IDEAS home Printed from https://ideas.repec.org/a/sae/ilrrev/v73y2020i1p3-24.html
   My bibliography  Save this article

Truck-Driving Jobs: Are They Headed for Rapid Elimination?

Author

Listed:
  • Maury Gittleman
  • Kristen Monaco

Abstract

The authors analyze the potential effects of automation on the jobs of truck drivers and conclude that media accounts predicting the imminent loss of millions of truck-driving jobs are overstated. Their conclusion is based on three main factors. First, the count of truck drivers is often inflated due to a misunderstanding of the occupational classification system used in federal statistics. Second, truck drivers do more than drive, and these non-driving tasks will continue to be in demand. Third, the requirements of technology, combined with complex regulations over how trucks can operate in the United States, imply that certain segments of trucking will be easier to automate than others. Long-haul trucking (which constitutes a minority of jobs) will be much easier to automate than will short-haul trucking (or the last mile), in which the bulk of employment lies. Although technology will likely transform the status quo in the trucking industry, it does not necessarily imply the wholesale elimination of the demand for truck drivers, as conventional accounts suggest.

Suggested Citation

  • Maury Gittleman & Kristen Monaco, 2020. "Truck-Driving Jobs: Are They Headed for Rapid Elimination?," ILR Review, Cornell University, ILR School, vol. 73(1), pages 3-24, January.
    • Handle: RePEc:sae:ilrrev:v:73:y:2020:i:1:p:3-24
    DOI: 10.1177/0019793919858079
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0019793919858079
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0019793919858079?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
    ---><---

    References listed on IDEAS

    as
    1. Melanie Arntz & Terry Gregory & Ulrich Zierahn, 2016. "The Risk of Automation for Jobs in OECD Countries: A Comparative Analysis," OECD Social, Employment and Migration Working Papers 189, OECD Publishing.
    2. Bronwyn H. Hall, 2004. "Innovation and Diffusion," NBER Working Papers 10212, National Bureau of Economic Research, Inc.
    3. Daron Acemoglu & Pascual Restrepo, 2017. "Robots and Jobs: Evidence from US Labor Markets," Boston University - Department of Economics - Working Papers Series dp-297, Boston University - Department of Economics.
    4. Erik Brynjolfsson & Tom Mitchell & Daniel Rock, 2018. "What Can Machines Learn, and What Does It Mean for Occupations and the Economy?," AEA Papers and Proceedings, American Economic Association, vol. 108, pages 43-47, May.
    5. Frey, Carl Benedikt & Osborne, Michael A., 2017. "The future of employment: How susceptible are jobs to computerisation?," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 254-280.
    6. David H. Autor, 2015. "Why Are There Still So Many Jobs? The History and Future of Workplace Automation," Journal of Economic Perspectives, American Economic Association, vol. 29(3), pages 3-30, Summer.
    7. Daron Acemoglu & Pascual Restrepo, 2020. "Robots and Jobs: Evidence from US Labor Markets," Journal of Political Economy, University of Chicago Press, vol. 128(6), pages 2188-2244.
    8. Burks, Stephen V. & Monaco, Kristen, 2018. "Is the U.S. Labor Market for Truck Drivers Broken? An Empirical Analysis Using Nationally Representative Data," IZA Discussion Papers 11813, Institute of Labor Economics (IZA).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).
    2. Burks, Stephen V. & Monaco, Kristen, 2018. "Is the U.S. Labor Market for Truck Drivers Broken? An Empirical Analysis Using Nationally Representative Data," IZA Discussion Papers 11813, Institute of Labor Economics (IZA).
    3. Burks, Stephen V. & Kildegaard, Arne & Miller, Jason W. & Monaco, Kristen, 2023. "When Is High Turnover Cheaper? A Simple Model of Cost Tradeoffs in a Long‐Distance Truckload Motor Carrier, with Empirical Evidence and Policy Implications," IZA Discussion Papers 16477, Institute of Labor Economics (IZA).
    4. Aniruddh Mohan & Parth Vaishnav, 2022. "Impact of automation on long haul trucking operator-hours in the United States," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-10, December.
    5. Daniel Silva & Liliana Cunha, 2022. "Aside from Deterministic Prophecies, What Is Missing in the Contemporary Debate on Automation and the Future of Work? The Case of Automated Vehicles," Social Sciences, MDPI, vol. 11(12), pages 1-29, December.
    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. Nassios, J. & Waschik, Robert & Dixon, P.B. & Rimmer, M., 2020. "Evaluating the impact of automation in long-haul trucking in the United States using USAGE-Hwy," Conference papers 333205, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    8. Ron Yang, 2022. "(Don’t) Take Me Home: Home Preference and the Effect of Self-Driving Trucks on Interstate Trade," NBER Chapters, in: Economics of Artificial Intelligence, National Bureau of Economic Research, Inc.
    9. 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.

    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. Fossen, Frank M. & Sorgner, Alina, 2019. "New Digital Technologies and Heterogeneous Employment and Wage Dynamics in the United States: Evidence from Individual-Level Data," IZA Discussion Papers 12242, Institute of Labor Economics (IZA).
    2. Wang, Huijuan & Ding, Lin & Guan, Rong & Xia, Yan, 2020. "Effects of advancing internet technology on Chinese employment: a spatial study of inter-industry spillovers," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    3. Manav Raj & Robert Seamans, 2018. "Artificial Intelligence, Labor, Productivity, and the Need for Firm-Level Data," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 553-565, National Bureau of Economic Research, Inc.
    4. Naude, Wim, 2019. "The race against the robots and the fallacy of the giant cheesecake: Immediate and imagined impacts of artificial intelligence," MERIT Working Papers 2019-005, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    5. Arntz, Melanie & Gregory, Terry & Zierahn, Ulrich, 2019. "Digitalization and the Future of Work: Macroeconomic Consequences," IZA Discussion Papers 12428, Institute of Labor Economics (IZA).
    6. Davide Dottori, 2021. "Robots and employment: evidence from Italy," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(2), pages 739-795, July.
    7. Giancarlo Cor? & Dejan Pejcic, 2018. "Cambiamento tecnologico e lavoro. gli impatti occupazionali di industria 4.0," ECONOMIA E SOCIET? REGIONALE, FrancoAngeli Editore, vol. 2018(1), pages 52-69.
    8. Nicola Cassandro & Marco Centra & Dario Guarascio & Piero Esposito, 2021. "What drives employment–unemployment transitions? Evidence from Italian task-based data," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 38(3), pages 1109-1147, October.
    9. Geiger, Niels & Prettner, Klaus & Schwarzer, Johannes A., 2018. "Automatisierung, Wachstum und Ungleichheit," Hohenheim Discussion Papers in Business, Economics and Social Sciences 13-2018, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    10. Genz, Sabrina & Bellmann, Lutz & Matthes, Britta, 2018. "Do German Works Councils Counter or Foster the Implementation of Digital Technologies?," IZA Discussion Papers 11616, Institute of Labor Economics (IZA).
    11. Crowley, Frank & Doran, Justin, 2019. "Automation and Irish Towns: Who's Most at Risk?," SRERC Working Paper Series SRERCWP2019-1, University College Cork (UCC), Spatial and Regional Economic Research Centre (SRERC).
    12. Cirillo, Valeria & Evangelista, Rinaldo & Guarascio, Dario & Sostero, Matteo, 2021. "Digitalization, routineness and employment: An exploration on Italian task-based data," Research Policy, Elsevier, vol. 50(7).
    13. Ben Vermeulen & Jan Kesselhut & Andreas Pyka & Pier Paolo Saviotti, 2018. "The Impact of Automation on Employment: Just the Usual Structural Change?," Sustainability, MDPI, vol. 10(5), pages 1-27, May.
    14. Lyu, Wenjing & Liu, Jin, 2021. "Artificial Intelligence and emerging digital technologies in the energy sector," Applied Energy, Elsevier, vol. 303(C).
    15. Fabian Stephany & Hanno Lorenz, 2021. "The Future of Employment Revisited: How Model Selection Determines Automation Forecasts," Papers 2104.13747, arXiv.org.
    16. Gries, Thomas & Naude, Wim, 2018. "Artificial intelligence, jobs, inequality and productivity: Does aggregate demand matter?," MERIT Working Papers 2018-047, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    17. Juan Ramón GARCÍA, 2018. "Galicia Ante Reto De La Automatización Del Trabajo," Revista Galega de Economía, University of Santiago de Compostela. Faculty of Economics and Business., vol. 27(3), pages 17-28.
    18. Damiani, Mirella & Pompei, Fabrizio & Kleinknecht, Alfred, 2020. "When robots do (not) enhance job quality: The role of innovation regimes," MPRA Paper 103059, University Library of Munich, Germany.
    19. Anderton, Robert & Jarvis, Valerie & Labhard, Vincent & Morgan, Julian & Petroulakis, Filippos & Vivian, Lara, 2020. "Virtually everywhere? Digitalisation and the euro area and EU economies," Occasional Paper Series 244, European Central Bank.
    20. Julia Bock-Schappelwein & Michael Böheim & Elisabeth Christen & Stefan Ederer & Matthias Firgo & Klaus S. Friesenbichler & Werner Hölzl & Mathias Kirchner & Angela Köppl & Agnes Kügler & Christine May, 2018. "Politischer Handlungsspielraum zur optimalen Nutzung der Vorteile der Digitalisierung für Wirtschaftswachstum, Beschäftigung und Wohlstand," WIFO Studies, WIFO, number 61256, April.

    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:sae:ilrrev:v:73:y:2020:i:1:p:3-24. 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: SAGE Publications (email available below). General contact details of provider: http://www.ilr.cornell.edu .

    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.