A Comparative Study on the Acceptance of Autonomous Driving Technology by China and Europe: A Cross-Cultural Empirical Analysis Based on the Technology Acceptance Model

As the global automobile industry undergoes rapid intelligent transformation, understanding public acceptance of autonomous driving emerges as a critical research challenge. This study adopts the Technology Acceptance Model (TAM) as its theoretical framework to conduct a comparative analysis between China and Europe, two major automotive markets and central arenas for the development of autonomous driving. It investigates how contextual factors—including policy support, infrastructure, social trust, and cultural values—influence acceptance patterns. The findings show that in China, strong policy guidance, rapid infrastructure deployment, and large-scale demonstration projects have substantially increased willingness to adopt, while the widespread use of L2-level systems has enhanced public familiarity with the technology. Nonetheless, high-profile accidents have also exposed vulnerabilities in public trust. In contrast, European consumers demonstrate a more cautious stance, emphasizing legal liability, data privacy, and ethical compliance, while simultaneously regarding autonomous driving as a means of achieving carbon reduction, traffic safety, and sustainable mobility. The results further indicate that in the European context, institutional guarantees and prior experience are decisive, with accident memory and institutional trust serving as critical moderators within TAM pathways.

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Publication Details

Journal
World Electric Vehicle Journal
Published
2025-10-22
DOI
https://doi.org/10.3390/wevj16110589
Primary Topic
Technology Adoption and User Behaviour
Type
article
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article

A Comparative Study on the Acceptance of Autonomous Driving Technology by China and Europe: A Cross-Cultural Empirical Analysis Based on the Technology Acceptance Model

Ling Peng, Dan Wan, Yifan Yang
World Electric Vehicle Journal
Technology Adoption and User Behaviour
article

A Comparative Study on the Acceptance of Autonomous Driving Technology by China and Europe: A Cross-Cultural Empirical Analysis Based on the Technology Acceptance Model

Ling Peng, Dan Wan, Yifan Yang
article en

Abstract

As the global automobile industry undergoes rapid intelligent transformation, understanding public acceptance of autonomous driving emerges as a critical research challenge. This study adopts the Technology Acceptance Model (TAM) as its theoretical framework to conduct a comparative analysis between China and Europe, two major automotive markets and central arenas for the development of autonomous driving. It investigates how contextual factors—including policy support, infrastructure, social trust, and cultural values—influence acceptance patterns. The findings show that in China, strong policy guidance, rapid infrastructure deployment, and large-scale demonstration projects have substantially increased willingness to adopt, while the widespread use of L2-level systems has enhanced public familiarity with the technology. Nonetheless, high-profile accidents have also exposed vulnerabilities in public trust. In contrast, European consumers demonstrate a more cautious stance, emphasizing legal liability, data privacy, and ethical compliance, while simultaneously regarding autonomous driving as a means of achieving carbon reduction, traffic safety, and sustainable mobility. The results further indicate that in the European context, institutional guarantees and prior experience are decisive, with accident memory and institutional trust serving as critical moderators within TAM pathways.

World Electric Vehicle JournalVol. 16(11)
Hunan Normal University (CN), Changsha Normal University (CN)
Openalex Percentile: Top 71%
Technology Adoption and User Behaviour
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A Comparative Study on the Acceptance of Autonomous Driving Technology by China and Europe: A Cross-Cultural Empirical Analysis Based on the Technology Acceptance Model — Ling Peng, Dan Wan, et al. · World Electric Vehicle Journal (2025) | TGRS Research Map | TGRS