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Willingness to pay for the infrastructure investments for alternative fuel vehicles

Author

Listed:
  • Nobuyuki Ito

    (Graduate School of Agriculture, Kyoto University)

  • Kenji Takeuchi

    (Graduate School of Economics, Kobe University)

  • Shunsuke Managi

    (Graduate School of Environmental Studies, Tohoku University)

Abstract

This study investigates potential demand for infrastructure investment for alternative fuel vehicles (AFVs) by using a stated preference survey of 1,531 Japanese citizens. The potential demand is estimated on the basis of how much people are willing to pay for AFVs under different refueling scenarios. By using the estimated parameters, the economic efficiency of establishing battery exchange stations for electric vehicles is examined. The result indicates that infrastructural development of battery exchange stations can be socially efficient when the percentage of electric vehicle purchasers out of the total number of new vehicle purchasers exceeds 5.63%. Furthermore, in contrast to intuitive prediction, we found a complement relationship between the cruising ranges of AFVs and the infrastructures established. The result suggests that people with AFVs might change their total trip distance depending on the sufficiency of infrastructure investment.

Suggested Citation

  • Nobuyuki Ito & Kenji Takeuchi & Shunsuke Managi, 2012. "Willingness to pay for the infrastructure investments for alternative fuel vehicles," Discussion Papers 1207, Graduate School of Economics, Kobe University.
  • Handle: RePEc:koe:wpaper:1207
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    File URL: http://www.econ.kobe-u.ac.jp/RePEc/koe/wpaper/2012/1207.pdf
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    References listed on IDEAS

    as
    1. 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.
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    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. Hensher, David A. & Greene, William H., 2002. "Specification and estimation of the nested logit model: alternative normalisations," Transportation Research Part B: Methodological, Elsevier, vol. 36(1), pages 1-17, January.
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    Citations

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    Cited by:

    1. Milan Scasny & Milan Scasny & Iva Zverinova & Mikolaj Czajkowski, 2015. "Individual preference for the alternative fuel vehicles and their attributes in Poland," EcoMod2015 8575, EcoMod.
    2. Hackbarth, André & Madlener, Reinhard, 2011. "Consumer Preferences for Alternative Fuel Vehicles: A Discrete Choice Analysis," FCN Working Papers 20/2011, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    3. repec:spr:envpol:v:20:y:2018:i:1:d:10.1007_s10018-017-0181-x is not listed on IDEAS
    4. Pacharaporn Arkornsakul & Woraphon Yamaka & Sombat Singkharat, 2015. "Consumer?s Willingness to Pay for Gasohol E100 in Chiang Mai Province and Nakhon Ratchasima Province," Proceedings of International Academic Conferences 2704676, International Institute of Social and Economic Sciences.
    5. Ito, Yutaka & Managi, Shunsuke, 2015. "The potential of alternative fuel vehicles: A cost-benefit analysis," Research in Transportation Economics, Elsevier, vol. 50(C), pages 39-50.
    6. Hackbarth, André & Madlener, Reinhard, 2016. "Willingness-to-pay for alternative fuel vehicle characteristics: A stated choice study for Germany," Transportation Research Part A: Policy and Practice, Elsevier, vol. 85(C), pages 89-111.
    7. Byunghun Choi, 2016. "A Study on Limitation of Government Initiative Model for Alternative Fuel Vehicle (AFV) Promotion in China," Eurasian Journal of Social Sciences, Eurasian Publications, vol. 4(2), pages 66-84.

    More about this item

    Keywords

    Alternative fuel vehicle; infrastructure investment; stated preference method; choice experiment; discrete choice; nested logit model; cost-benefit analysis;

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