期望理论
自适应神经模糊推理系统
相容性(地球化学)
计算机科学
心理学
模糊逻辑
人工智能
社会心理学
工程类
模糊控制系统
化学工程
作者
Behzad Foroughi,Pham Viet Nhan,Mohammad Iranmanesh,Morteza Ghobakhloo,Mehrbakhsh Nilashi,Elaheh Yadegaridehkordi
标识
DOI:10.1016/j.jretconser.2022.103158
摘要
Artificial intelligence (AI)-powered autonomous vehicles (AVs) are one of the most disruptive technologies with potentially wide-ranging social implications, including improvements in passenger/driver safety, environmental protection, and equity considerations. The current research extends the UTAUT2 model in the context of fully AVs (level 5 automation) to determine and rank determinants of intention to adopt AVs. Collected data from 378 respondents were analysed by a hybrid approach employing partial least squares (PLS) complemented by the Adaptive Neuro-Fuzzy Inference Systems (ANFIS) technique. According to the findings, five major determinants emerged: trust, hedonic motivation, social influence, compatibility, and effort expectancy. Furthermore, compatibility positively moderates the association between performance expectancy and intention to use AVs. The findings shed light on determinant factors, their level of importance, and the potential interplay between them in shaping individuals' intention to adopt and use AVs. Furthermore, the current research provides valuable insights to carmakers, technology developers, and practitioners on determinants of AVs adoption, assisting them in devising effective AVs-related strategies.
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