DECODING BEHAVIORAL INTENTIONS TOWARDS AUTONOMOUS VEHICLES: A META-ANALYSIS AND EMPIRICAL STUDY
Keywords:
Autonomous Vehicles (Avs), Behavioral Intentions, Technology Acceptance, Meta-Framework, Adoption PatternsAbstract
This article presents a comprehensive analysis of behavioral intentions towards autonomous vehicles (AVs), addressing a critical gap in understanding AV adoption. Through a systematic review of existing literature, we develop a meta-framework that synthesizes previous findings and identifies key research gaps. Our article reveals distinct patterns of behavioral intention based on personal technology innovativeness. Innovative users are influenced by both utilitarian and hedonic factors, while laggards are primarily motivated by hedonic aspects. Importantly, technological fears, particularly data privacy concerns, significantly impact innovative users' intentions, whereas laggards experience more generalized technological anxiety. The article also explores the relationship between individual intentions and anticipated societal outcomes, such as equal mobility opportunities. Our findings highlight the crucial role of moderating variables in shaping AV adoption patterns and offer valuable insights for researchers and practitioners in the autonomous vehicle industry. This article contributes to the growing body of literature on AV acceptance and provides a foundation for future studies in this rapidly evolving field.
References
S. A. Cohen and D. Hopkins, "Autonomous vehicles and the future of urban tourism," Annals of Tourism Research, vol. 74, pp. 33-42, 2019. [Online]. Available: https://doi.org/10.1016/j.annals.2018.10.009
S. Nordhoff, J. de Winter, M. Kyriakidis, B. van Arem and R. Happee, "Acceptance of Driverless Vehicles: Results from a Large Cross-National Questionnaire Study," Journal of Advanced Transportation, vol. 2018, Article ID 5382192, 22 pages, 2018, doi: 10.1155/2018/5382192. [Online]. Available: https://www.hindawi.com/journals/jat/2018/5382192/
V. Venkatesh, J. Y. L. Thong, and X. Xu, "Unified Theory of Acceptance and Use of Technology: A Synthesis and the Road Ahead," Journal of the Association for Information Systems, vol. 17, no. 5, pp. 328-376, 2016. [Online]. Available: https://aisel.aisnet.org/jais/vol17/iss5/1/
F. Becker and K. W. Axhausen, "Literature review on surveys investigating the acceptance of automated vehicles," Transportation, vol. 44, pp. 1293-1306, 2017. [Online]. Available: https://doi.org/10.1007/s11116-017-9808-9
D. Moher et al., "Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement," PLoS Medicine, vol. 6, no. 7, e1000097, 2009. [Online]. Available: https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1000097
M. Borenstein, L. V. Hedges, J. P. T. Higgins, and H. R. Rothstein, "Introduction to Meta-Analysis," John Wiley & Sons, 2021. [Online]. Available: https://www.wiley.com/en-us/Introduction+to+Meta+Analysis%2C+2nd+Edition-p-9781119558354
J. Henseler, C. M. Ringle, and M. Sarstedt, "A new criterion for assessing discriminant validity in variance-based structural equation modeling," Journal of the Academy of Marketing Science, vol. 43, no. 1, pp. 115-135, 2015. [Online]. Available: https://link.springer.com/article/10.1007/s11747-014-0403-8
M. Ghazizadeh, J. D. Lee, and L. N. Boyle, "Extending the Technology Acceptance Model to assess automation," Cognition, Technology & Work, vol. 14, no. 1, pp. 39-49, 2012. [Online]. Available: https://link.springer.com/article/10.1007/s10111-011-0194-3
F. D. Davis, R. P. Bagozzi, and P. R. Warshaw, "User Acceptance of Computer Technology: A Comparison of Two Theoretical Models," Management Science, vol. 35, no. 8, pp. 982-1003, 1989. [Online]. Available: https://pubsonline.informs.org/doi/abs/10.1287/mnsc.35.8.982
E. M. Rogers, "Diffusion of Innovations," 5th ed. New York: Free Press, 2003. [Online]. Available: https://books.google.com/books?id=9U1K5LjUOwEC
