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Traffic Congestion and Trucking Managers' Use of Automated Routing and Scheduling

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  • Golob, Thomas F.
  • Regan, A C

Abstract

Using data from a 2001 survey of managers of 700 trucking companies operating in California, we tested competing hypotheses about the relationship between managers' perceptions of the impact of traffic congestion on their operations and their companies' adoption of routing and scheduling software. Demand for automated routing and scheduling was found to be influenced directly by the need to re-route drivers, and indirectly by the need, generated by customers' schedules, to operate during congested periods. We were also able to identify which types of trucking companies are most affected by congestion and which types are more likely to adopt such software.

Suggested Citation

  • 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.
    • Handle: RePEc:cdl:uctcwp:qt74z234n4
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    1. Golob, Thomas F. & Regan, A C, 2002. "Trucking Industry Adoption of Information Technology: A Structural Multivariate Probit Model," University of California Transportation Center, Working Papers qt9w1988t7, University of California Transportation Center.
    2. Hall, Randolph W. & Intihar, Chris, 1997. "Commercial Vehicle Operations: Government Interfaces And Intelligent Transportation Systems," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt9p272488, Institute of Transportation Studies, UC Berkeley.
    3. 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.
    4. 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.
    5. Scapinakis, Dimitris A. & Garrison, William L., 1991. "Communications And Positioning Systems In The Motor Carrier Industry," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt15j086pf, Institute of Transportation Studies, UC Berkeley.
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    Cited by:

    1. Güner, Ali R. & Murat, Alper & Chinnam, Ratna Babu, 2017. "Dynamic routing for milk-run tours with time windows in stochastic time-dependent networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 97(C), pages 251-267.
    2. 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.
    3. Faiq Matin & Gobind M. Herani & Usman Ali Warraich, 2012. "Factors Affecting Traffic Jam in Karachi and its Impact on Performance of Economy," KASBIT Business Journals (KBJ), Khadim Ali Shah Bukhari Institute of Technology (KASBIT), vol. 5, pages 25-32, December.
    4. de Abreu e Silva, João & Alho, André Romano, 2017. "Using Structural Equations Modeling to explore perceived urban freight deliveries parking issues," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 18-32.
    5. Regan, Amelia C. & Golob, Thomas F., 2003. "Trucking Industry Demand for Urban Shared Use Freight Terminals," University of California Transportation Center, Working Papers qt0v33g422, University of California Transportation Center.
    6. Maloni, Michael J. & Jackson, Eric C., 2007. "Stakeholder Contributions to Container Port Capacity: A Survey of Port Authorities," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 46(1).

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