IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v196y2023ics0040162523005486.html
   My bibliography  Save this article

Sociotechnical expectations of vehicle automation in the UK trucking sector

Author

Listed:
  • Hopkins, Debbie
  • Schwanen, Tim

Abstract

Expectations about emerging innovations are an important part of innovation pathways that can help to overcome uncertainties and build hype. Such sociotechnical expectations have been studied extensively by social scientists but the focus is often on collective, widely shared expectations and much less on individuals' specific expectations. Examining the latter can nonetheless aid understanding of the development of, buy-in into and power dynamics around collective sociotechnical expectations. This paper therefore examines individually articulated expectations about vehicle automation in the trucking industry in the UK. It draws on 61 in-depth interviews with freight transport actors, including truck drivers, freight company management, industry representatives, and representative from government departments. It demonstrates alignment of individual expectations on some aspects of vehicle automation, including the difficulty of expression them in terms of chronological (calendar) time and the belief that automation will be quicker and easier on motorways than on other kinds of road. Multiple differences in expectations are identified, in particular regarding the practical feasibility of truck platooning and the role of truck drivers. In all cases, it is clear that individual expectations are shaped strongly by people's current and past professional experience and practices and how these have been affected by wider technological and organisational changes in the freight and logistics sector.

Suggested Citation

  • Hopkins, Debbie & Schwanen, Tim, 2023. "Sociotechnical expectations of vehicle automation in the UK trucking sector," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    • Handle: RePEc:eee:tefoso:v:196:y:2023:i:c:s0040162523005486
    DOI: 10.1016/j.techfore.2023.122863
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162523005486
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2023.122863?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Hopkins, Debbie & Schwanen, Tim, 2021. "Talking about automated vehicles: What do levels of automation do?," Technology in Society, Elsevier, vol. 64(C).
    2. Sindi, Safaa & Woodman, Roger, 2021. "Implementing commercial autonomous road haulage in freight operations: An industry perspective," Transportation Research Part A: Policy and Practice, Elsevier, vol. 152(C), pages 235-253.
    3. Korsnes, Marius, 2016. "Ambition and ambiguity: Expectations and imaginaries developing offshore wind in China," Technological Forecasting and Social Change, Elsevier, vol. 107(C), pages 50-58.
    4. 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.
    5. van Lente, Harro & Spitters, Charlotte & Peine, Alexander, 2013. "Comparing technological hype cycles: Towards a theory," Technological Forecasting and Social Change, Elsevier, vol. 80(8), pages 1615-1628.
    6. Kriechbaum, Michael & Posch, Alfred & Hauswiesner, Angelika, 2021. "Hype cycles during socio-technical transitions: The dynamics of collective expectations about renewable energy in Germany," Research Policy, Elsevier, vol. 50(9).
    7. Kriechbaum, Michael & López Prol, Javier & Posch, Alfred, 2018. "Looking back at the future: Dynamics of collective expectations about photovoltaic technology in Germany & Spain," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 76-87.
    8. Monios, Jason & Bergqvist, Rickard, 2020. "Logistics and the networked society: A conceptual framework for smart network business models using electric autonomous vehicles (EAVs)," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    9. Liu, Peng & Xu, Zhigang, 2020. "Public attitude toward self-driving vehicles on public roads: Direct experience changed ambivalent people to be more positive," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    10. Yap, Menno D. & Correia, Gonçalo & van Arem, Bart, 2016. "Preferences of travellers for using automated vehicles as last mile public transport of multimodal train trips," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 1-16.
    11. Dedehayir, Ozgur & Steinert, Martin, 2016. "The hype cycle model: A review and future directions," Technological Forecasting and Social Change, Elsevier, vol. 108(C), pages 28-41.
    12. Debbie Hopkins & Tim Schwanen, 2018. "Automated Mobility Transitions: Governing Processes in the UK," Sustainability, MDPI, vol. 10(4), pages 1-19, March.
    13. Liu, Peng, 2020. "Positive, negative, ambivalent, or indifferent? Exploring the structure of public attitudes toward self-driving vehicles on public roads," Transportation Research Part A: Policy and Practice, Elsevier, vol. 142(C), pages 27-38.
    14. Robert Martin, 2021. "AV futures or futures with AVs? Bridging sociotechnical imaginaries and a multi-level perspective of autonomous vehicle visualisations in praxis," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-15, December.
    15. Nicky Gregson, 2017. "Logistics at Work: Trucks, Containers and the Friction of Circulation in the UK," Mobilities, Taylor & Francis Journals, vol. 12(3), pages 343-364, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Williams, Laurence & Bergman, Noam, 2023. "Koomey's law forevermore? A document analysis of the production and circulation of the promise of ‘green 5G’," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    2. Li, Dun & Huang, Youlin & Qian, Lixian, 2022. "Potential adoption of robotaxi service: The roles of perceived benefits to multiple stakeholders and environmental awareness," Transport Policy, Elsevier, vol. 126(C), pages 120-135.
    3. Kriechbaum, Michael & Posch, Alfred & Hauswiesner, Angelika, 2021. "Hype cycles during socio-technical transitions: The dynamics of collective expectations about renewable energy in Germany," Research Policy, Elsevier, vol. 50(9).
    4. Kriechbaum, Michael & López Prol, Javier & Posch, Alfred, 2018. "Looking back at the future: Dynamics of collective expectations about photovoltaic technology in Germany & Spain," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 76-87.
    5. White, Gareth R.T. & Samuel, Anthony, 2019. "Programmatic Advertising: Forewarning and avoiding hype-cycle failure," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 157-168.
    6. Shi, Yuwei & Herniman, John, 2023. "The role of expectation in innovation evolution: Exploring hype cycles," Technovation, Elsevier, vol. 119(C).
    7. Cohen, Scott & Stienmetz, Jason & Hanna, Paul & Humbracht, Michael & Hopkins, Debbie, 2020. "Shadowcasting tourism knowledge through media: Self-driving sex cars?," Annals of Tourism Research, Elsevier, vol. 85(C).
    8. Weiss, Daniel & Nemeczek, Fabian, 2021. "A text-based monitoring tool for the legitimacy and guidance of technological innovation systems," Technology in Society, Elsevier, vol. 66(C).
    9. Jack Stilgoe & Miloš Mladenović, 2022. "The politics of autonomous vehicles," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-6, December.
    10. Uddin, Md Hamid & Mollah, Sabur & Ali, Md Hakim, 2020. "Does cyber tech spending matter for bank stability?," International Review of Financial Analysis, Elsevier, vol. 72(C).
    11. Jessica Mancilla-de-la-Cruz & Marisela Rodriguez-Salvador & Laura Ruiz-Cantu, 2020. "The Next Pharmaceutical Path: Determining Technology Evolution in Drug Delivery Products Fabricated with Additive Manufacturing," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 14(3), pages 55-70.
    12. Du, Manqing & Zhang, Tingru & Liu, Jinting & Xu, Zhigang & Liu, Peng, 2022. "Rumors in the air? Exploring public misconceptions about automated vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 156(C), pages 237-252.
    13. Dasom Lee & David J. Hess, 2022. "Public concerns and connected and automated vehicles: safety, privacy, and data security," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-13, December.
    14. Hashemi, Fariba & Gallay, Olivier & Hongler, Max-Olivier, 2021. "Opinion formation dynamics — Swift collective disillusionment triggered by unmet expectations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 569(C).
    15. Thomas Davenport & Abhijit Guha & Dhruv Grewal & Timna Bressgott, 2020. "How artificial intelligence will change the future of marketing," Journal of the Academy of Marketing Science, Springer, vol. 48(1), pages 24-42, January.
    16. Leminen, Seppo & Rajahonka, Mervi & Wendelin, Robert & Westerlund, Mika & Nyström, Anna-Greta, 2022. "Autonomous vehicle solutions and their digital servitization business models," Technological Forecasting and Social Change, Elsevier, vol. 185(C).
    17. Hopkins, Debbie & Schwanen, Tim, 2022. "Recruiting research participants for transport research: Reflections from studies on autonomous vehicles in the UK," Journal of Transport Geography, Elsevier, vol. 102(C).
    18. Alvarez León, Luis F. & Aoyama, Yuko, 2022. "Industry emergence and market capture: The rise of autonomous vehicles," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    19. Mejía, Cristian & Kajikawa, Yuya, 2019. "Technology news and their linkage to production of knowledge in robotics research," Technological Forecasting and Social Change, Elsevier, vol. 143(C), pages 114-124.
    20. Bjerkan, Kristin Ystmark & Ryghaug, Marianne, 2021. "Diverging pathways to port sustainability: How social processes shape and direct transition work," Technological Forecasting and Social Change, Elsevier, vol. 166(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:tefoso:v:196:y:2023:i:c:s0040162523005486. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.