Consumers’ Preferences for Domestic Lithium Content in Electric Vehicles: A U.S. Discrete Choice Experiment

Published: 22 April 2026| Version 3 | DOI: 10.17632/fmyd5785k3.3
Contributors:
, Bruktawit Ahmed,

Description

Despite substantial research on consumer preferences for electric vehicle (EV) performance, limited studies explicitly model preferences for domestic sourcing of battery minerals. We administer a discrete choice experiment to a nationally representative online sample of 1,200 U.S. respondents, incorporating the location of lithium mining and refining as key attributes. We randomly assign respondents to one of four information conditions: environmental impacts of lithium mining, emissions from refining, economic benefits of mining, or a control group. Mixed logit results reveal measurable but heterogeneous willingness to pay (WTP) for domestic sourcing. In the full sample, respondents are willing to pay approximately $29 per percentage-point increase in domestically mined lithium and $1,613 for domestic refining. Respondents exposed to positive information about economic benefits of mining are willing to pay $59 per percentage-point increase in domestic mining and $2,226 for domestic refining, whereas the control group does not exhibit a statistically significant valuation for these sourcing attributes. Respondents exposed to negative information about lithium refining show WTP of $25 and $1,609, respectively. These results suggest that information framing shapes preferences: positive information increases WTP for domestic sourcing, and negative information lowers but does not reverse preference for domestic sourcing. The findings highlight the importance of supply-chain transparency and informational context in shaping EV consumer preferences.

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Steps to reproduce

To reproduce all results, users should run the provided Stata do-file in Stata/MP 18. The do-file contains all commands required to replicate the analyses and outputs reported in the study.

Categories

Environmental Science, Environmental Economics, Energy Economics, Lithium Battery, Decision Making, Electric Vehicles

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