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Peer effect matters for the adoption of new energy vehicles: Evidence from consumer sentiment analysis using Chat-GPT

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  • Fu, Tong
  • Yu, Shuyi
  • Tan, Shiyu

Abstract

Although it is widely believed that reducing technological uncertainty can promote the adoption of new technologies, the mechanisms through which consumers perceive such reductions—and how these perceptions influence adoption decisions—remain underexplored. Utilizing Chat-GPT for sentiment analysis of online consumer reviews and treating consumer sentiment as a key measure of the peer effect, this study investigates the role of peer effects in mediating the causal relationship between technology uncertainty and the adoption of new energy vehicles (NEVs). The findings indicate that reducing technological uncertainty enhances both online word-of-mouth (active peer effects) and government procurement (passive peer effects), both of which facilitate greater NEVs adoption. Additionally, moderation effect analyses suggest that social trust amplifies the negative impact of technological uncertainty on NEV consumption intensity, thereby indirectly validating the role of peer effects in fostering NEV adoption. Ultimately, this research underscores that, even without government fiscal subsidies, peer effects can serve as a vital self-reinforcing mechanism in adopting green technologies.

Suggested Citation

  • Fu, Tong & Yu, Shuyi & Tan, Shiyu, 2025. "Peer effect matters for the adoption of new energy vehicles: Evidence from consumer sentiment analysis using Chat-GPT," Energy Economics, Elsevier, vol. 148(C).
    • Handle: RePEc:eee:eneeco:v:148:y:2025:i:c:s0140988325005195
    DOI: 10.1016/j.eneco.2025.108692
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