Trucking industry adoption of information technology: a multivariate discrete choice model |
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| Institution: | 1. Institute of Transportation Studies, University of California, Irvine, CA 92697 3600, USA;2. Department of Civil and Environmental Engineering and Institute of Transportation Studies, University of California, Irvine, CA 92697, USA;1. Department of Civil, Environmental & Construction Engineering, University of Central Florida, United States;2. Department of Urban and Engineering Research, Umm Al-Qura University, Saudi Arabia;1. Department of Applied Economics and Institute of Environmental Sciences (IUCA), University of Zaragoza, C/Violante de Hungría 23, 50009 Zaragoza, Spain;2. Department of Economic Analysis, University of Zaragoza, Gran Vía 2, 50005 Zaragoza, Spain;1. The University of Texas at Austin, Department of Civil, Architectural and Environmental Engineering, 301 E. Dean Keeton St. Stop C1761, Austin, TX 78712, USA;2. University of South Australia, Institute for Choice, 140 Arthur St, Level 13, North Sydney, NSW 2060, Australia;3. University of South Florida, Department of Civil and Environmental Engineering, 4202 E Fowler Ave, ENB 118, Tampa, FL 33620, USA;4. Newcastle University, Transport Operations Research Group, School of Civil Engineering and Geoscience, Cassie Building, NE1 7RU Newcastle, UK;5. Cornell University, School of Civil and Environmental Engineering, 305 Hollister Hall, Ithaca, NY 14853, USA;1. University of California at Berkeley, 116 McLaughlin Hall, Berkeley, CA 94720-1720, United States;2. University of California at Berkeley, 111 McLaughlin Hall, Berkeley, CA 94720-1720, United States |
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| Abstract: | The objective of this research is to understand the demand for information technology among trucking companies. A multivariate discrete choice model is estimated on data from a large-scale survey of the trucking industry in California. This model is designed to identify the influences of each of twenty operational characteristics on the propensity to adopt each of seven different information technologies, while simultaneously allowing the seven error terms to be freely correlated. Results showed that the distinction between for-hire and private fleets is paramount, as is size of the fleet and the provision of intermodal maritime and air services. |
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