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An estimation of the future adoption rate of autonomous trucks by freight organizations

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  • Simpson, Jesse R.
  • Mishra, Sabyasachee
  • Talebian, Ahmadreza
  • Golias, Mihalis M.

Abstract

This paper presents a model to estimate the future adoption of connected autonomous trucks (CATs) by freight transportation organizations. An accurate estimation of the market penetration rate of CATs is necessary to adequately prepare the infrastructure and legislation needed to support the technology. Building upon the theory of Diffusion of Innovations, we develop Bass models for various freight transportation innovations, including improved tractor and trailer aerodynamics, and anti-idling technologies for trucks. The proposed model accounts for heterogeneity between organizations by using a modified Bass model to vary parameters within a designated range for each of the potentially adopting organizations. The results of the paper are Bass models for existing freight organization innovation adoption and estimates of multiple scenarios of CAT adoption over time by freight organizations within the case study region of Shelby County, Tennessee and provide a foundation for organizational innovation adoption research. Our analyses suggest that the market penetration rate of CATs within 25 years varies from nearly universal adoption (i.e., more than 95%) to 20% or less depending on the rate at which autonomous technology improves over time, changes in public opinion on autonomous technology, and the addition of external influencing factors such as price and marketing.

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  • Simpson, Jesse R. & Mishra, Sabyasachee & Talebian, Ahmadreza & Golias, Mihalis M., 2019. "An estimation of the future adoption rate of autonomous trucks by freight organizations," Research in Transportation Economics, Elsevier, vol. 76(C).
  • Handle: RePEc:eee:retrec:v:76:y:2019:i:c:s0739885919302495
    DOI: 10.1016/j.retrec.2019.100737
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    Cited by:

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    2. Schuster, Amy M. & Agrawal, Shubham & Britt, Noah & Sperry, Danielle & Van Fossen, Jenna A. & Wang, Sicheng & Mack, Elizabeth A. & Liberman, Jessica & Cotten, Shelia R., 2023. "Will automated vehicles solve the truck driver shortages? Perspectives from the trucking industry," Technology in Society, Elsevier, vol. 74(C).
    3. Simone Pettigrew & Leon Booth & Victoria Farrar & Branislava Godic & Julie Brown & Charles Karl & Jason Thompson, 2022. "Walking in the Era of Autonomous Vehicles," Sustainability, MDPI, vol. 14(17), pages 1-13, August.
    4. Kishore Bhoopalam, A. & van den Berg, R. & Agatz, N.A.H. & Chorus, C.G., 2021. "The long road to automated trucking: Insights from driver focus groups," ERIM Report Series Research in Management ERS-2021-003-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    5. Sharma, Ishant & Mishra, Sabyasachee, 2022. "Quantifying the consumer’s dependence on different information sources on acceptance of autonomous vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 179-203.
    6. Catherine Taylor & Robert Waschik, 2022. "Evaluating the impact of automation in long-haul trucking using USAGE-Hwy," Centre of Policy Studies/IMPACT Centre Working Papers g-326, Victoria University, Centre of Policy Studies/IMPACT Centre.
    7. Engholm, Albin & Kristoffersson, Ida & Pernestal, Anna, 2021. "Impacts of large-scale driverless truck adoption on the freight transport system," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 227-254.
    8. Talebian, Ahmadreza & Mishra, Sabyasachee, 2022. "Unfolding the state of the adoption of connected autonomous trucks by the commercial fleet owner industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    9. Simpson, Jesse R. & Mishra, Sabyasachee, 2021. "Developing a methodology to predict the adoption rate of Connected Autonomous Trucks in transportation organizations using peer effects," Research in Transportation Economics, Elsevier, vol. 90(C).

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    More about this item

    Keywords

    Connected autonomous trucks; Organizational adoption; Diffusion of innovations; Freight transportation; Market penetration predictions;
    All these keywords.

    JEL classification:

    • R42 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government and Private Investment Analysis; Road Maintenance; Transportation Planning

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