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What does Tesla mean to car buyers? Exploring the role of automotive brand in perceptions of battery electric vehicles

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  • Long, Zoe
  • Axsen, Jonn
  • Miller, Inger
  • Kormos, Christine

Abstract

Among the broad literature on consumer research of battery electric vehicles (BEVs), the role of brand perceptions is neglected. Consumers may gravitate towards automotive brands that they are accustomed to (“brand loyalty”), or they might prefer a new brand (i.e., Tesla) for being new and innovative (“pioneer brand advantage”). Further, BEV-supportive policies may indirectly favor or disfavor the BEVs produced by a given brand. We explore consumer perceptions of automotive brand perceptions in general, and for the specific case of Tesla, using survey data from a representative sample of 2123 Canadian new vehicle-buyers collected in 2017. Respondents most frequently associate BEVs with Tesla (27%), Toyota (27%), and Chevrolet (26%). Over two-thirds of respondents are familiar with Tesla, and 40% select Tesla as a brand representing the “future of BEVs”. In contrast, when asked which brand they would prefer to buy a BEV from, responses are more evenly spread across several brands, with 30% of respondents selecting a brand they already own. Of Tesla-familiar respondents, most indicate that Tesla has influenced them to perceive BEVs as more innovative, stylish, and environmentally-beneficial. Respondents have stronger image associations with Tesla, relative to BEVs more generally, and such perceptions are statistically associated with stated interest in purchasing a BEV. These exploratory findings indicate the potential importance of brand in shaping consumer perceptions of BEVs. Tesla in particular may have played a role in developing positive perceptions of BEVs, suggesting that it might be desirable for policy to support such a brand.

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  • Long, Zoe & Axsen, Jonn & Miller, Inger & Kormos, Christine, 2019. "What does Tesla mean to car buyers? Exploring the role of automotive brand in perceptions of battery electric vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 185-204.
    • Handle: RePEc:eee:transa:v:129:y:2019:i:c:p:185-204
    DOI: 10.1016/j.tra.2019.08.006
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    References listed on IDEAS

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    3. Wang, Guoqiang & Tan, Garry Wei-Han & Yuan, Yunpeng & Ooi, Keng-Boon & Dwivedi, Yogesh K., 2022. "Revisiting TAM2 in behavioral targeting advertising: A deep learning-based dual-stage SEM-ANN analysis," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
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    7. Wei, Hongqian & Zhang, Nan & Liang, Jun & Ai, Qiang & Zhao, Wenqiang & Huang, Tianyi & Zhang, Youtong, 2022. "Deep reinforcement learning based direct torque control strategy for distributed drive electric vehicles considering active safety and energy saving performance," Energy, Elsevier, vol. 238(PB).
    8. Han‐Chung Chou & Shiu‐Wan Hung & Wen‐Min Lu, 2022. "Exploring competition efficiency of automobile brands: An extensional data envelopment analysis‐metafrontier framework," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(1), pages 206-218, January.
    9. Kowalska-Pyzalska, Anna & Michalski, Rafał & Kott, Marek & Skowrońska-Szmer, Anna & Kott, Joanna, 2022. "Consumer preferences towards alternative fuel vehicles. Results from the conjoint analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
    10. Cruz-Jesus, Frederico & Figueira-Alves, Hugo & Tam, Carlos & Pinto, Diego Costa & Oliveira, Tiago & Venkatesh, Viswanath, 2023. "Pragmatic and idealistic reasons: What drives electric vehicle drivers' satisfaction and continuance intention?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 170(C).
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