The demand for conventional and vehicle-to-grid electric vehicles: A latent class random utility model

I estimated a Latent Class Random Utility Model of conventional and Vehicle-to-Grid electric vehicle choice using stated preference data. I used a web-based national sample to elicit consumer preference in a choice experiment format that includes the respondent's preferred gasoline vehicle and two electric versions of it. The latent class model allowed me to capture preference heterogeneity and identify the source of the heterogeneity. I found consumer preference for electric vehicles (EVs) can be grouped into two preference groups- those who have high proclivity towards EV and those who have low proclivity towards EVs. My analysis shows the primary drive for purchasing EVs is not only to save the environment, but also to save on fuel cost.;I used the model to simulate willingness to pay for several EV designs and found that people who have high interest in EVs are willing to pay substantial premium. However, these premiums are not enough to cover battery cost. My estimates show for EVs to compete on the market, battery costs have to decline from the current level of ;For the Vehicle-to-grid (V2G) EV model, I found people have high discount rate for revenue earned from V2G service and high inconvenience cost for long plug-in time and short guaranteed minimum driving range. These results suggest, for the concept of V2G to help EVs, V2G contract terms should be either completely eliminated or set at very flexible terms.