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Forecasting the Market for Electric Vehicles in California Using Conjoint Analysis

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  • Robin Segal

Abstract

Beginning in 1998 a percentage of large auto companies' sales in California must include zero-emission vehicles (ZEVs), which at this time art! synonymous with electric vehicles. Data on consumer values and the level of consumer acceptance for alternative fuel vehicles are necessary to determine the practicality of the State's policy. This paper presents the results of a forecast for alternative fuel vehicle purchases in California. This forecast uses conjoint analysis, a multi-attribute utility market forecast methodology developed within the field of marketing research. The forecast yields several types of results, including market simulations of the alternative fuel vehicle market, relative preferences among vehicle attributes, and the identification of market segments most likely to purchase each type of vehicle. The research suggests a market for electric vehicles too small to support California's ZEV sales mandate, and a very, large market for natural gas vehicles. This paper concludes with a discussion of automobile and electric utility industry interests with regard to these forecast market consequences.

Suggested Citation

  • Robin Segal, 1995. "Forecasting the Market for Electric Vehicles in California Using Conjoint Analysis," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 89-112.
    • Handle: RePEc:aen:journl:1995v16-03-a04
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    Cited by:

    1. Dimitropoulos, Alexandros & Rietveld, Piet & van Ommeren, Jos N., 2013. "Consumer valuation of changes in driving range: A meta-analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 55(C), pages 27-45.
    2. Golob, Thomas F. & Gould, Jane, 1998. "Projecting use of electric vehicles from household vehicle trials," Transportation Research Part B: Methodological, Elsevier, vol. 32(7), pages 441-454, September.
    3. John Bridges & Elizabeth Kinter & Lillian Kidane & Rebekah Heinzen & Colleen McCormick, 2008. "Things are Looking up Since We Started Listening to Patients," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 1(4), pages 273-282, October.
    4. Michaelis, Laurie, 1997. "Transport sector-strategies markets, technology and innovation," Energy Policy, Elsevier, vol. 25(14-15), pages 1163-1171, December.
    5. Soares, N. & Martins, A.G. & Carvalho, A.L. & Caldeira, C. & Du, C. & Castanheira, É. & Rodrigues, E. & Oliveira, G. & Pereira, G.I. & Bastos, J. & Ferreira, J.P. & Ribeiro, L.A. & Figueiredo, N.C. & , 2018. "The challenging paradigm of interrelated energy systems towards a more sustainable future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 95(C), pages 171-193.
    6. Takanori Ida & Kayo Murakami & Makoto Tanaka, 2012. "Keys to Smart Home Diffusion: A Stated Preference Analysis of Smart Meters, Photovoltaic Generation, and Electric/Hybrid Vehicles," Discussion papers e-11-011, Graduate School of Economics Project Center, Kyoto University.
    7. Robert W. Turner & Laura Noddin & Alita Giuda, 2005. "Estimating nonuse values using conjoint analysis," Economics Bulletin, AccessEcon, vol. 17(7), pages 1-15.
    8. Alexandros Dimitropoulos & Piet Rietveld & Jos N. van Ommeren, 2011. "Consumer Valuation of Driving Range: A Meta-Analysis," Tinbergen Institute Discussion Papers 11-133/3, Tinbergen Institute.
    9. repec:ebl:ecbull:v:17:y:2005:i:7:p:1-15 is not listed on IDEAS
    10. Kang, Min Jung & Park, Heejun, 2011. "Impact of experience on government policy toward acceptance of hydrogen fuel cell vehicles in Korea," Energy Policy, Elsevier, vol. 39(6), pages 3465-3475, June.
    11. Mourato, Susana & Saynor, Bob & Hart, David, 2004. "Greening London's black cabs: a study of driver's preferences for fuel cell taxis," Energy Policy, Elsevier, vol. 32(5), pages 685-695, March.
    12. Zhang, Xian & Wang, Ke & Hao, Yu & Fan, Jing-Li & Wei, Yi-Ming, 2013. "The impact of government policy on preference for NEVs: The evidence from China," Energy Policy, Elsevier, vol. 61(C), pages 382-393.
    13. Türnau, Marc, 2015. "Assessing the impact of long-term mobility choice motivation and short-term mobility means connotation on the use intention of electric cars in rural areas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 75(C), pages 16-29.
    14. Tanaka, Makoto & Ida, Takanori & Murakami, Kayo & Friedman, Lee, 2014. "Consumers’ willingness to pay for alternative fuel vehicles: A comparative discrete choice analysis between the US and Japan," Transportation Research Part A: Policy and Practice, Elsevier, vol. 70(C), pages 194-209.
    15. Michaelis, Laurie & Davidson, Ogunlade, 1996. "GHG mitigation in the transport sector," Energy Policy, Elsevier, vol. 24(10-11), pages 969-984.
    16. Yan, Jianghui & Tseng, Fang-Mei & Lu, Louis Y.Y., 2018. "Developmental trajectories of new energy vehicle research in economic management: Main path analysis," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 168-181.
    17. O'Garra, Tanya & Mourato, Susana & Garrity, Lisa & Schmidt, Patrick & Beerenwinkel, Anne & Altmann, Matthias & Hart, David & Graesel, Cornelia & Whitehouse, Simon, 2007. "Is the public willing to pay for hydrogen buses? A comparative study of preferences in four cities," Energy Policy, Elsevier, vol. 35(7), pages 3630-3642, July.

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    JEL classification:

    • F0 - International Economics - - General

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