Trucking Industry Adoption of Information Technology: A Structural Multivariate Probit Model

Thomas F. Golob and A C Regan

University of California Transportation Center, Working Papers from University of California Transportation Center

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.

Keywords: Information technology; Commercial Vehicle Operations; Freight Transportation; Trucking Operations; Intermodal operations; Intelligent Transportation Systems; Discrete Choice Models; Multivariate Probit; Social and Behavioral Sciences (search for similar items in EconPapers)
Date: 2002-09-01
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (23)

Downloads: (external link)
https://www.escholarship.org/uc/item/9w1988t7.pdf;origin=repeccitec (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cdl:uctcwp:qt9w1988t7

Access Statistics for this paper

More papers in University of California Transportation Center, Working Papers from University of California Transportation Center Contact information at EDIRC.
Bibliographic data for series maintained by Lisa Schiff ().