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Accelerating the Adoption of Disruptive Technologies: The Impact of COVID-19 on Intentions to Use Autonomous Vehicles

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  • Maher Said
  • Emma R. Zajdela
  • Amanda Stathopoulos

Abstract

One of the most notable global transportation trends is the accelerated pace of development in vehicle automation technologies. Uncertainty surrounds the future of automated mobility as there is no clear consensus on potential adoption patterns, ownership versus shared use status and travel impacts. Adding to this uncertainty is the impact of the COVID-19 pandemic that has triggered profound changes in mobility behaviors as well as accelerated adoption of new technologies at an unprecedented rate. Accordingly, this study examines the impact of the COVID-19 pandemic on willingness to adopt the emerging technology of autonomous vehicles (AVs). Using data from a survey disseminated in June 2020 to 700 respondents in the United States, we perform a difference-in-difference regression to analyze the shift in willingness to use autonomous vehicles as part of a shared fleet before and during the pandemic. The results reveal that the COVID-19 pandemic has a positive and highly significant impact on the consideration of using autonomous vehicles. This shift is present regardless of tech-savviness, gender or urban/rural household location. Individuals who are younger, left-leaning and frequent users of shared modes of travel are expected to become more likely to use autonomous vehicles once offered. Understanding the effects of these attributes on the increase in consideration of AVs is important for policy making, as these effects provide a guide to predicting adoption of autonomous vehicles - once available - and to identify segments of the population likely to be more resistant to adopting AVs.

Suggested Citation

  • Maher Said & Emma R. Zajdela & Amanda Stathopoulos, 2021. "Accelerating the Adoption of Disruptive Technologies: The Impact of COVID-19 on Intentions to Use Autonomous Vehicles," Papers 2108.01615, arXiv.org, revised Dec 2021.
    • Handle: RePEc:arx:papers:2108.01615
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    References listed on IDEAS

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    1. Mohamed Alawadhi & Jumah Almazrouie & Mohammed Kamil & Khalil Abdelrazek Khalil, 2020. "A systematic literature review of the factors influencing the adoption of autonomous driving," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(6), pages 1065-1082, December.
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    4. Greene,William H. & Hensher,David A., 2010. "Modeling Ordered Choices," Cambridge Books, Cambridge University Press, number 9780521194204.
    5. Brem, Alexander & Viardot, Eric & Nylund, Petra A., 2021. "Implications of the coronavirus (COVID-19) outbreak for innovation: Which technologies will improve our lives?," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    6. Smith, Nicholas A. & Sabat, Isaac E. & Martinez, Larry R. & Weaver, Kayla & Xu, Shi, 2015. "A Convenient Solution: Using MTurk To Sample From Hard-To-Reach Populations," Industrial and Organizational Psychology, Cambridge University Press, vol. 8(2), pages 220-228, June.
    7. Kapser, Sebastian & Abdelrahman, Mahmoud & Bernecker, Tobias, 2021. "Autonomous delivery vehicles to fight the spread of Covid-19 – How do men and women differ in their acceptance?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 183-198.
    8. Ozili, Peterson & Arun, Thankom, 2020. "Spillover of COVID-19: Impact on the Global Economy," MPRA Paper 99317, University Library of Munich, Germany.
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    Cited by:

    1. Gibson, Samantha & Hsu, Maxwell K. & Zhou, Xing, 2022. "Convenience stores in the digital age: A focus on the customer experience and revisit intentions," Journal of Retailing and Consumer Services, Elsevier, vol. 68(C).

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