences of Indian Consumers for Electric Vehicles," Papers 2101.08008, arXiv.org, revised May 2021.
    3. Simsekoglu, Özlem, 2018. "Socio-demographic characteristics, psychological factors and knowledge related to electric car use: A comparison between electric and conventional car drivers," Transport Policy, Elsevier, vol. 72(C), pages 180-186.
    4. Baresch, Martin & Moser, Simon, 2019. "Allocation of e-car charging: Assessing the utilization of charging infrastructures by location," Transportation Research Part A: Policy and Practice, Elsevier, vol. 124(C), pages 388-395.
    5. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, September.
    6. Giansoldati, Marco & Rotaris, Lucia & Scorrano, Mariangela & Danielis, Romeo, 2020. "Does electric car knowledge influence car choice? Evidence from a hybrid choice model," Research in Transportation Economics, Elsevier, vol. 80(C).
    7. Jianmin Jia & Chenhui Liu & Tao Wan, 2019. "Planning of the Charging Station for Electric Vehicles Utilizing Cellular Signaling Data," Sustainability, MDPI, vol. 11(3), pages 1-16, January.
    8. Müller-Seitz, Gordon & Dautzenberg, Kirsti & Creusen, Utho & Stromereder, Christine, 2009. "Customer acceptance of RFID technology: Evidence from the German electronic retail sector," Journal of Retailing and Consumer Services, Elsevier, vol. 16(1), pages 31-39.
    9. Christos Karolemeas & Stefanos Tsigdinos & Panagiotis G. Tzouras & Alexandros Nikitas & Efthimios Bakogiannis, 2021. "Determining Electric Vehicle Charging Station Location Suitability: A Qualitative Study of Greek Stakeholders Employing Thematic Analysis and Analytical Hierarchy Process," Sustainability, MDPI, vol. 13(4), pages 1-21, February.
    10. Bansal, Prateek & Kumar, Rajeev Ranjan & Raj, Alok & Dubey, Subodh & Graham, Daniel J., 2021. "Willingness to pay and attitudinal preferences of Indian consumers for electric vehicles," Energy Economics, Elsevier, vol. 100(C).
    11. Hess, Stephane & Bierlaire, Michel & Polak, John W., 2005. "Estimation of value of travel-time savings using mixed logit models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(2-3), pages 221-236.
    12. Patt, Anthony & Aplyn, David & Weyrich, Philippe & van Vliet, Oscar, 2019. "Availability of private charging infrastructure influences readiness to buy electric cars," Transportation Research Part A: Policy and Practice, Elsevier, vol. 125(C), pages 1-7.
    13. Joan L. Walker & Yanqiao Wang & Mikkel Thorhauge & Moshe Ben-Akiva, 2018. "D-efficient or deficient? A robustness analysis of stated choice experimental designs," Theory and Decision, Springer, vol. 84(2), pages 215-238, March.
    14. Qian, Lixian & Grisolía, Jose M. & Soopramanien, Didier, 2019. "The impact of service and government-policy attributes on consumer preferences for electric vehicles in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 122(C), pages 70-84.
    15. Ruoso, Ana Cristina & Ribeiro, José Luis Duarte, 2022. "An assessment of barriers and solutions for the deployment of electric vehicles in the Brazilian market," Transport Policy, Elsevier, vol. 127(C), pages 218-229.
    16. Hess, Stephane & Palma, David, 2019. "Apollo: A flexible, powerful and customisable freeware package for choice model estimation and application," Journal of choice modelling, Elsevier, vol. 32(C), pages 1-1.
    17. Chakraborty, Rahul & Chakravarty, Sujoy, 2023. "Factors affecting acceptance of electric two-wheelers in India: A discrete choice survey," Transport Policy, Elsevier, vol. 132(C), pages 27-41.
    18. Chunlin Guo & Jingjing Yang & Lin Yang, 2018. "Planning of Electric Vehicle Charging Infrastructure for Urban Areas with Tight Land Supply," Energies, MDPI, vol. 11(9), pages 1-17, September.
    19. Morrissey, Patrick & Weldon, Peter & O’Mahony, Margaret, 2016. "Future standard and fast charging infrastructure planning: An analysis of electric vehicle charging behaviour," Energy Policy, Elsevier, vol. 89(C), pages 257-270.
    20. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    21. Globisch, Joachim & Plötz, Patrick & Dütschke, Elisabeth & Wietschel, Martin, 2019. "Consumer preferences for public charging infrastructure for electric vehicles," Transport Policy, Elsevier, vol. 81(C), pages 54-63.
    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. Bhat, Furqan A. & Verma, Ashish, 2024. "Electric two-wheeler adoption in India – A discrete choice analysis of motivators and barriers affecting the potential electric two-wheeler buyers," Transport Policy, Elsevier, vol. 152(C), pages 118-131.
    2. Jia, Wenjian & Jiang, Zhiqiu & Wang, Qian & Xu, Bin & Xiao, Mei, 2023. "Preferences for zero-emission vehicle attributes: Comparing early adopters with mainstream consumers in California," Transport Policy, Elsevier, vol. 135(C), pages 21-32.
    3. Poudel, Niranjan & Singleton, Patrick A., 2024. "Willingness to pay for changes in travel time and work time: A stated choice experiment of US commuters," Research in Transportation Economics, Elsevier, vol. 103(C).
    4. Iogansen, Xiatian & Wang, Kailai & Bunch, David & Matson, Grant & Circella, Giovanni, 2023. "Deciphering the factors associated with adoption of alternative fuel vehicles in California: An investigation of latent attitudes, socio-demographics, and neighborhood effects," Transportation Research Part A: Policy and Practice, Elsevier, vol. 168(C).
    5. Solvi Hoen, Fredrik & Díez-Gutiérrez, María & Babri, Sahar & Hess, Stephane & Tørset, Trude, 2023. "Charging electric vehicles on long trips and the willingness to pay to reduce waiting for charging. Stated preference survey in Norway," Transportation Research Part A: Policy and Practice, Elsevier, vol. 175(C).
    6. Jia, Wenjian & Chen, T. Donna, 2023. "Investigating heterogeneous preferences for plug-in electric vehicles: Policy implications from different choice models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    7. Oyama, Yuki & Fukuda, Daisuke & Imura, Naoto & Nishinari, Katsuhiro, 2024. "Do people really want fast and precisely scheduled delivery? E-commerce customers' valuations of home delivery timing," Journal of Retailing and Consumer Services, Elsevier, vol. 78(C).
    8. Yuki Oyama & Daisuke Fukuda & Naoto Imura & Katsuhiro Nishinari, 2022. "E-commerce users' preferences for delivery options," Papers 2301.00666, arXiv.org, revised Aug 2023.
    9. Bera, Reema & Maitra, Bhargab, 2021. "Assessing consumer preferences for Plug-in Hybrid Electric Vehicle (PHEV): An Indian perspective," Research in Transportation Economics, Elsevier, vol. 90(C).
    10. Qian, Lixian & Huang, Youlin & Tyfield, David & Soopramanien, Didier, 2023. "Dynamic consumer preferences for electric vehicles in China: A longitudinal approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 176(C).
    11. Fosgerau, Mogens & Bierlaire, Michel, 2007. "A practical test for the choice of mixing distribution in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 41(7), pages 784-794, August.
    12. Martínez-Pardo, Ana & Orro, Alfonso & Garcia-Alonso, Lorena, 2020. "Analysis of port choice: A methodological proposal adjusted with public data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 136(C), pages 178-193.
    13. Juan Carlos Martín & Concepción Román & Cira Mendoza, 2018. "Determinants for sun-and-beach self-catering accommodation selection," Tourism Economics, , vol. 24(3), pages 319-336, May.
    14. Stergios Statharas & Yannis Moysoglou & Pelopidas Siskos & Pantelis Capros, 2021. "Simulating the Evolution of Business Models for Electricity Recharging Infrastructure Development by 2030: A Case Study for Greece," Energies, MDPI, vol. 14(9), pages 1-24, April.
    15. Isler, Cassiano Augusto & Blumenfeld, Marcelo & Caldeira, Gabriel Pereira & Roberts, Clive, 2024. "Long-Distance railway mode choice in Brazil: Evidence from a discrete choice experiment," Research in Transportation Economics, Elsevier, vol. 104(C).
    16. Visaria, Anant Atul & Jensen, Anders Fjendbo & Thorhauge, Mikkel & Mabit, Stefan Eriksen, 2022. "User preferences for EV charging, pricing schemes, and charging infrastructure," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 120-143.
    17. Reema Bera & Bhargab Maitra, 2021. "Analyzing Prospective Owners’ Choice Decision towards Plug-in Hybrid Electric Vehicles in Urban India: A Stated Preference Discrete Choice Experiment," Sustainability, MDPI, vol. 13(14), pages 1-24, July.
    18. Punel, Aymeric & Stathopoulos, Amanda, 2017. "Modeling the acceptability of crowdsourced goods deliveries: Role of context and experience effects," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 105(C), pages 18-38.
    19. Ladenburg, Jacob & Olsen, Søren Bøye, 2014. "Augmenting short Cheap Talk scripts with a repeated Opt-Out Reminder in Choice Experiment surveys," Resource and Energy Economics, Elsevier, vol. 37(C), pages 39-63.
    20. Saxena, N. & Rashidi, T.H. & Dixit, V.V. & Waller, S.T., 2019. "Modelling the route choice behaviour under stop-&-go traffic for different car driver segments," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 62-72.

    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:149:y:2024:i:c:p:177-197. 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.