IDEAS home Printed from https://ideas.repec.org/a/kap/transp/v45y2018i3d10.1007_s11116-017-9758-2.html
   My bibliography  Save this article

A business establishment fleet ownership and composition model

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11116-017-9758-2
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11116-017-9758-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bhat, Chandra R. & Eluru, Naveen, 2009. "A copula-based approach to accommodate residential self-selection effects in travel behavior modeling," Transportation Research Part B: Methodological, Elsevier, vol. 43(7), pages 749-765, August.
    2. John G. Klincewicz & Hanan Luss & Martha G. Pilcher, 1990. "Fleet Size Planning when Outside Carrier Services Are Available," Transportation Science, INFORMS, vol. 24(3), pages 169-182, August.
    3. John R. Schroeter, 1983. "A Model of Taxi Service under Fare Structure and Fleet Size Regulation," Bell Journal of Economics, The RAND Corporation, vol. 14(1), pages 81-96, Spring.
    4. P. Seetharaman & Siddhartha Chib & Andrew Ainslie & Peter Boatwright & Tat Chan & Sachin Gupta & Nitin Mehta & Vithala Rao & Andrei Strijnev, 2005. "Models of Multi-Category Choice Behavior," Marketing Letters, Springer, vol. 16(3), pages 239-254, December.
    5. Bhat, Chandra R. & Sen, Sudeshna, 2006. "Household vehicle type holdings and usage: an application of the multiple discrete-continuous extreme value (MDCEV) model," Transportation Research Part B: Methodological, Elsevier, vol. 40(1), pages 35-53, January.
    6. de Jong, Gerard & Ben-Akiva, Moshe, 2007. "A micro-simulation model of shipment size and transport chain choice," Transportation Research Part B: Methodological, Elsevier, vol. 41(9), pages 950-965, November.
    7. Samuel D. Oman & Victoria Landsman & Yohay Carmel & Ronen Kadmon, 2007. "Analyzing Spatially Distributed Binary Data Using Independent-Block Estimating Equations," Biometrics, The International Biometric Society, vol. 63(3), pages 892-900, September.
    8. S. le Cessie & J. C. van Houwelingen, 1994. "Logistic Regression for Correlated Binary Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 43(1), pages 95-108, March.
    9. Baltas, George, 2004. "A model for multiple brand choice," European Journal of Operational Research, Elsevier, vol. 154(1), pages 144-149, April.
    10. Ruan, Minyan & Lin, Jie (Jane) & Kawamura, Kazuya, 2012. "Modeling urban commercial vehicle daily tour chaining," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(6), pages 1169-1184.
    11. Koetse, Mark J. & Hoen, Anco, 2014. "Preferences for alternative fuel vehicles of company car drivers," Resource and Energy Economics, Elsevier, vol. 37(C), pages 279-301.
    12. Sundararajan Arunapuram & Kamlesh Mathur & Daniel Solow, 2003. "Vehicle Routing and Scheduling with Full Truckloads," Transportation Science, INFORMS, vol. 37(2), pages 170-182, May.
    13. Roorda, Matthew J. & Cavalcante, Rinaldo & McCabe, Stephanie & Kwan, Helen, 2010. "A conceptual framework for agent-based modelling of logistics services," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(1), pages 18-31, January.
    14. Bhat, Chandra R., 2005. "A multiple discrete-continuous extreme value model: formulation and application to discretionary time-use decisions," Transportation Research Part B: Methodological, Elsevier, vol. 39(8), pages 679-707, September.
    15. Alexandros Dimitropoulos & Jos N. van Ommeren & Paul Koster & Piet Rietveld†, 2014. "Welfare Effects of Distortionary Tax Incentives under Preference Heterogeneity: An Application to Employer-provided Electric Cars," Tinbergen Institute Discussion Papers 14-064/VIII, Tinbergen Institute.
    16. 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.
    17. Gerard Jong & Ryuichi Kitamura, 2009. "A review of household dynamic vehicle ownership models: holdings models versus transactions models," Transportation, Springer, vol. 36(6), pages 733-743, November.
    18. Hunt, J.D. & Stefan, K.J., 2007. "Tour-based microsimulation of urban commercial movements," Transportation Research Part B: Methodological, Elsevier, vol. 41(9), pages 981-1013, November.
    19. Fred Mannering & Clifford Winston, 1985. "A Dynamic Empirical Analysis of Household Vehicle Ownership and Utilization," RAND Journal of Economics, The RAND Corporation, vol. 16(2), pages 215-236, Summer.
    20. David Hensher & Tu Ton, 2002. "TRESIS: A transportation, land use and environmental strategy impact simulator for urban areas," Transportation, Springer, vol. 29(4), pages 439-457, November.
    21. Bhat, Chandra R. & Sener, Ipek N. & Eluru, Naveen, 2010. "A flexible spatially dependent discrete choice model: Formulation and application to teenagers' weekday recreational activity participation," Transportation Research Part B: Methodological, Elsevier, vol. 44(8-9), pages 903-921, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tapia, Rodrigo J. & de Jong, Gerard & Larranaga, Ana M. & Bettella Cybis, Helena B., 2020. "Application of MDCEV to infrastructure planning in regional freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 255-271.
    2. Pani, Agnivesh & Mishra, Sabya & Sahu, Prasanta, 2022. "Developing multi-vehicle freight trip generation models quantifying the relationship between logistics outsourcing and insourcing decisions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 159(C).
    3. 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.
    4. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sabreena Anowar & Naveen Eluru & Luis F. Miranda-Moreno, 2014. "Alternative Modeling Approaches Used for Examining Automobile Ownership: A Comprehensive Review," Transport Reviews, Taylor & Francis Journals, vol. 34(4), pages 441-473, July.
    2. Bhat, Chandra R., 2008. "The multiple discrete-continuous extreme value (MDCEV) model: Role of utility function parameters, identification considerations, and model extensions," Transportation Research Part B: Methodological, Elsevier, vol. 42(3), pages 274-303, March.
    3. Erika Spissu & Abdul Pinjari & Ram Pendyala & Chandra Bhat, 2009. "A copula-based joint multinomial discrete–continuous model of vehicle type choice and miles of travel," Transportation, Springer, vol. 36(4), pages 403-422, July.
    4. Bhat, Chandra R. & Sen, Sudeshna & Eluru, Naveen, 2009. "The impact of demographics, built environment attributes, vehicle characteristics, and gasoline prices on household vehicle holdings and use," Transportation Research Part B: Methodological, Elsevier, vol. 43(1), pages 1-18, January.
    5. Khan, Mubassira & Machemehl, Randy, 2017. "Commercial vehicles time of day choice behavior in urban areas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 68-83.
    6. Sharman, Bryce W. & Roorda, Matthew J., 2013. "Multilevel modelling of commercial vehicle inter-arrival duration using GPS data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 56(C), pages 94-107.
    7. Liu, Yangwen & Tremblay, Jean-Michel & Cirillo, Cinzia, 2014. "An integrated model for discrete and continuous decisions with application to vehicle ownership, type and usage choices," Transportation Research Part A: Policy and Practice, Elsevier, vol. 69(C), pages 315-328.
    8. Bhat, Chandra R. & Srinivasan, Sivaramakrishnan & Sen, Sudeshna, 2006. "A joint model for the perfect and imperfect substitute goods case: Application to activity time-use decisions," Transportation Research Part B: Methodological, Elsevier, vol. 40(10), pages 827-850, December.
    9. Fang, Hao Audrey, 2008. "A discrete-continuous model of households' vehicle choice and usage, with an application to the effects of residential density," Transportation Research Part B: Methodological, Elsevier, vol. 42(9), pages 736-758, November.
    10. Tapia, Rodrigo J. & de Jong, Gerard & Larranaga, Ana M. & Bettella Cybis, Helena B., 2020. "Application of MDCEV to infrastructure planning in regional freight transport," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 255-271.
    11. Bruno De Borger & Jan Rouwendal, 2014. "Car User Taxes, Quality Characteristics, and Fuel Efficiency Household Behaviour and Market Adjustment," Journal of Transport Economics and Policy, University of Bath, vol. 48(3), pages 345-366, September.
    12. de Bok, Michiel & Tavasszy, Lóránt & Sebastiaan Thoen,, 2022. "Application of an empirical multi-agent model for urban goods transport to analyze impacts of zero emission zones in The Netherlands," Transport Policy, Elsevier, vol. 124(C), pages 119-127.
    13. Cinzia Cirillo & Yangwen Liu & Jean-Michel Tremblay, 2017. "Simulation, numerical approximation and closed forms for joint discrete continuous models with an application to household vehicle ownership and use," Transportation, Springer, vol. 44(5), pages 1105-1125, September.
    14. Khan, Mubassira & Machemehl, Randy, 2017. "Analyzing tour chaining patterns of urban commercial vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 84-97.
    15. Lara Al Otary & Maya Abou-Zeid & Isam Kaysi, 2022. "Modeling car ownership and use in a developing country context with informal public transportation," Transportation, Springer, vol. 49(1), pages 1-36, February.
    16. Beser Hugosson, Muriel & Algers, Staffan & Habibi, Shiva & Sundbergh, Pia, 2016. "Evaluation of the Swedish car fleet model using recent applications," Transport Policy, Elsevier, vol. 49(C), pages 30-40.
    17. Don Fullerton & Li Gan & Miwa Hattori, 2015. "A model to evaluate vehicle emission incentive policies in Japan," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 17(1), pages 79-108, January.
    18. de Jong, Gerard & Kouwenhoven, Marco & Ruijs, Kim & van Houwe, Pieter & Borremans, Dana, 2016. "A time-period choice model for road freight transport in Flanders based on stated preference data," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 86(C), pages 20-31.
    19. Castro, Marisol & Bhat, Chandra R. & Pendyala, Ram M. & Jara-Díaz, Sergio R., 2012. "Accommodating multiple constraints in the multiple discrete–continuous extreme value (MDCEV) choice model," Transportation Research Part B: Methodological, Elsevier, vol. 46(6), pages 729-743.
    20. Bhat, Chandra R. & Astroza, Sebastian & Sidharthan, Raghuprasad & Alam, Mohammad Jobair Bin & Khushefati, Waleed H., 2014. "A joint count-continuous model of travel behavior with selection based on a multinomial probit residential density choice model," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 31-51.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:kap:transp:v:45:y:2018:i:3:d:10.1007_s11116-017-9758-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.