What we know and do not know about connected and autonomous vehicles

Rashidi, Taha Hossein; Najmi, Ali; Haider, Ahsan; Wang, Charlotte; Hosseinzadeh, Fatemeh

doi:10.1080/23249935.2020.1720860

Cited by 26 publications

(13 citation statements)

References 117 publications

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“…With ongoing technological advances in automation and connectivity, several studies have been discussed concerning IoV-based services in recent years that have concentrated on different issues [1,17], such as the concept of IoV [18,19], architecture (four layers including vehicle network environment sensing and control layer, network access and transport layer, coordinative computing control layer, and application layer) [20,21], and key technologies for IoV [22,23], as well as barriers and determinants of IoV-based services and vehicles adoption [24,25]. Numerous studies have investigated key factors for consumers' willingness-to-pay (WTP) and the adoption of IoV-based services and vehicles from the perspectives of various innovation adoption theories [6,26].…”

Section: Introductionmentioning

confidence: 99%

User Acceptance of Internet of Vehicles Services: Empirical Findings of Partial Least Square Structural Equation Modeling (PLS-SEM) and Fuzzy Sets Qualitative Comparative Analysis (fsQCA)

Liang

Zhang

et al. 2020

Mobile Information Systems

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Recently, IoV-based services and vehicles have come to the forefront as part of the growing market for the automobile industry. Since IoV-based services and vehicles were introduced, they have been expected to grow rapidly. However, contrary to optimistic expectations for future market growth, the IoV-based services and vehicles market has appeared to hit a roadblock and remains at an early market stage. Therefore, research of the determinants leading to consumers’ intention to accept and purchase IoV-based services and vehicles is significant for either academics or practitioners. Drawing upon the extended unified theory of acceptance and use of technology acceptance model (UTAUT2), the perceived risk theory, and the initial trust model, we developed an integrated conceptual model and explored what and how various determinant antecedent conditions fit together on consumer intention to accept IoV-based services and vehicles. The proposed model and hypotheses were assessed by both symmetric (partial least square structural equation modeling, PLS-SEM) and asymmetric (fsQCA) approaches using online survey datasets with 362 Chinese consumers. The findings suggest that PLS-SEM and fsQCA are complementary analytical techniques providing comparable results. PLS-SEM results indicate that performance expectancy, price value, habit, and initial trust have significant effects on behavioral intention to accept IoV services. Despite other determinants, e.g., effort expectancy, social influence, facilitating conditions, hedonic motivation, and perceived risk, have no significant effect. FsQCA results reveal twelve different configurations of determinants resulting in a high level of behavioral intention to accept IoV services, and eight causal paths equifinally leading to the negation of behavioral intention to accept IoV services. These findings suggest that several conditions that were not significant in PLS-SEM are sufficient conditions when combined with other conditions. This study enriches relevant research studies on IoV-based services acceptance and provides relevant insights and marketing suggestions for incentivizing consumers to accept the IoV-based services.

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Section: Introductionmentioning

confidence: 99%

User Acceptance of Internet of Vehicles Services: Empirical Findings of Partial Least Square Structural Equation Modeling (PLS-SEM) and Fuzzy Sets Qualitative Comparative Analysis (fsQCA)

Liang

Zhang

et al. 2020

Mobile Information Systems

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“…In addition, the analysis has made it possible to cluster these concepts in groups of thematically related keywords, helping researchers to grasp the bigger picture. The higher level of detail that this paper offers also becomes evident when comparing the keyword-topic-theme correlations embedded in each thematic cluster with the manually labelled co-citation clusters identified by Rashidi et al. (2020) , whose thematic focus is defined by using single keywords rather than a group of complementary sub-information systems of latent variables.…”

Section: Discussionmentioning

confidence: 94%

“…Recent developments in AV have raised information overload concerns ( Cavazza et al., 2019 ; Gandia et al., 2019 ; Rashidi et al., 2020 ). The interest of research institutions in examining the largely unknown socio-cultural, environmental, economic, and technological implications of vehicle automation has grown conspicuously over the years, especially during the last decade.…”

Section: Latent Knowledge Discovery In Av Research: a Multi-granulatimentioning

confidence: 99%

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Mind the gap: Developments in autonomous driving research and the sustainability challenge

Mora

Guo

Panori³

2020

Journal of Cleaner Production

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Scientific knowledge on autonomous-driving technology is expanding at a faster-than-ever pace. As a result, the likelihood of incurring information overload is particularly notable for researchers, who can struggle to overcome the gap between information processing requirements and information processing capacity. We address this issue by adopting a multi-granulation approach to latent knowledge discovery and synthesis in large-scale research domains. The proposed methodology combines citation-based community detection methods and topic modelling techniques to give a concise but comprehensive overview of how the autonomous vehicle (AV) research field is conceptually structured. Thirteen core thematic areas are extracted and presented by mining the large data-rich environments resulting from 50 years of AV research. The analysis demonstrates that this research field is strongly oriented towards examining the technological developments needed to enable the widespread rollout of AVs, whereas it largely overlooks the wide-ranging sustainability implications of this sociotechnical transition. On account of these findings, we call for a broader engagement of AV researchers with the sustainability concept and we invite them to increase their commitment to conducting systematic investigations into the sustainability of AV deployment. Sustainability research is urgently required to produce an evidence-based understanding of what new sociotechnical arrangements are needed to ensure that the systemic technological change introduced by AV-based transport systems can fulfill societal functions while meeting the urgent need for more sustainable transport solutions.

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“…With the Fourth Industrial Revolution ongoing, more and more systems are being automated. This overall trend across industrial sectors has also led to intense activity in various transportation modes to develop and implement autonomous transport systems [1]. Regardless if one decides to call it automation or autonomy [2], the key defining features of these developments is the increased implementation of digital functions, the extensive interconnectivity, along with hardware and software making decisions and performing tasks (including safety-critical ones) without the direct control of a human operator.…”

Section: Introductionmentioning

confidence: 99%

A Cross-Domain Scientometric Analysis of Situational Awareness of Autonomous Vehicles With Focus on the Maritime Domain

Bogusllwski

Nasur

et al. 2022

IEEE Access

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Highly automated vehicles are making their way towards implementation in many modes of transportation, including shipping. From the safety perspective, it is critically important that such vehicles or the operators overseeing them maintain their sense of the environment, also referred to as situational awareness. The present study investigates the worldwide research effort focusing on situational awareness for autonomous transport and explores how the maritime domain could benefit from it. The results indicate that most of the research originates from the automotive, but the topic is developing fast in other transportation modes too. Some findings have been shared across the modes of transportation, but only to a limited extent. Although technology development is performed based on the achievements within basic research domains, there has been little feedback from applied sciences. Similarly, collaborative research is not strongly developed.

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What we know and do not know about connected and autonomous vehicles

Cited by 26 publications

References 117 publications

User Acceptance of Internet of Vehicles Services: Empirical Findings of Partial Least Square Structural Equation Modeling (PLS-SEM) and Fuzzy Sets Qualitative Comparative Analysis (fsQCA)

User Acceptance of Internet of Vehicles Services: Empirical Findings of Partial Least Square Structural Equation Modeling (PLS-SEM) and Fuzzy Sets Qualitative Comparative Analysis (fsQCA)

Mind the gap: Developments in autonomous driving research and the sustainability challenge

A Cross-Domain Scientometric Analysis of Situational Awareness of Autonomous Vehicles With Focus on the Maritime Domain

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