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Product Abstract

PRISM 2.0: Mixed Logit Consumer Vehicle Choice Modeling Using Revealed Preference Data

Product ID:3002001455
Date Published:30-Sep-2013
Sector Name:Environment
Document Type:Technical Results
Price:No Charge

This Product is publicly available

   807.66 KB - Adobe PDF (.pdf)


Predicting the penetration of electric vehicles into the automotive market is challenging because these vehicles do not exist in the market today and therefore consumer reaction is largely unknown. One way to estimate consumer demand for electric vehicles is to model the attribute bundles of vehicles that are present in the market today and predict market share using state-of-the-art discrete choice demand models.

This research develops a choice-based demand model to extract consumer preferences from data available on historic vehicle purchases (revealed preference data). The report begins with an introduction to the discrete choice models in Section 1, followed by a literature review leading to the choice of a mixed logit model for this analysis. Section 2 describes the methods used and presents sample results. Section 3 presents the results from several counterfactual analyses intended to “stress test” the model. The results indicate that the mixed logit model characterized in this study may be an effective tool for predicting market demand for future vehicle designs and configurations.


2010 Program 181   PRISM 2.0
  • Prism 2.0
  • Consumer preferences
  • Discrete choice models
  • Mixed logit
  • US-REGEN (U.S. Regional Economy
  • Greenhouse Gas
  • and Energy model)

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