TFS_EV Business model paper_manuscript_20210115.pdf (697.11 kB)
Download fileBuy, lease, or share? Consumer preferences for innovative business models in the market for electric vehicles
journal contribution
posted on 2021-02-04, 09:02 authored by Youlin Huang, Lixian Qian, Didier Soopramanien, David TyfieldAlthough business models are critical to the successful market penetration and diffusion of sustainable innovations, little is known about consumer preferences for adopting electric vehicles (EVs) under innovative business models. Drawing on existing conceptualisations of business models, we study consumers’ preferences for three innovative EV business models: (i) battery-leasing, (ii) EV-leasing, and (iii) Business-to-Customer (B2C) EV-sharing, in addition to the conventional EV-buying model. By conducting a nationwide stated preference (SP) experiment in China, we show that consumers perceive battery-leasing and EV-buying models to be close substitutes, while EV-leasing and EV-sharing models are perceived as independent. Important monetary attributes are the operational cost saving in the battery-leasing model and the leasing cost in the EV-leasing model. Critical service and policy attributes include home charging capability, vehicle licensing policy, and the density of battery-swapping stations for the battery-leasing model. We also find that female consumers, those who are well-educated, and those who have a pro-EV attitude are most likely to adopt EVs in innovative business models. Our work has significant value for companies and government in terms of better designing and supporting the innovative business models for EV adoption.
Funding
National Natural Science Foundation of China (Grant No. 71573213, 71973107 and 71804149)
History
School
- Business and Economics
Department
- Business
Published in
Technological Forecasting and Social ChangeVolume
166Publisher
ElsevierVersion
- AM (Accepted Manuscript)
Rights holder
© ElsevierPublisher statement
This paper was accepted for publication in the journal Technological Forecasting and Social Change and the definitive published version is available at https://doi.org/10.1016/j.techfore.2021.120639.Acceptance date
2021-01-21Publication date
2021-02-06Copyright date
2021ISSN
0040-1625Publisher version
Language
- en