The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles
Abstract
Abstract We 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 attributes. The mixed logit models provide improved fits over logit that are highly significant, and show large heterogeneity in respondents' preferences for alternative-fuel vehicles. The effects of including this heterogeneity are demonstrated in forecasting exercises. The alternative-fuel vehicle models presented here also highlight the advantages of merging SP and revealed preference (RP) data. RP data appear to be critical for obtaining realistic body-type choice and scaling information, but they are plagued by multicollinearity and difficulties with measuring vehicle attributes. SP data are critical for obtaining information about attributes not available in the marketplace, but pure SP models with these data give implausible forecasts.
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Cites
Mixed MNL models for discrete response
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Self-citationUsing stated response choice data to enrich revealed preference discrete choice models
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A transactions choice model for forecasting demand for alternative-fuel vehicles
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Discrete Choice Methods with Simulation
Train, K. E. (2001) · doi:10.1017/cbo9780511805271 · Cited by 7,784
Self-citationThe Mixed Logit model: The state of practice
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The influence of financial incentives and other socio-economic factors on electric vehicle adoption
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Willingness to pay for electric vehicles and their attributes
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Metadata
- Authors
- Brownstone, D., Bunch, D. S., & Train, K.
- Venue
- Transportation Research Part B: Methodological
- Publisher
- Elsevier BV
- Published
- 2000-06
- Volume
- 34
- Issue
- 5
- Pages
- 315-338
- ISSN
- 0191-2615 (ISSN-L)
- OpenAlex
- W2237681562
- Cited by
- 747
- References
- 13
- FWCI
- 29.71
- Type
- journal article
- Language
- en
- Open access
- closed
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