A study on psychological determinants of users' autonomous vehicles adoption from anthropomorphism and UTAUT perspectives

Abstract

As the autonomous vehicles technology gradually enters the public eye, understanding consumers' psychological motivations for accepting autonomous vehicles is critical for the development of autonomous vehicles and society. Previously, researchers have explored the determinants of fully autonomous vehicles but the relevant research is far from enough. Moreover, the relationship between anthropomorphism and users' behavior has been ignored to a large extent. Therefore, this study aim to fill the gap by using anthropomorphism and the unified theory of acceptance and use of technology (UTAUT) to explore how system attributes (i.e., perceived anthropomorphism, perceived intelligence) and UTAUT attributes influence consumers' acceptance behavior. The data were collected via questionnaire survey conducted in Beijing, China, which can be a promising early adopter of AVs. Structural equation modeling was used to analyze the data. The results reveal that perceived anthropomorphism and perceived intelligence have a direct positive influence on the adoption of AVs; performance expectancy, effort expectancy, and facilitating conditions have an indirect positive influence on intention to adopt AVs. Also, this research contributes to the literature by enriching studies on psychological determinants of autonomous vehicles' adoption by taking an initial step to highlight anthropomorphism perceptions. This can provide managerial implications for policy-makers and businesses on how to effectively allocate resources to enhance autonomous vehicle adoption.

Extended TAM based acceptance of AI-Powered ChatGPT for supporting metacognitive self-regulated learning in education: A mixed-methods study

“…Perceived AI Intelligence (PAI) and Metacognitive Self-Regulated Learning (MSR): The survey strongly supported this hypothesis, demonstrating that perceived AI intelligence strongly affects instructors' MSR [ 95 ]. In interviews, educators said AI's intelligence helped them encourage self-regulated learning.…”

Investigating the intention of purchasing private pension scheme based on an integrated FBM-UTAUT model: The case of China

“…According to earlier research, people are more likely to embrace and keep using new technology if they see that it has benefits that outweigh its drawbacks ( Venkatesh et al, 2003 , 2012 ). Additionally, numerous research findings indicate that PE has a significant impact on people’s propensity to use certain products or services ( Williams et al, 2015 ; Hoque and Sorwar, 2017 ; Chao, 2019 ; Nan et al, 2022 ; Tian and Wang, 2022 ). For example, Chao (2019) reported a study on the use of mobile learning on the basis of the UTAUT model, and the author showed that PE has a significantly positive impact on behavioral intention with a coefficient of 0.18.…”

“… Nan et al (2022) studied the intention of using face recognition payment and also found a positive effect of PE on behavioral intention with a coefficient of 0.27. Tian and Wang (2022) found that the intention to adopt autonomous vehicles could be indirectly influenced by performance expectancy through perceived value. On the other hand, the antecedents of PE are in fact less understood, and existing studies have clearly indicated that risk and trust are two important factors determining behavioral intentions in various finance-related contexts ( Gu et al, 2009 ; Slade et al, 2015 ; Kaur and Arora, 2020 ; Nan et al, 2022 ).…”

Psychological factors affecting potential users’ intention to use autonomous vehicles

“…It is extremely important to carry out research on users' psychological factors [39]. Although research on user behavior of driverless cars has gradually attracted attention, the psychological factors were focused on only in a small number of previous studies [35,40,41].…”

“…Although there are many current studies investigating users' behavioral intentions for autonomous vehicles, they are still not comprehensive [39]. The current research on the behavioral intention of autonomous vehicles has problems such as the use motivation is not unified [58].…”