IDEAS home Printed from https://ideas.repec.org/p/cdl/itsdav/qt20n8n4mb.html
   My bibliography  Save this paper

Determinants of Medium- and Heavy-Duty Truck Fleet Turnover

Author

Listed:
  • Kurani, Kenneth S
  • Miller, Marshall
  • Sugihara, Claire
  • Stepnitz, Eli-Alston
  • Nesbitt, Kevin A

Abstract

This study solicited information directly from decision-makers in private businesses operating fleets of medium- and heavy-duty trucks in California via interviews and pre-interview questionnaires. Additional interviews were conducted with truck manufacturers, consultants and other businesses providing services to the freight industry including leasing and auction. All these data were collected in 2021 and 2022. Fleet decision-makers describe what determines when and why they acquire and retire trucks and how they use those determinants. The purpose is to better understand vehicle turnover in the trucking sector. Direct contact with fleet decision-makers was preceded by a review of relevant literatures. This review helped in the design of joint questionnaires and interview protocols. Results are presented as 1) a set of determinants (internal to each fleet, external, and linking internal to external), 2) a typology based on decision-making structure, adaptation, and complexity, 3) case studies of decision-making types, 4) generalizations across fleets, and 5) extension to fleet consideration of alternative fuel trucks. One overarching conclusion is drawn: fleet truck turnover behavior varies widely—our highest-level abstraction—the typology—results in more than 20 types among 90 fleets allowing that some types involve mixed types of structure, adaptation, and/or complexity. Few fleets’ decision-making conforms to the commonly assumed model of total cost of ownership; many more do not. This report describes the varied ways fleets acquire and retire trucks, extends this to understand how this variety is already affecting freight fleets’ consideration of alternative fuel trucks, and poses questions as to how understanding this variety aids in promotion of zero-emission trucks.

Suggested Citation

  • Kurani, Kenneth S & Miller, Marshall & Sugihara, Claire & Stepnitz, Eli-Alston & Nesbitt, Kevin A, 2023. "Determinants of Medium- and Heavy-Duty Truck Fleet Turnover," Institute of Transportation Studies, Working Paper Series qt20n8n4mb, Institute of Transportation Studies, UC Davis.
  • Handle: RePEc:cdl:itsdav:qt20n8n4mb
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/20n8n4mb.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nesbitt, Kevin & Sperling, Daniel, 2001. "Fleet Purchase Behavior: Decision Processes and Implications for New Vehicle Technologies and Fuels," Institute of Transportation Studies, Working Paper Series qt15k63162, Institute of Transportation Studies, UC Davis.
    2. Askin, Amanda C. & Barter, Garrett E. & West, Todd H. & Manley, Dawn K., 2015. "The heavy-duty vehicle future in the United States: A parametric analysis of technology and policy tradeoffs," Energy Policy, Elsevier, vol. 81(C), pages 1-13.
    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. Pedro Gerber Machado & Ana Carolina Rodrigues Teixeira & Flavia Mendes de Almeida Collaço & Adam Hawkes & Dominique Mouette, 2020. "Assessment of Greenhouse Gases and Pollutant Emissions in the Road Freight Transport Sector: A Case Study for São Paulo State, Brazil," Energies, MDPI, vol. 13(20), pages 1-26, October.
    2. Bae, Youngeun & Rindt, Craig R. & Mitra, Suman Kumar & Ritchie, Stephen G., 2024. "Fleet operator perspectives on alternative fuels for heavy-duty vehicles," Transport Policy, Elsevier, vol. 149(C), pages 36-48.
    3. Mesut Yavuz & Ismail Çapar, 2017. "Alternative-Fuel Vehicle Adoption in Service Fleets: Impact Evaluation Through Optimization Modeling," Transportation Science, INFORMS, vol. 51(2), pages 480-493, May.
    4. Schücking, Maximilian & Jochem, Patrick, 2021. "Two-stage stochastic program optimizing the cost of electric vehicles in commercial fleets," Applied Energy, Elsevier, vol. 293(C).
    5. Ensslen, Axel & Gnann, Till & Jochem, Patrick & Plötz, Patrick & Dütschke, Elisabeth & Fichtner, Wolf, 2020. "Can product service systems support electric vehicle adoption?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 343-359.
    6. Lebeau, Philippe & Macharis, Cathy & Van Mierlo, Joeri, 2016. "Exploring the choice of battery electric vehicles in city logistics: A conjoint-based choice analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 91(C), pages 245-258.
    7. Figenbaum, Erik, 2018. "Can battery electric light commercial vehicles work for craftsmen and service enterprises?," Energy Policy, Elsevier, vol. 120(C), pages 58-72.
    8. Ingo Kastner & Annalena Becker & Sebastian Bobeth & Ellen Matthies, 2021. "Are Professionals Rationals? How Organizations and Households Make E-Car Investments," Sustainability, MDPI, vol. 13(5), pages 1-19, February.
    9. Koyuncu, Işıl & Yavuz, Mesut, 2019. "Duplicating nodes or arcs in green vehicle routing: A computational comparison of two formulations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 605-623.
    10. Imran Khan, Muhammad, 2017. "Policy options for the sustainable development of natural gas as transportation fuel," Energy Policy, Elsevier, vol. 110(C), pages 126-136.
    11. Fontaras, Georgios & Grigoratos, Theodoros & Savvidis, Dimitrios & Anagnostopoulos, Konstantinos & Luz, Raphael & Rexeis, Martin & Hausberger, Stefan, 2016. "An experimental evaluation of the methodology proposed for the monitoring and certification of CO2 emissions from heavy-duty vehicles in Europe," Energy, Elsevier, vol. 102(C), pages 354-364.
    12. Juan C. González Palencia & Van Tuan Nguyen & Mikiya Araki & Seiichi Shiga, 2020. "The Role of Powertrain Electrification in Achieving Deep Decarbonization in Road Freight Transport," Energies, MDPI, vol. 13(10), pages 1-24, May.
    13. James J. Winebrake & James J. Corbett & Fatima Umar & Daniel Yuska, 2019. "Pollution Tradeoffs for Conventional and Natural Gas-Based Marine Fuels," Sustainability, MDPI, vol. 11(8), pages 1-19, April.
    14. Flávia Mendes de Almeida Collaço & Ana Carolina Rodrigues Teixeira & Pedro Gerber Machado & Raquel Rocha Borges & Thiago Luis Felipe Brito & Dominique Mouette, 2022. "Road Freight Transport Literature and the Achievements of the Sustainable Development Goals—A Systematic Review," Sustainability, MDPI, vol. 14(6), pages 1-18, March.
    15. Gnann, Till & Plötz, Patrick & Funke, Simon & Wietschel, Martin, 2014. "What is the market potential of electric vehicles as commercial passenger cars? A case study from Germany," Working Papers "Sustainability and Innovation" S14/2014, Fraunhofer Institute for Systems and Innovation Research (ISI).
    16. Jie Lin & Cynthia Chen & Debbie Niemeier, 2008. "An analysis on long term emission benefits of a government vehicle fleet replacement plan in northern illinois," Transportation, Springer, vol. 35(2), pages 219-235, March.
    17. Mahlia, T.M.I. & Tohno, S. & Tezuka, T., 2012. "A review on fuel economy test procedure for automobiles: Implementation possibilities in Malaysia and lessons for other countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 4029-4046.
    18. Gu, Yan & Ho, Kung-Cheng & Xia, Senmao & Yan, Cheng, 2022. "Do public environmental concerns promote new energy enterprises' development? Evidence from a quasi-natural experiment," Energy Economics, Elsevier, vol. 109(C).
    19. Sahu, Prasanta K. & Qureshi, Danish & Pani, Agnivesh, 2022. "Examining commercial vehicle fleet ownership decisions and the mediating role of freight generation: A structural equation modeling assessment," Transport Policy, Elsevier, vol. 126(C), pages 26-33.
    20. Schücking, Maximilian & Jochem, Patrick, 2020. "Two-stage stochastic program optimizing the total cost of ownership of electric vehicles in commercial fleets," Working Paper Series in Production and Energy 50, Karlsruhe Institute of Technology (KIT), Institute for Industrial Production (IIP).

    More about this item

    Keywords

    Engineering; Social and Behavioral Sciences;

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:cdl:itsdav:qt20n8n4mb. 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: Lisa Schiff (email available below). General contact details of provider: https://edirc.repec.org/data/itucdus.html .

    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.