Forecasting the Demand for Electric Vehicles: Accounting for Attitudes and Perceptions

Aurélie Glerum (), Lidija Stankovikj (), Michaël Thémans () and Michel Bierlaire ()
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Aurélie Glerum: École Polytechnique Fédérale de Lausanne (EPFL), School of Architecture, Civil and Environmental Engineering (ENAC), Transport and Mobility Laboratory (TRANSP-OR), Lausanne, Switzerland CH-1015
Lidija Stankovikj: École Polytechnique Fédérale de Lausanne (EPFL), School of Architecture, Civil and Environmental Engineering (ENAC), Transport and Mobility Laboratory (TRANSP-OR), Lausanne, Switzerland CH-1015
Michaël Thémans: École Polytechnique Fédérale de Lausanne (EPFL), Vice-Presidency for Technology Transfer (VPIV), Transportation Center (TRACE), Lausanne, Switzerland CH-1015
Michel Bierlaire: École Polytechnique Fédérale de Lausanne (EPFL), School of Architecture, Civil and Environmental Engineering (ENAC), Transport and Mobility Laboratory (TRANSP-OR), Lausanne, Switzerland CH-1015

Transportation Science, 2014, vol. 48, issue 4, 483-499

Abstract: In the context of the arrival of electric vehicles on the car market, new mathematical models are needed to understand and predict the impact on the market shares. This research provides a comprehensive methodology to forecast the demand of a technology that is not widespread yet, such as electric cars. It aims at providing contributions regarding three issues related to the prediction of the demand for electric vehicles: survey design, model estimation, and forecasting. We develop a stated preferences (SP) survey with personalized choice situations involving standard gasoline/diesel cars and electric cars. We specify a hybrid choice model accounting for attitudes toward leasing contracts or practical aspects of a car in the decision-making process. A forecasting analysis based on the collected SP data and additional market information is performed to evaluate the future demand for electric cars.

Keywords: electric vehicles; discrete-choice modeling; demand prediction; transportation; attitudes and perceptions; hybrid choice models; fractional factorial design (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (45)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ortrsc:v:48:y:2014:i:4:p:483-499

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