IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i6p3035-d514405.html
   My bibliography  Save this article

Evaluation of Prospective Users’ Choice Decision toward Electric Two-Wheelers Using a Stated Preference Survey: An Indian Perspective

Author

Listed:
  • Mallikarjun Patil

    (Department of Civil Engineering, Birla Institute of Technology and Science Pilani, Hyderabad 500078, India)

  • Bandhan Bandhu Majumdar

    (Department of Civil Engineering, Birla Institute of Technology and Science Pilani, Hyderabad 500078, India)

  • Prasanta Kumar Sahu

    (Department of Civil Engineering, Birla Institute of Technology and Science Pilani, Hyderabad 500078, India)

  • Long T. Truong

    (Department of Engineering, La Trobe University, Melbourne 3086, Australia)

Abstract

Electric two-wheelers (E2W) can help de-carbonize transport in Indian cities. To promote E2W as an attractive alternative compared to the conventional two-wheelers, an investigation on prospective users’ choice decisions is necessary. This paper proposed a comprehensive methodology to evaluate the prospective users’ choice decision toward electric two-wheelers and related attributes in the Indian context. In this paper, attributes such as Operating Cost (OC) savings, top speed, range, charging duration, acceleration, and purchase cost were considered to design a Stated Preference (SP) survey to collect data from prospective E2W users in Hyderabad, India. Concurrently, multinomial logit (MNL) and random parameter logit (RPL) models are developed, and the willingness-to-pay (WTP) associated with each of the identified attributes was estimated. Additionally, the effect of socio-economic characteristics on prospective users’ choice decision was also assessed. Subsequently, a sensitivity analysis was carried out to estimate the relative influence of the attributes on an individual’s choice decision in terms of the shift in probability to choose alternatives with better attribute levels than the base alternative. The results revealed that top speed was perceived as the most important attribute influencing an individual’s choice decision, followed by acceleration and charging duration. Age, income, and journey time significantly influenced an individual’s perception toward E2W and related attributes in the Indian context.

Suggested Citation

  • Mallikarjun Patil & Bandhan Bandhu Majumdar & Prasanta Kumar Sahu & Long T. Truong, 2021. "Evaluation of Prospective Users’ Choice Decision toward Electric Two-Wheelers Using a Stated Preference Survey: An Indian Perspective," Sustainability, MDPI, vol. 13(6), pages 1-22, March.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:6:p:3035-:d:514405
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/6/3035/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/6/3035/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hamed Taherdoost, 2017. "Determining Sample Size; How to Calculate Survey Sample Size," Post-Print hal-02557333, HAL.
    2. Laura Eboli & Gabriella Mazzulla, 2008. "A Stated Preference Experiment for Measuring Service Quality in Public Transport," Transportation Planning and Technology, Taylor & Francis Journals, vol. 31(5), pages 509-523, February.
    3. Cirillo, Cinzia & Liu, Yan & Maness, Michael, 2017. "A time-dependent stated preference approach to measuring vehicle type preferences and market elasticity of conventional and green vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 294-310.
    4. Sarmad Zaman Rajper & Johan Albrecht, 2020. "Prospects of Electric Vehicles in the Developing Countries: A Literature Review," Sustainability, MDPI, vol. 12(5), pages 1-19, March.
    5. Han-Shen Chen & Bi-Kun Tsai & Chi-Ming Hsieh, 2018. "The Effects of Perceived Barriers on Innovation Resistance of Hydrogen-Electric Motorcycles," Sustainability, MDPI, vol. 10(6), pages 1-15, June.
    6. Bhat, Chandra R., 2001. "Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 677-693, August.
    7. Yen-Ching Sung, 2010. "Consumer learning behavior in choosing electric motorcycles," Transportation Planning and Technology, Taylor & Francis Journals, vol. 33(2), pages 139-155, January.
    8. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    9. Brownstone, David & Bunch, David S. & Golob, Thomas F., 1994. "A Demand Forecasting System for Clean-Fuel Vehicles," University of California Transportation Center, Working Papers qt79c3g7xv, University of California Transportation Center.
    10. Wang, Jueyu & Lindsey, Greg, 2019. "Do new bike share stations increase member use: A quasi-experimental study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 121(C), pages 1-11.
    11. Bansal, Prateek & Daziano, Ricardo A. & Achtnicht, Martin, 2018. "Extending the logit-mixed logit model for a combination of random and fixed parameters," Journal of choice modelling, Elsevier, vol. 27(C), pages 88-96.
    12. Ziwen Ling & Christopher R. Cherry & John H. MacArthur & Jonathan X. Weinert, 2017. "Differences of Cycling Experiences and Perceptions between E-Bike and Bicycle Users in the United States," Sustainability, MDPI, vol. 9(9), pages 1-18, September.
    13. Hidrue, Michael K. & Parsons, George R. & Kempton, Willett & Gardner, Meryl P., 2011. "Willingness to pay for electric vehicles and their attributes," Resource and Energy Economics, Elsevier, vol. 33(3), pages 686-705, September.
    14. Jones, Luke R. & Cherry, Christopher R. & Vu, Tuan A. & Nguyen, Quang N., 2013. "The effect of incentives and technology on the adoption of electric motorcycles: A stated choice experiment in Vietnam," Transportation Research Part A: Policy and Practice, Elsevier, vol. 57(C), pages 1-11.
    15. Massimo Filippini & Nilkanth Kumar & Suchita Srinivasan, 2020. "Nudging the Adoption of Fuel-Efficient Vehicles: Evidence from a Stated Choice Experiment in Nepal," CER-ETH Economics working paper series 20/333, CER-ETH - Center of Economic Research (CER-ETH) at ETH Zurich.
    16. Zhu, Lichao & Song, Qingbin & Sheng, Ni & Zhou, Xiu, 2019. "Exploring the determinants of consumers’ WTB and WTP for electric motorcycles using CVM method in Macau," Energy Policy, Elsevier, vol. 127(C), pages 64-72.
    17. Denzil G. Fiebig & Michael P. Keane & Jordan Louviere & Nada Wasi, 2010. "The Generalized Multinomial Logit Model: Accounting for Scale and Coefficient Heterogeneity," Marketing Science, INFORMS, vol. 29(3), pages 393-421, 05-06.
    18. Majumdar, Bandhan Bandhu & Mitra, Sudeshna, 2018. "Analysis of bicycle route-related improvement strategies for two Indian cities using a stated preference survey," Transport Policy, Elsevier, vol. 63(C), pages 176-188.
    19. 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.
    20. Lin, Boqiang & Tan, Ruipeng, 2017. "Estimation of the environmental values of electric vehicles in Chinese cities," Energy Policy, Elsevier, vol. 104(C), pages 221-229.
    21. Sadhukhan, Shubhajit & Banerjee, Uttam K. & Maitra, Bhargab, 2016. "Commuters’ willingness-to-pay for improvement of transfer facilities in and around metro stations – A case study in Kolkata," Transportation Research Part A: Policy and Practice, Elsevier, vol. 92(C), pages 43-58.
    22. Woongchul Choi & Seokho Yun, 2020. "A Comparative Study of Initial Cost Recuperation Period of Plug-In Series Hybrid Electric Two-Wheel Vehicles in Southeast Asian Countries," Sustainability, MDPI, vol. 12(24), pages 1-10, December.
    23. Changxi Ma & Jibiao Zhou & Dong Yang & Yuanyuan Fan, 2020. "Research on the Relationship between the Individual Characteristics of Electric Bike Riders and Illegal Speeding Behavior: A Questionnaire-Based Study," Sustainability, MDPI, vol. 12(3), pages 1-12, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Scorrano, Mariangela & Rotaris, Lucia, 2022. "The role of environmental awareness and knowledge in the choice of a seated electric scooter," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 333-347.
    2. Marazi, Naveed Farooz & Majumdar, Bandhan Bandhu & Sahu, Prasanta K. & Potoglou, Dimitris, 2022. "Congestion pricing acceptability among commuters: An Indian perspective," Research in Transportation Economics, Elsevier, vol. 95(C).

    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. 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.
    2. 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.
    3. 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).
    4. Sadhukhan, Shubhajit & Banerjee, Uttam K. & Maitra, Bhargab, 2016. "Commuters’ willingness-to-pay for improvement of transfer facilities in and around metro stations – A case study in Kolkata," Transportation Research Part A: Policy and Practice, Elsevier, vol. 92(C), pages 43-58.
    5. Laura Eboli & Gabriella Mazzulla, 2014. "Investigating the heterogeneity of bus users' preferences through discrete choice modelling," Transportation Planning and Technology, Taylor & Francis Journals, vol. 37(8), pages 695-710, December.
    6. Loría, Luis Enrique & Watson, Verity & Kiso, Takahiko & Phimister, Euan, 2019. "Investigating users' preferences for Low Emission Buses: Experiences from Europe's largest hydrogen bus fleet," Journal of choice modelling, Elsevier, vol. 32(C), pages 1-1.
    7. 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).
    8. 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.
    9. Daina, Nicolò & Sivakumar, Aruna & Polak, John W., 2017. "Modelling electric vehicles use: a survey on the methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 447-460.
    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. Hoyos, David, 2010. "The state of the art of environmental valuation with discrete choice experiments," Ecological Economics, Elsevier, vol. 69(8), pages 1595-1603, June.
    12. I. G. Ukpong & K. G. Balcombe & I. M. Fraser & F. J. Areal, 2019. "Preferences for Mitigation of the Negative Impacts of the Oil and Gas Industry in the Niger Delta Region of Nigeria," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 74(2), pages 811-843, October.
    13. De Ayala Bilbao, Amaya & Hoyos Ramos, David & Mariel Chladkova, Petr, 2012. "Landscape valuation through discrete choice experiments: Current practice and future research reflections," BILTOKI 1134-8984, Universidad del País Vasco - Departamento de Economía Aplicada III (Econometría y Estadística).
    14. 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.
    15. Aravena, C. & Denny, E., 2021. "The impact of learning and short-term experience on preferences for electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    16. Junyi Shen & Yusuke Sakata & Yoshizo Hashimoto, 2006. "A Comparison between Latent Class Model and Mixed Logit Model for Transport Mode Choice: Evidences from Two Datasets of Japan," Discussion Papers in Economics and Business 06-05, Osaka University, Graduate School of Economics.
    17. Sarrias, Mauricio & Daziano, Ricardo, 2017. "Multinomial Logit Models with Continuous and Discrete Individual Heterogeneity in R: The gmnl Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i02).
    18. Ji, Dandan & Gan, Hongcheng, 2022. "Effects of providing total cost of ownership information on below-40 young consumers’ intent to purchase an electric vehicle: A case study in China," Energy Policy, Elsevier, vol. 165(C).
    19. Sarmad Zaman Rajper & Johan Albrecht, 2020. "Prospects of Electric Vehicles in the Developing Countries: A Literature Review," Sustainability, MDPI, vol. 12(5), pages 1-19, March.
    20. Majumdar, Bandhan Bandhu & Mitra, Sudeshna, 2018. "Analysis of bicycle route-related improvement strategies for two Indian cities using a stated preference survey," Transport Policy, Elsevier, vol. 63(C), pages 176-188.

    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:gam:jsusta:v:13:y:2021:i:6:p:3035-:d:514405. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.