JOINT MIXED LOGIT MODELS OF STATED AND REVEALED PREFERENCES FOR ALTERNATIVE-FUEL VEHICLES
infrastructure - vehicle, ridership - forecasting, ridership - forecasting, technology - alternative fuels
Vehicles by motive power, Travel by vehicle type, Scenarios, Road transportation, Projections, Multinomial logits, Motor vehicles, Mixed logit models, Logits, Logit models, Highway transportation, Forecasting, Consumers' preferences, Consumer preferences, Consumer behavior, Automotive vehicles, Alternative fuels, Alternate fuels
In this paper, the authors compare multinomial logit and mixed logit models for data on California households' revealed and stated preferences for automobiles. The stated preference (SP) data elicited households' preferences among gasoline, electric, methanol, and compressed natural gas vehicles with various features. The mixed logit models provide improved fits over logit that are highly significant, and show large heterogeneity in respondents' preferences for alternative-fuel vehicles (AFV). The effects of this heterogeneity are demonstrated in forecasting exercises. The AFV models presented here also highlight the advantages of merging SP and revealed preference (RP) data. RP data appears to be critical for obtaining realistic body-type choice and scaling information, but this data is plagued by multicollinearity and difficulties with measuring vehicle attributes. SP data is critical for obtaining information about attributes not available in the marketplace, but pure SP models with this data give implausible forecasts.
Brownstone, D, Bunch, D, Train, K, (2000). JOINT MIXED LOGIT MODELS OF STATED AND REVEALED PREFERENCES FOR ALTERNATIVE-FUEL VEHICLES. Transportation Research Part B: Methodological, Volume 34, Issue 5, p. 315-338.