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On the heterogeneity in consumer preferences for electric vehicles across generations and cities in China

journal contribution
posted on 25.02.2021, 12:05 by Youlin Huang, Lixian Qian, David Tyfield, Didier Soopramanien
China is currently the world's biggest electric vehicle (EV) market, in which mostly mature consumers in first-tier cities are buying EVs. However, the changing market and policy environment are challenging the sustainability of this trend. This study conducts a nationwide stated preference (SP) experiment in China to examine preference heterogeneity towards EVs across (1) different generations and (2) different tiers of cities. Discrete choice analysis reveals that the tier of cities has a significant effect on adoption preferences for EVs. Surprisingly, consumers in smaller cities exhibit stronger preference for EVs, while an insignificant difference in preference is found between consumers of different generations. The interaction effect between the tier of cities and the generations further demonstrates that younger consumers in small cities most prefer EVs. This can be explained by their evaluations of the psychosocial advantages of EVs and their aspiration for a future of EV-based mobility. This research contributes to the broad literature of technology adoption, but more specifically, the research offers new insights on consumers’ EV preference heterogeneity with respect to geographic and demographic dimensions. The study has important business and policy implications relating to the EV transition in China in consideration of the two tested dimensions.

Funding

National Natural Science Foundation of China (Grant No. 71573213 and 71973107)

History

School

  • Business and Economics

Department

  • Business

Published in

Technological Forecasting and Social Change

Volume

167

Publisher

Elsevier BV

Version

AM (Accepted Manuscript)

Rights holder

© Elsevier

Publisher 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.2021.120687.

Acceptance date

17/02/2021

Publication date

2021-02-24

Copyright date

2021

ISSN

0040-1625

Language

en

Depositor

Dr Didier Soopramanien. Deposit date: 24 February 2021

Article number

120687