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Electrifying Freight: Modeling the Decision-Making Process for Battery Electric Truck Procurement

Author

Listed:
  • Levent Özlü

    (Department of Management Engineering, Istanbul Technical University, Istanbul 34469, Turkey)

  • Dilay Çelebi

    (Department of Management Engineering, Istanbul Technical University, Istanbul 34469, Turkey
    South-East European Research Centre, 54622 Thessaloniki, Greece
    City College, University of York Europe Campus, 54626 Thessaloniki, Greece)

Abstract

As the transportation industry seeks sustainable alternatives to internal combustion engine trucks (ICET), understanding the dynamics behind battery electric truck (BET) adoption becomes essential. This paper explores the critical factors influencing the procurement decision for BET in the freight transportation sector, employing a novel combination of fuzzy logic and the Delphi method to bridge qualitative assessments and quantitative analysis. Through a comprehensive literature review and expert consultations via the Delphi method, the research identifies the barriers to BET adoption, including initial investment costs, charging infrastructure, and legislative clarity. Fuzzy logic is then applied to model these factors’ impacts on the purchasing decision, translating subjective judgments into a structured analytical framework. This approach enables the assessment of BETs’ viability against ICETs, considering the total cost of ownership (TCO), travel time (TT) ratios, and perceived social benefits. While economic factors primarily drive the purchasing decision, the study reveals that social utility also plays a crucial role. This research contributes to the sustainable transportation literature by offering a detailed model of the decision-making process for BET procurement, providing valuable insights for industry professionals, policymakers, and academics committed to advancing environmentally friendly freight solutions.

Suggested Citation

  • Levent Özlü & Dilay Çelebi, 2024. "Electrifying Freight: Modeling the Decision-Making Process for Battery Electric Truck Procurement," Sustainability, MDPI, vol. 16(9), pages 1-23, April.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:9:p:3801-:d:1387083
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    References listed on IDEAS

    as
    1. Pasura Aungkulanon & Walailak Atthirawong & Pongchanun Luangpaiboon, 2023. "Fuzzy Analytical Hierarchy Process for Strategic Decision Making in Electric Vehicle Adoption," Sustainability, MDPI, vol. 15(8), pages 1-20, April.
    2. Liimatainen, Heikki & van Vliet, Oscar & Aplyn, David, 2019. "The potential of electric trucks – An international commodity-level analysis," Applied Energy, Elsevier, vol. 236(C), pages 804-814.
    3. Rowe, Gene & Wright, George, 1999. "The Delphi technique as a forecasting tool: issues and analysis," International Journal of Forecasting, Elsevier, vol. 15(4), pages 353-375, October.
    4. Burke, Andrew & Sinha, Anish Kumar, 2020. "Technology, Sustainability, and Marketing of Battery Electric and Hydrogen Fuel Cell Medium-Duty and Heavy-Duty Trucks and Buses in 2020-2040," Institute of Transportation Studies, Working Paper Series qt7s25d8bc, Institute of Transportation Studies, UC Davis.
    5. Zichong Lyu & Dirk Pons & Yilei Zhang, 2023. "Emissions and Total Cost of Ownership for Diesel and Battery Electric Freight Pickup and Delivery Trucks in New Zealand: Implications for Transition," Sustainability, MDPI, vol. 15(10), pages 1-23, May.
    6. Plötz, Patrick & Gnann, Till & Jochem, Patrick & Yilmaz, Hasan Ümitcan & Kaschub, Thomas, 2019. "Impact of electric trucks powered by overhead lines on the European electricity system and CO2 emissions," Energy Policy, Elsevier, vol. 130(C), pages 32-40.
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