Factors influencing autonomous vehicle adoption: an application of the technology acceptance model and innovation diffusion theory
Kum Fai Yuen, Lanhui Cai, Guanqiu Qi, Xueqin Wang
Abstract
Kum Fai Yuen, Lanhui Cai, Guanqiu Qi, Xueqin Wang
Abstract
Autonomous vehicles (AVs) are a key transportation technology of the future and will be integral to smart cities. An increased understanding of user adoption is necessary to promote AV usage. This study applied an integrated model based on innovation diffusion theory (IDT) and the technology acceptance model (TAM) to examine the factors influencing a user’s behavioural intention to use AVs. Then, a questionnaire was designed, and structural equation analysis was conducted on the 274 collected survey results. Results confirmed previous research findings that perceived usefulness (PU) and perceived ease of use (PEOU) positively influence users’ behavioural intention to use AVs. Moreover, the results revealed new findings that both PU and PEOU were influenced by the perceived characteristics of innovation (PCIs, i.e. relative advantage, compatibility, image, result demonstrability, visibility, and trialability). These findings contribute to theory building concerning human–computer interactions and guide policy and strategy formulation for promoting AVs.
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Autonomous vehicles (AVs) are a key transportation technology of the future and will be integral to smart cities. An increased understanding of user adoption is necessary to promote AV usage. This study applied an integrated model based on innovation diffusion theory (IDT) and the technology acceptance model (TAM) to examine the factors influencing a user’s behavioural intention to use AVs. Then, a questionnaire was designed, and structural equation analysis was conducted on the 274 collected survey results. Results confirmed previous research findings that perceived usefulness (PU) and perceived ease of use (PEOU) positively influence users’ behavioural intention to use AVs. Moreover, the results revealed new findings that both PU and PEOU were influenced by the perceived characteristics of innovation (PCIs, i.e. relative advantage, compatibility, image, result demonstrability, visibility, and trialability). These findings contribute to theory building concerning human–computer interactions and guide policy and strategy formulation for promoting AVs.
Key concepts: Technology acceptance model, Innovation diffusion, Structural equation modeling, Usability, Knowledge management, Diffusion of innovations, Diffusion theory, Computer science