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Identification and quantification of principal–agent problems affecting energy efficiency investments and use decisions in the trucking industry

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  • Vernon, David
  • Meier, Alan

Abstract

Energy related Principal–Agent (PA) problems cause inefficient combinations of investment, operating costs, and usage behavior. The complex market structure of the trucking industry contributes to split incentives because entities responsible for investments in energy efficiency do not always pay fuel costs and drivers are often not rewarded for fuel-efficient operation. Some contractual relationships exist in the trucking industry that hinder responses to fuel price signals. Up to 91% of total trucking fuel consumption in the U.S. is affected by “usage” PA problems, where the driver does not pay fuel costs and lacks incentive for fuel saving operation. Approximately 23% of trailers are exposed to an “efficiency problem” when owners of rented trailers do not pay fuel costs and therefore have little incentive to invest in efficiency upgrades such as improved trailer aerodynamics and reduced tire rolling resistance. This study shows that PA problems have the potential to significantly increase fuel consumption through avoided investments, insufficient maintenance, and fuel-wasting practices. Further research into the causes and effects of PA problems can shape policies to promote better alignment of costs and benefits, leading to reduced fuel use and carbon emissions.

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  • Vernon, David & Meier, Alan, 2012. "Identification and quantification of principal–agent problems affecting energy efficiency investments and use decisions in the trucking industry," Energy Policy, Elsevier, vol. 49(C), pages 266-273.
    • Handle: RePEc:eee:enepol:v:49:y:2012:i:c:p:266-273
    DOI: 10.1016/j.enpol.2012.06.016
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    5. Fraas, Arthur & Lutter, Randall & Porter, Zachary & Wallace, Alexander, 2016. "The Energy Paradox and the Adoption of Energy-Saving Technologies in the Trucking Industry," Working Papers 06870, George Mason University, Mercatus Center.
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    8. Guerrero, Sebastian E. & Madanat, Samer M. & Leachman, Robert C., 2013. "The Trucking Sector Optimization Model: A tool for predicting carrier and shipper responses to policies aiming to reduce GHG emissions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 59(C), pages 85-107.
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