The determinants of public acceptance of autonomous vehicles: An innovation diffusion perspective

Yuen, Kum Fai; Wong, Yiik Diew; Ma, Fei; Wang, Xueqin

doi:10.1016/j.jclepro.2020.121904

Cited by 162 publications

(105 citation statements)

References 52 publications

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“…Therefore, the remaining hypotheses are accepted (i.e., H 4a , H 4b , H 5a , H 5b , H 6a , H 6b , H 7a and H 7b ). The cognitive components are represented by relative advantage, compatibility and complexity which are constructs obtained from the innovation diffusion framework [50]. The affective component is reflected by hedonic motivation.…”

Section: Structural Model Analysismentioning

confidence: 99%

Understanding Public Acceptance of Autonomous Vehicles Using the Theory of Planned Behaviour

Yuen

Chua

Wang

et al. 2020

IJERPH

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Public acceptance of autonomous vehicles (AVs) is vital for a society to reap their intended benefits such as reduced traffic accidents, land usage, congestion and environmental pollution. The purpose of this paper is to use the theory of planned behaviour to pinpoint and examine the components affecting public acceptance of AVs. A model consisting of a network of hypothesised relationships is introduced. Thereafter, 526 residents in Seoul, Korea, were given a survey created for this research. Subsequently, to evaluate the collected information and estimate the model, structural equation modelling was adopted. The outcomes show individuals’ mindset on AVs, subjective customs, and behavioural influence directly influencing the acceptance of AVs. Furthermore, cognitive and emotive factors, namely comparative advantage, compatibility, complexity and hedonic motivation indirectly influence the acceptance of AVs via mindset and behavioural manipulation. Based on analysing the cumulative effect, attitude emerged with the strongest effect on public acceptance of autonomous vehicles. After this is, in decreasing order of influence, behavioural control, relative advantage, subjective norms, compatibility, hedonic motivation and complexity. The findings of this study implicate the prioritisation and allocation of resources, and policies relating to marketing, education, subsidisation and infrastructure development to better public acceptance of AVs.

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Section: Structural Model Analysismentioning

confidence: 99%

Understanding Public Acceptance of Autonomous Vehicles Using the Theory of Planned Behaviour

Yuen

Chua

Wang

et al. 2020

IJERPH

Self Cite

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“…Table 5 displays a matrix of the AVE, correlations and squared correlations of the variables. The AVE of the latent variables ranged between from 0.54 to 0.76, higher than the recommended cut-off value of 0.5 [ 54 , 55 , 56 , 57 ]. This suggests that variations in the indicators have a higher explanatory power through their latent variables rather than their errors.…”

Section: Resultsmentioning

confidence: 73%

Factors Influencing the Adoption of Shared Autonomous Vehicles

Yuen

Huyen

Wang

et al. 2020

IJERPH

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Shared autonomous vehicles (SAVs), which have several potential benefits, are an emerging innovative technology in the market. However, the successful operation of SAVs largely depends on the extent of travellers’ intention to adopt them. This study aims to analyse the factors that influence the adoption of SAVs by integrating two theoretical perspectives: the unified theory of acceptance and use of technology 2 (UTAUT2) and the theory of planned behaviour (TPB). A valid survey sample of 268 participants in Da Nang, Vietnam was collected. Subsequently, structural equation modelling was deployed to test the research model. The results indicate that the five dimensions of UTUAT2: performance expectation, effort expectation, habit, price value and hedonic motivation, are mediated by the attitudes toward using SAVs. Further, the TPB constructs, namely attitude, subject norm, perceived behavioural control, along with its perceived facilitating conditions, are all effective predictors of intention to use SAVs. The findings of this study can serve as a crucial resource for transport operators and the government to enhance transportation services and policies.

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“…Second, some of the findings and discussions might be idiosyncratic to the automotive sector and only to a limited extent transferrable to other contexts. Besides, developments like autonomous driving and mobility services are still in pretty early stages and are associated with high future uncertainty (Hörcher & Graham, 2020; Yuen, Wong, Ma, & Wang, 2020). Although these issues have been addressed in the analysis and discussion, it might be insightful to examine incumbents' differentiation engagements in sustainability transitions in other industries, such as retail and energy, given the quite different industry natures.…”

Section: Discussionmentioning

confidence: 99%

Fun to drive? The dynamics of car manufacturers' differentiation strategies

Hoeft

2021

Strategic Change

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Car manufacturers attempt to differentiate through a combination of technological and nontechnological differentiators, motivated by varying degrees of sustainability and competitive advantage rationale across first movers and followers. This paper investigates how differentiation efforts disseminate from individual firms to industry‐wide engagements and why some firms decide to move first. The case of incumbent car manufacturers is used to shed light on how and why firms differentiate and how differentiation links to the sustainability transition of the industry. The research highlights that car manufacturers attempt to differentiate through a combination of technological and nontechnological differentiators, motivated by varying degrees of sustainability and competitive advantage rationale across first movers and followers. A first‐mover advantage is particularly evident in technological differentiators.

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The determinants of public acceptance of autonomous vehicles: An innovation diffusion perspective

Cited by 162 publications

References 52 publications

Understanding Public Acceptance of Autonomous Vehicles Using the Theory of Planned Behaviour

Understanding Public Acceptance of Autonomous Vehicles Using the Theory of Planned Behaviour

Factors Influencing the Adoption of Shared Autonomous Vehicles

Fun to drive? The dynamics of car manufacturers' differentiation strategies

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