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Information technology and efficiency in trucking

Author

Listed:
  • Philippe Barla
  • Denis Bolduc
  • Nathalie Boucher
  • Jonathan Watters

Abstract

In this paper, we develop an econometric model to estimate the impacts of Electronic Vehicle Management Systems (EVMS) on the load factor (LF) of heavy trucks using data at the operational level. This technology is supposed to improve capacity utilization by reducing coordination costs between demand and supply. The model is estimated on a subsample of the 1999 National Roadside Survey, covering heavy trucks travelling in the province of Quebec. The LF is explained as a function of truck, trip and carrier characteristics. We show that the use of EVMS results in a 16 percentage points increase of LF on backhaul trips. However, we also find that the LF of equipped trucks is reduced by about 7.6 percentage points on fronthaul movements. This last effect could be explained by a rebound effect: higher expected LF on the returns lead carriers to accept shipments with lower fronthaul LF. Overall, we find that this technology has increased the tonne-kilometers transported of equipped trucks by 6.3% and their fuel efficiency by 5%.

Suggested Citation

  • Philippe Barla & Denis Bolduc & Nathalie Boucher & Jonathan Watters, 2008. "Information technology and efficiency in trucking," Working Papers of Department of Economics, Leuven ces0813, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
    • Handle: RePEc:ete:ceswps:ces0813
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    Cited by:

    1. is not listed on IDEAS
    2. Abate, Megersa & de Jong, Gerard, 2014. "The optimal shipment size and truck size choice – The allocation of trucks across hauls," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 262-277.
    3. Cédric Gossart, 2015. "Rebound effects and ICT : a review of the literature," Post-Print hal-01258112, HAL.
    4. Cédric Gossart, 2015. "Rebound effects and ICT : a review of the literature," Grenoble Ecole de Management (Post-Print) hal-01258112, HAL.
    5. Yang,Ron Nan, 2024. "Geographic Imbalance, Search Frictions, and Regulation : Causes of Empty Miles in Freight Trucking," Policy Research Working Paper Series 10775, The World Bank.
    6. Zolfagharinia, Hossein & Haughton, Michael A., 2017. "Operational flexibility in the truckload trucking industry," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 437-460.
    7. 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.

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    Keywords

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    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation
    • R40 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - General

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