IDEAS home Printed from https://ideas.repec.org/p/ift/wpaper/2042.html
   My bibliography  Save this paper

Electric Street Car as a Clean Public Transport Alternative: A Choice Experiment Approach

Author

Listed:
  • Oindrila Dey

    (Indian Institute of Foreign Trade (IIFT))

  • Debalina Chakravarty

    (Indian Institute of Management (IIM) Calcutta)

Abstract

Electric Street Car (ESC) has established itself as an ideal public transport system for urban agglomeration by offering better safety, minimum pollution and conservation of fossil fuel. Yet, India envisions going all-electric by 2030 by procuring electric buses (e-buses) rather than ESCs. The crucial question is, why not upgrade the existing ESC considering that the e-buses need a profound infrastructural development in India. This paper studies the potential uptake rate of ESC over e-buses using stratified sampling data from 1226 daily public transport commuters of Kolkata, the only Indian city having an operational ESCs. We identify the demographic, psychometric and socio-economic factors influencing the probabilistic uptake of ESC over e-buses using a random utility choice model. It estimates that 38% of the commuters demand ESC over e-buses given the alternatives’ comparative details. ESC can be a model electric public transport if there is an improvement in factors, like frequent availability of ESCs and technological upgradation. By promoting the ESC services over e-buses, the government can potentially save on public investment and reach a low carbon pathway cost-effectively. The findings have crucial implications in exploration of the operational feasibility of ESC in the small and medium-sized cities of developing economies like India.

Suggested Citation

  • Oindrila Dey & Debalina Chakravarty, 2020. "Electric Street Car as a Clean Public Transport Alternative: A Choice Experiment Approach," Working Papers 2042, Indian Institute of Foreign Trade.
    • Handle: RePEc:ift:wpaper:2042
    as

    Download full text from publisher

    File URL: ftp://203.190.248.10/RePEc/ift/workingpapers/EC-20-42.pdf
    File Function: First version, 2020
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Lin, Boqiang & Du, Zhili, 2017. "Can urban rail transit curb automobile energy consumption?," Energy Policy, Elsevier, vol. 105(C), pages 120-127.
    2. Walker, Joan & Ben-Akiva, Moshe, 2002. "Generalized random utility model," Mathematical Social Sciences, Elsevier, vol. 43(3), pages 303-343, July.
    3. J. R. DeShazo, 2016. "Improving Incentives for Clean Vehicle Purchases in the United States: Challenges and Opportunities," Review of Environmental Economics and Policy, Association of Environmental and Resource Economists, vol. 10(1), pages 149-165.
    4. Armstrong, J. Scott & Morwitz, Vicki G. & Kumar, V., 2000. "Sales forecasts for existing consumer products and services: Do purchase intentions contribute to accuracy?," International Journal of Forecasting, Elsevier, vol. 16(3), pages 383-397.
    5. Cai, Zhen & Xie, Yi & Aguilar, Francisco X., 2017. "Eco-label credibility and retailer effects on green product purchasing intentions," Forest Policy and Economics, Elsevier, vol. 80(C), pages 200-208.
    6. Brownstone, David & Bunch, David S. & Train, Kenneth, 2000. "Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 34(5), pages 315-338, June.
    7. Cecere, Grazia & Corrocher, Nicoletta & Guerzoni, Marco, 2018. "Price or performance? A probabilistic choice analysis of the intention to buy electric vehicles in European countries," Energy Policy, Elsevier, vol. 118(C), pages 19-32.
    8. William J. Infosino, 1986. "Forecasting New Product Sales from Likelihood of Purchase Ratings," Marketing Science, INFORMS, vol. 5(4), pages 372-384.
    9. Feng Xie & David Levinson, 2009. "Modeling the Growth of Transportation Networks: A Comprehensive Review," Networks and Spatial Economics, Springer, vol. 9(3), pages 291-307, September.
    10. Bagozzi, Richard P. & Yi, Youjae & Nassen, Kent D., 1998. "Representation of measurement error in marketing variables: Review of approaches and extension to three-facet designs," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 393-421, November.
    11. Daniel L. McFadden, 1976. "Quantal Choice Analysis: A Survey," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 363-390, National Bureau of Economic Research, Inc.
    12. Richard Carson & Theodore Groves, 2007. "Incentive and informational properties of preference questions," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 37(1), pages 181-210, May.
    13. Adamowicz W. & Louviere J. & Williams M., 1994. "Combining Revealed and Stated Preference Methods for Valuing Environmental Amenities," Journal of Environmental Economics and Management, Elsevier, vol. 26(3), pages 271-292, May.
    14. Brownstone, David & Bunch, David S. & Train, Kenneth, 2000. "Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 34(5), pages 315-338, June.
    15. Jonathan Bendor & Dilip Mookherjee & Debraj Ray, 2001. "Aspiration-Based Reinforcement Learning In Repeated Interaction Games: An Overview," International Game Theory Review (IGTR), World Scientific Publishing Co. Pte. Ltd., vol. 3(02n03), pages 159-174.
    16. Langbroek, Joram H.M. & Franklin, Joel P. & Susilo, Yusak O., 2017. "When do you charge your electric vehicle? A stated adaptation approach," Energy Policy, Elsevier, vol. 108(C), pages 565-573.
    17. Langbroek, Joram H.M. & Franklin, Joel P. & Susilo, Yusak O., 2016. "The effect of policy incentives on electric vehicle adoption," Energy Policy, Elsevier, vol. 94(C), pages 94-103.
    18. Dorina Pojani & Dominic Stead, 2015. "Sustainable Urban Transport in the Developing World: Beyond Megacities," Sustainability, MDPI, vol. 7(6), pages 1-22, June.
    19. Leibowicz, Benjamin D., 2018. "Policy recommendations for a transition to sustainable mobility based on historical diffusion dynamics of transport systems," Energy Policy, Elsevier, vol. 119(C), pages 357-366.
    20. Amil Petrin & Kenneth Train, 2003. "Omitted Product Attributes in Discrete Choice Models," NBER Working Papers 9452, National Bureau of Economic Research, Inc.
    21. Louise M. Hassan & Edward Shiu & Deirdre Shaw, 2016. "Who Says There is an Intention–Behaviour Gap? Assessing the Empirical Evidence of an Intention–Behaviour Gap in Ethical Consumption," Journal of Business Ethics, Springer, vol. 136(2), pages 219-236, June.
    22. Bendor Jonathan & Mookherjee Dilip & Ray Debraj, 2001. "Reinforcement Learning in Repeated Interaction Games," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 1(1), pages 1-44, March.
    23. Stephane Hess & Andrew Daly & Richard Batley, 2018. "Revisiting consistency with random utility maximisation: theory and implications for practical work," Theory and Decision, Springer, vol. 84(2), pages 181-204, March.
    24. Ben-Akiva, Moshe & McFadden, Daniel & Train, Kenneth, 2019. "Foundations of Stated Preference Elicitation: Consumer Behavior and Choice-based Conjoint Analysis," Foundations and Trends(R) in Econometrics, now publishers, vol. 10(1-2), pages 1-144, January.
    25. Sun, Baohong & Morwitz, Vicki G., 2010. "Stated intentions and purchase behavior: A unified model," International Journal of Research in Marketing, Elsevier, vol. 27(4), pages 356-366.
    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. Manoj Pant & Sugandha Huria, 2022. "Technological Change and Demographics in a model where consumption is time-constrained," Working Papers 2259, Indian Institute of Foreign Trade.
    2. Nivedita Mullick & Areej A. Siddiqui, 2021. "Economic Integration Agreements and Extensive Margin of Export: An Empirical Study of India," Working Papers 2155, Indian Institute of Foreign Trade.

    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. Haghani, Milad & Bliemer, Michiel C.J. & Rose, John M. & Oppewal, Harmen & Lancsar, Emily, 2021. "Hypothetical bias in stated choice experiments: Part I. Macro-scale analysis of literature and integrative synthesis of empirical evidence from applied economics, experimental psychology and neuroimag," Journal of choice modelling, Elsevier, vol. 41(C).
    2. 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).
    3. Milad Haghani & Michiel C. J. Bliemer & John M. Rose & Harmen Oppewal & Emily Lancsar, 2021. "Hypothetical bias in stated choice experiments: Part I. Integrative synthesis of empirical evidence and conceptualisation of external validity," Papers 2102.02940, arXiv.org.
    4. Milad Haghani & Michiel C. J. Bliemer & John M. Rose & Harmen Oppewal & Emily Lancsar, 2021. "Hypothetical bias in stated choice experiments: Part II. Macro-scale analysis of literature and effectiveness of bias mitigation methods," Papers 2102.02945, arXiv.org.
    5. Richard T. Carson, 2011. "Contingent Valuation," Books, Edward Elgar Publishing, number 2489.
    6. Cecere, Grazia & Corrocher, Nicoletta & Guerzoni, Marco, 2018. "Price or performance? A probabilistic choice analysis of the intention to buy electric vehicles in European countries," Energy Policy, Elsevier, vol. 118(C), pages 19-32.
    7. Helveston, John Paul & Feit, Elea McDonnell & Michalek, Jeremy J., 2018. "Pooling stated and revealed preference data in the presence of RP endogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 109(C), pages 70-89.
    8. Haghani, Milad & Bliemer, Michiel C.J. & Rose, John M. & Oppewal, Harmen & Lancsar, Emily, 2021. "Hypothetical bias in stated choice experiments: Part II. Conceptualisation of external validity, sources and explanations of bias and effectiveness of mitigation methods," Journal of choice modelling, Elsevier, vol. 41(C).
    9. B. Douglas Bernheim & Daniel Bjorkegren & Jeffrey Naecker & Antonio Rangel, 2013. "Non-Choice Evaluations Predict Behavioral Responses to Changes in Economic Conditions," NBER Working Papers 19269, National Bureau of Economic Research, Inc.
    10. Richard T. Carson & Miko_aj Czajkowski, 2014. "The discrete choice experiment approach to environmental contingent valuation," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 9, pages 202-235, Edward Elgar Publishing.
    11. Kim, Junghun & Seung, Hyunchan & Lee, Jongsu & Ahn, Joongha, 2020. "Asymmetric preference and loss aversion for electric vehicles: The reference-dependent choice model capturing different preference directions," Energy Economics, Elsevier, vol. 86(C).
    12. Tamara L. Sheldon & J. R. DeShazo & Richard T. Carson, 2017. "Electric And Plug-In Hybrid Vehicle Demand: Lessons For An Emerging Market," Economic Inquiry, Western Economic Association International, vol. 55(2), pages 695-713, April.
    13. Michael P. Keane & Nada Wasi, 2013. "The Structure of Consumer Taste Heterogeneity in Revealed vs. Stated Preference Data," Economics Papers 2013-W10, Economics Group, Nuffield College, University of Oxford.
    14. Hasselwander, Marc & Bigotte, Joao F. & Antunes, Antonio P. & Sigua, Ricardo G., 2022. "Towards sustainable transport in developing countries: Preliminary findings on the demand for mobility-as-a-service (MaaS) in Metro Manila," Transportation Research Part A: Policy and Practice, Elsevier, vol. 155(C), pages 501-518.
    15. 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.
    16. Adelina Gschwandtner & Jose Eduardo Ribeiro & Cesar Revoredo-Giha & Michael Burton, 2021. "Combining Stated and Revealed Preferences for valuing Organic Chicken Meat," Studies in Economics 2113, School of Economics, University of Kent.
    17. Makena Coffman & Paul Bernstein & Sherilyn Wee, 2017. "Electric vehicles revisited: a review of factors that affect adoption," Transport Reviews, Taylor & Francis Journals, vol. 37(1), pages 79-93, January.
    18. Bergantino, Angela Stefania & Bolis, Simona, 2004. "An analysis of maritime ro-ro freight transport service attributes through adaptive stated preference: an application to a sample of freight forwarders," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 25-26, pages 33-51.
    19. Aurélie Glerum & Lidija Stankovikj & Michaël Thémans & Michel Bierlaire, 2014. "Forecasting the Demand for Electric Vehicles: Accounting for Attitudes and Perceptions," Transportation Science, INFORMS, vol. 48(4), pages 483-499, November.
    20. Li, Zili & Washington, Simon P. & Zheng, Zuduo & Prato, Carlo G., 2023. "A Bayesian hierarchical approach to the joint modelling of Revealed and stated choices," Journal of choice modelling, Elsevier, vol. 47(C).

    More about this item

    Keywords

    Public Transport; Electric Bus; Electric Street Car; Sustainability; Urban Area;
    All these keywords.

    JEL classification:

    • R58 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Regional Development Planning and Policy
    • R49 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Other
    • Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:ift:wpaper:2042. 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: S. Balasubramanian (email available below). General contact details of provider: https://edirc.repec.org/data/iifttin.html .

    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.