Autonomous vehicles can be shared, but a feeling of ownership is important: Examination of the influential factors for intention to use autonomous vehicles
Introduction
Autonomous vehicles have great potential for improving the safety and efficiency of transportation. With minimized human intervention and optimized traffic control systems, autonomous vehicles can lead to a new transportation environment with less traffic and safer driving. Over the last decades, autonomous vehicles have been a conceptual idea. However, advances in artificial intelligence and real-time data processing technologies have enabled the development of practical autonomous vehicles. Early autonomous vehicles were only able to recognize and handle some driving situations, but these limitations have been removed due to continued technological advances. Several vehicle companies, including Ford, Honda, Toyota, Nissan, Volvo, Hyundai, Daimler, Fiat-Chrysler, and BMW, are developing autonomous vehicles and have plans to release full-automation vehicles (i.e., vehicles that can drive without any human intervention) starting in 2021 (Walker, 2018).
With ongoing technological advances in autonomous vehicles, several researchers have investigated influential factors for vehicle adoption. Merat et al. (2012) suggested that the reliability of autonomous vehicles may be a crucial factor affecting adoption. Verberne et al. (2012) suggested that trust is a crucial psychological factor when considering the acceptability of automation technologies in automobiles. Choi and Ji (2015) showed that trust was a major construct determining users’ willingness to adopt autonomous vehicles. Finally, Ward et al. (2017) found that perceptions of risk and benefit, knowledge, and trust were related to the intention to use automated vehicles.
Although these studies have suggested various factors that influence the potential adoption of autonomous vehicles, influential factors for autonomous vehicle adoption still need to be investigated further from two perspectives. First, factors related to the technology acceptance model need to be reexamined by considering the context of autonomous vehicles in more detail. Many previous studies have addressed factors that influence the technology acceptance model, but these reports are often inconsistent due to the different considerations of underlying structures. Reviewing the existing studies of autonomous vehicles and reorganizing the relationships of the factors can yield meaningful insights related to the use of autonomous vehicles. Second, psychological factors influencing the use of autonomous vehicles also need to be examined accordingly. When reconstructing influential factors in the technology acceptance model, several psychological factors related to the use of autonomous vehicles can be examined together, thereby extending the understanding of users’ perceptions of autonomous vehicles.
Based on these issues, this study reviews previous studies related to autonomous vehicles and identifies the relationships between factors that need to be examined. By reviewing the identified factors in detail, we design a structural equation model and examine how users perceive the properties of autonomous vehicles when determining their potential use of autonomous vehicles. Based on the findings from existing studies and this study, we aim to provide more detailed information related to users’ perceptions of autonomous vehicles, as well as the influential factors determining an individual’s intention to use autonomous vehicles.
Section snippets
A brief review of previous studies
Numerous studies have investigated factors that influence the potential use of autonomous vehicles and suggested that safety, environmental concerns, relative advantage, compatibility, subjective norms, and self-efficacy can be considered influential factors for intention to use of autonomous vehicles (Gkartzonikas and Gkritza, 2019). We reviewed previous studies which addressed influential factors for autonomous vehicles based on a theoretical framework of technology acceptance and provided
Perceived ease of use and perceived usefulness
Previous studies of TAM have considered three core factors: perceived ease of use, perceived usefulness, and intention to use. However, these reports have been inconsistent. For example, some studies reported that all of the relationships were significant (e.g., Panagiotopoulos and Dimitrakopoulos, 2018, Wu et al., 2019) but other studies reported that only some relationships were significant (e.g., Buckley et al., 2018, Choi and Ji, 2015, Hein et al., 2018). Choi and Ji (2015) found that
Data collection
To examine the hypotheses of the developed research model, we designed a questionnaire consisting of 28 items to measure seven constructs. The items were adapted from previous studies and modified according to the context of autonomous vehicles. Table 2 shows the constructs and questionnaire items considered in this study.
The questionnaire was provided to 313 Korean respondents who were recruited from the research panel of Macromill Embrain, an online survey company with the largest panel in
Structural equation modeling
To identify the underlying structure of the items, we conducted a factor analysis based on respondent data. Because the examined items were designed to measure seven constructs in previous studies (i.e., PEOU, PU, ITU, PR, RA, SE, and PO), we considered that the number of constructs in factor analysis should be seven (Matsunaga, 2010). Also, through iterative checking of communalities and factor scores for seven constructs, we excluded 5 items from the analysis (PEOU4, PU3, ITU2, PR4, PO2) and
Discussion
It is an autonomous vehicle. The matter is how useful it is rather than how easy it is to use.
The original technology acceptance model assumed that the perceived ease of use affected the perceived usefulness, and both factors affect the intention to use (Davis, 1989, Davis et al., 1989). However, among previous studies looking into autonomous vehicles, which examined all of these relationships, only Panagiotopoulos and Dimitrakopoulos (2018) reported that all of the relationships were
Limitations of this study
To help grasp the results and findings of this study in more detail, three limitations need to be stated. First, although statistical tests showed that the examined constructs were acceptable in terms of reliability and validity, some of the constructs were measured by items less than three (i.e., intention to use) and presented high correlations. Thus, future studies can consider different sets of items for the constructs and further improve the reliability and validity of the findings in this
Conclusion
In this study, we examined influential factors for intention to use autonomous vehicles. Relationships between seven factors (i.e., perceived usefulness, perceived ease of use, intention to use, perceived risk, relative advantage, self-efficacy, and psychological ownership) were examined using structural equation modeling. Our results showed that perceived usefulness, self-efficacy, perceived risk, and psychological ownership can be significant factors that affect intention to use autonomous
Acknowledgements
This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2019S1A5A8035093).
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP; Ministry of Science, ICT & Future Planning) (NRF-2017R1C 1B 1003650).
References (61)
The theory of planned behavior
Organ. Behav. Hum. Decis. Process.
(1991)- et al.
Psychosocial factors associated with intended use of automated vehicles: a simulated driving study
Accid. Anal. Prev.
(2018) - et al.
A critical assessment of potential measurement biases in the technology acceptance model: three experiments
Int. J. Hum Comput. Stud.
(1996) - et al.
Factors affecting the adoption of vehicle sharing systems by young drivers
Transp. Pol.
(2013) - et al.
Predicting e-services adoption: a perceived risk facets perspective
Int. J. Hum. Comput. Stud.
(2003) - et al.
What have we learned? A review of stated preference and choice studies on autonomous vehicles
Transport. Res. Part C: Emerg. Technol.
(2019) - et al.
Not fearless, but self-enhanced: the effects of anxiety on the willingness to use autonomous cars depend on individual levels of self-enhancement
Technol. Forecast. Soc. Chang.
(2017) - et al.
A meta-analysis of the technology acceptance model
Inform. Manage.
(2006) - et al.
Users’ resistance towards radical innovations: the case of the self-driving car
Transport. Res. Part F: Traffic Psychol. Behav.
(2017) - et al.
Public opinion on automated driving: results of an international questionnaire among 5000 respondents
Transport. Res. Part F: Traffic Psychol. Behav.
(2015)
Road tests of self-driving vehicles: affective and cognitive pathways in acceptance formation
Transport. Res. Part A: Pol. Pract.
What influences the decision to use automated public transport? Using UTAUT to understand public acceptance of automated road transport systems
Transport. Res. Part F: Traffic Psychol. Behav.
Policy and society related implications of automated driving: a review of literature and directions for future research
J. Intell. Transport. Syst.
Antecedent variables of intentions to use an autonomous shuttle: moving beyond TAM and TPB?
Revue Européenne de Psychologie Appliquée/Europ Rev Appl Psychol
An empirical investigation on consumers’ intentions towards autonomous driving
Transport. Res. Part C: Emerg. Technol.
Intention to use a fully automated car: attitudes and a priori acceptability
Transport. Res. Part F: Traffic Psychol. Behav.
Car sharing as a means to raise acceptance of electric vehicles: an empirical study on regime change in automobility
Transport. Res. Part F: Traffic Psychol. Behav.
The mind in the machine: anthropomorphism increases trust in an autonomous vehicle
J. Exp. Soc. Psychol.
The role of environmental concern in the public acceptance of autonomous electric vehicles: a survey from China
Transport. Res. Part F: Traffic Psychol. Behav.
What drives people to accept automated vehicles? Findings from a field experiment
Transport. Res. Part C: Emerg. Technol.
Self-efficacy mechanism in human agency
Am. Psychol.
Self-efficacy conception of anxiety
Anxiety Res.
Literature review on surveys investigating the acceptance of automated vehicles
Transportation
sCARy! Risk perceptions in autonomous driving: the influence of experience on perceived benefits and barriers
Risk Anal.
The Essentials of Factor Analysis
Commentary: issues and opinion on structural equation modeling
MIS Quarterly
Investigating the importance of trust on adopting an autonomous vehicle
Int. J. Human-Comput. Interact.
Computer self-efficacy: development of a measure and initial test
MIS Quarterly
Perceived usefulness, perceived ease of use, and user acceptance of information technology
MIS Quarterly
User acceptance of computer technology: a comparison of two theoretical models
Manage. Sci.
Cited by (141)
Shared versus pooled automated vehicles: Understanding behavioral intentions towards adopting on-demand automated vehicles
2024, Travel Behaviour and SocietyThe impact of people's subjective perception on their acceptance of automated vehicles: A meta-analysis
2024, Transportation Research Part F: Traffic Psychology and BehaviourPricing strategies of a battery swapping servicefor electric vehicles
2024, Transportation Research Part D: Transport and EnvironmentDriving forward together: The common intention of Indonesians in different residential areas to use autonomous vehicles
2024, Transportation Research Interdisciplinary PerspectivesExploring university students’ acceptability of autonomous vehicles and urban air mobility
2024, Journal of Air Transport Management