The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
Toward Mass Adoption of Electric Vehicles: Impact of the Range and Resale Anxieties
Abstract
Key to the mass adoption of electric vehicles (EVs) is the establishment of successful business models based on sound understanding of consumer behavior in adopting this new technology. In this paper, we study the impact of two major barriers to mass adoption of EVs: (i) range anxiety, the concern that the driving range of EVs may be insufficient to meet the driving needs, and (ii) resale anxiety, the concern that used values of EVs may deteriorate quickly. Using a stylized model calibrated to a data set based on the San Francisco Bay Area, we show that although both types of consumer anxieties typically harm the firm’s profit, they often improve consumer surplus. In addition, we show that a business model that requires consumers to lease the EV batteries (rather than purchase them) may lead to a greater level of adoption and emission savings when the level of resale anxiety is high. Further, a business model that offers EV range improvement through enhanced charging infrastructure typically yields greater adoption and consumer surplus, but lowers the firm’s profit, compared with one that offers enlarged batteries. Overall, we find that the combinations of battery owning/leasing with enhanced charging service, referred to as the (O, E) and (L, E) models in our paper, typically yield the best balance among the objectives of EV adoption, emission savings, profitability, and consumer surplus, when the degree of resale anxiety is low and high, respectively.
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Adoption of electric vehicle: A literature review and prospects for sustainability
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Metadata
- Authors
- Lim, M. K., Mak, H.-Y., & Rong, Y.
- Venue
- Manufacturing & Service Operations Management
- Published
- 2015-02
- Volume
- 17
- Issue
- 1
- Pages
- 101-119
- ISSN
- 1523-4614 (ISSN-L)
- 1526-5498
- OpenAlex
- W3122885463
- Cited by
- 284
- References
- 32
- FWCI
- 4.60
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.