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A business establishment fleet ownership and composition model

Author

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  • Taha Hossein Rashidi

    (University of New South Wales)

  • Matthew J. Roorda

    (University of Toronto)

Abstract

Commercial vehicle fleet ownership is a business decision that is fundamental to the transportation operations of a business establishment. This paper develops a model of fleet ownership and composition for the Region of Peel, Canada. A trivariate model is developed to represent a business establishment’s correlated decisions of how many passenger cars, pickups/vans, or trucks/tractors are owned by the company. The joint model is approximated into a closed-form formulation by using the composite marginal likelihood approach combined with copula functions. The models are estimated using establishment data from the Region of Peel Commercial Travel Survey, and land use and transportation infrastructure variables developed from GIS databases. Larger establishments, as measured by number of employees, are more likely to own vehicles, as are establishments with greater demand for goods and services. Differences are found between establishments in different industry classifications, with the construction industry favoring pickups/vans, and the office/service industries less inclined to own trucks or pickups/vans. Significant negative copulas between ownership of different vehicle types reveal a substitution effect. This also shows the importance of developing the joint model over the independent formulation for decisions on ownership of different types of vehicles.

Suggested Citation

  • Taha Hossein Rashidi & Matthew J. Roorda, 2018. "A business establishment fleet ownership and composition model," Transportation, Springer, vol. 45(3), pages 971-987, May.
    • Handle: RePEc:kap:transp:v:45:y:2018:i:3:d:10.1007_s11116-017-9758-2
    DOI: 10.1007/s11116-017-9758-2
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    Cited by:

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    2. Rodrigo J. Tapia & Gerard Jong & Ana M. Larranaga & Helena B. Bettella Cybis, 2021. "Exploring Multiple‐discreteness in Freight Transport. A Multiple Discrete Extreme Value Model Application for Grain Consolidators in Argentina," Networks and Spatial Economics, Springer, vol. 21(3), pages 581-608, September.
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    4. Xiaoxuan Wei & Meng Ye & Liang Yuan & Wei Bi & Weisheng Lu, 2022. "Analyzing the Freight Characteristics and Carbon Emission of Construction Waste Hauling Trucks: Big Data Analytics of Hong Kong," IJERPH, MDPI, vol. 19(4), pages 1-21, February.

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