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Surveying and Modeling Trucking Industry Perceptions, Preferences and Behavior

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  • Golob, Thomas F.
  • Regan, Amelia C.

Abstract

Methods developed to study passenger travel behaviour can be usefully applied in studying perceptions, preferences, and behaviour of important actors in freight transportation. Transportation planners throughout the world can benefit by gaining improved understanding of how trucking companies are coping with changes in transportation system levels of service and how companies are likely to react to opportunities presented by information technologies and intelligent transportation systems. In this paper we present five different structural equations models (SEM) that have been estimated using large-scale survey data from the trucking industry. These models are used to examine carrier perceptions related to problems accounting for operational inefficiencies, impacts of traffic congestion on roads and at terminal facilities, transportation policy priorities, and uses of and opportunities for implementing computer and information technologies.

Suggested Citation

  • Golob, Thomas F. & Regan, Amelia C., 2003. "Surveying and Modeling Trucking Industry Perceptions, Preferences and Behavior," University of California Transportation Center, Working Papers qt1gw166zk, University of California Transportation Center.
  • Handle: RePEc:cdl:uctcwp:qt1gw166zk
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    References listed on IDEAS

    as
    1. Golob, Thomas F. & Regan, A C, 2003. "Traffic Congestion and Trucking Managers' Use of Automated Routing and Scheduling," University of California Transportation Center, Working Papers qt74z234n4, University of California Transportation Center.
    2. Golob, Thomas F. & Regan, Amelia C., 2000. "Freight industry attitudes towards policies to reduce congestion," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 36(1), pages 55-77, March.
    3. Golob, Thomas F., 2003. "Structural equation modeling for travel behavior research," Transportation Research Part B: Methodological, Elsevier, vol. 37(1), pages 1-25, January.
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    7. Hamparsum Bozdogan, 1987. "Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 345-370, September.
    8. Golob, Thomas F. & Regan, Amelia C., 2003. "Traffic congestion and trucking managers' use of automated routing and scheduling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 39(1), pages 61-78, January.
    9. Golob, Thomas F. & Regan, Amelia C., 2001. "Impacts of highway congestion on freight operations: perceptions of trucking industry managers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(7), pages 577-599, August.
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    12. Thomas N. Hubbard, 2000. "The Demand for Monitoring Technologies: The Case of Trucking," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 115(2), pages 533-560.
    13. Golob, Thomas F. & Reagan, Amelia C., 2002. "Trucking Industry Adoption of Information Technology: A structural Multivariate Discrete Choice Model," University of California Transportation Center, Working Papers qt7kv5f17n, University of California Transportation Center.
    14. Hensher, David A. & Golob, Thomas F., 1998. "Searching for Policy Priorities in the Formulation of a Freight Transport Strategy: An Analysis of Freight Industry Attitudes," University of California Transportation Center, Working Papers qt169505dh, University of California Transportation Center.
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