Information technology and efficiency in trucking
AbstractIn 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%.
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Bibliographic InfoPaper provided by Katholieke Universiteit Leuven in its series Open Access publications from Katholieke Universiteit Leuven with number urn:hdl:123456789/182727.
Date of creation: 2008
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Other versions of this item:
- O33 - Economic Development, Technological Change, and Growth - - Technological Change; Research and Development; 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
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- Alfonso Miranda & Sophia Rabe-Hesketh, 2006. "Maximum likelihood estimation of endogenous switching and sample selection models for binary, ordinal, and count variables," Stata Journal, StataCorp LP, vol. 6(3), pages 285-308, September.
- Jeffrey M. Wooldridge, 1999. "Asymptotic Properties of Weighted M-Estimators for Variable Probability Samples," Econometrica, Econometric Society, vol. 67(6), pages 1385-1406, November.
- Thomas N. Hubbard, 2003. "Information, Decisions, and Productivity: On-Board Computers and Capacity Utilization in Trucking," American Economic Review, American Economic Association, vol. 93(4), pages 1328-1353, September.
- Jeffrey M Wooldridge, 2010.
"Econometric Analysis of Cross Section and Panel Data,"
MIT Press Books,
The MIT Press,
edition 2, volume 1, number 0262232588, June.
- Jeffrey M. Wooldridge, 2001. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262232197, June.
- A. Greening, Lorna & Greene, David L. & Difiglio, Carmen, 2000. "Energy efficiency and consumption -- the rebound effect -- a survey," Energy Policy, Elsevier, vol. 28(6-7), pages 389-401, June.
- Dirk Pilat, 2004. "The ICT Productivity Paradox: Insights from Micro Data," OECD Economic Studies, OECD Publishing, vol. 2004(1), pages 37-65.
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