IDEAS home Printed from https://ideas.repec.org/a/eee/jotrge/v54y2016icp102-111.html
   My bibliography  Save this article

Conditional Freight Trip Generation modelling

Author

Listed:
  • Günay, Gürkan
  • Ergün, Gökmen
  • Gökaşar, Ilgın

Abstract

Freight Trip Generation (FTG) in general and FTG modelling in particular are fields that are not concentrated upon as much as passenger trip generation. Therefore, the main objective of this work was to improve the understanding of the underlying processes that generate freight trips and through this understanding, to improve the modelling of FTG. To achieve this goal, the authors first had an extensive literature review to understand the reasons for the weaknesses of the current FTG modelling approaches. After identifying these weaknesses, some of them were brought to a focus in this work. One of the main weaknesses was the inadequacy of the classification system which was used to group commercial establishments in a set of standardized classes. Hence, firstly an experiment was conducted to create groups of logistical sites that had homogeneous FTG characteristics. It was observed that one of these segments had too many zero trips for a particular vehicle category, namely tractor-trailers. Then, to solve this problem, a new ‘conditional’ modelling approach for FTG modelling of this group and this vehicle category was proposed and tested using the data obtained from Kocaeli City Logistics Master Plan. This new hypothesised conditional approach aimed to find the probability of the segment generating tractor-trailer trips using the binary logit model and the generated trips given that the sites produced tractor-trailer trips using the regression technique. Afterwards, the models developed using the new approach were compared with the models obtained using only the common modelling approach of the regression analysis. The results indicated that creating homogeneous groups of logistical sites was possible and the new conditional modelling approach which was applied to one segment of the logistical sites for FTG of tractor-trailers, performed better than the regular regression modelling. Lastly, some recommendations for further improvement of this modelling approach were provided.

Suggested Citation

  • Günay, Gürkan & Ergün, Gökmen & Gökaşar, Ilgın, 2016. "Conditional Freight Trip Generation modelling," Journal of Transport Geography, Elsevier, vol. 54(C), pages 102-111.
    • Handle: RePEc:eee:jotrge:v:54:y:2016:i:c:p:102-111
    DOI: 10.1016/j.jtrangeo.2016.05.013
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0966692316302745
    Download Restriction: no
    File URL: https://libkey.io/10.1016/j.jtrangeo.2016.05.013?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
    ---><---

    References listed on IDEAS

    as
    1. Allen, J. & Browne, M. & Cherrett, T., 2012. "Investigating relationships between road freight transport, facility location, logistics management and urban form," Journal of Transport Geography, Elsevier, vol. 24(C), pages 45-57.
    2. Iding, Mirjam H.E. & Meester, Wilhelm J. & Tavasszy, Lóri, 2002. "Freight trip generation by firms," ERSA conference papers ersa02p453, European Regional Science Association.
    3. Holguín-Veras, José & Thorson, Ellen, 2003. "Modeling commercial vehicle empty trips with a first order trip chain model," Transportation Research Part B: Methodological, Elsevier, vol. 37(2), pages 129-148, February.
    4. Lindholm, Maria & Behrends, Sönke, 2012. "Challenges in urban freight transport planning – a review in the Baltic Sea Region," Journal of Transport Geography, Elsevier, vol. 22(C), pages 129-136.
    5. José Holguín-Veras & Gopal Patil, 2008. "A Multicommodity Integrated Freight Origin–destination Synthesis Model," Networks and Spatial Economics, Springer, vol. 8(2), pages 309-326, September.
    6. Joseph Chow & Choon Yang & Amelia Regan, 2010. "State-of-the art of freight forecast modeling: lessons learned and the road ahead," Transportation, Springer, vol. 37(6), pages 1011-1030, November.
    7. Hensher, David & Figliozzi, Miguel Andres, 2007. "Behavioural insights into the modelling of freight transportation and distribution systems," Transportation Research Part B: Methodological, Elsevier, vol. 41(9), pages 921-923, November.
    Full references (including those not matched with items on IDEAS)

    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. 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.
    2. Márquez, Luis & Cantillo, Víctor & Paternina-Arboleda, Carlos D., 2024. "Temporal accessibility and freight generation of agricultural products: An empirical study in Colombia," Research in Transportation Economics, Elsevier, vol. 104(C).
    3. 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.
    4. Ottemöller, Ole & Friedrich, Hanno, 2019. "Modelling change in supply-chain-structures and its effect on freight transport demand," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 121(C), pages 23-42.
    5. McLeod, Sam & Schapper, Jake H.M. & Curtis, Carey & Graham, Giles, 2019. "Conceptualizing freight generation for transport and land use planning: A review and synthesis of the literature," Transport Policy, Elsevier, vol. 74(C), pages 24-34.
    6. Chandra, Aitichya & Sharath, M.N. & Pani, Agnivesh & Sahu, Prasanta K., 2021. "A multi-objective genetic algorithm approach to design optimal zoning systems for freight transportation planning," Journal of Transport Geography, Elsevier, vol. 92(C).
    7. Oliveira, Leise Kelli de & Lopes, Gabriela Pereira & Oliveira, Renata Lúcia Magalhães de & Bracarense, Lílian dos Santos Fontes Pereira & Pitombo, Cira Souza, 2022. "An investigation of contributing factors for warehouse location and the relationship between local attributes and explanatory variables of Warehouse Freight Trip Generation Model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 162(C), pages 206-219.
    8. Pani, Agnivesh & Sahu, Prasanta K. & Tavasszy, Lóránt & Mishra, Sabya, 2023. "Freight activity-travel pattern generation (FAPG) as an enhancement of freight (trip) generation modelling: Methodology and case study," Transport Policy, Elsevier, vol. 144(C), pages 34-48.
    9. Cheah, Lynette & Mepparambath, Rakhi Manohar & Ricart Surribas, Gabriella Marie, 2021. "Freight trips generated at retail malls in dense urban areas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 145(C), pages 118-131.
    10. Hensher, David A. & Teye, Collins, 2019. "Commodity interaction in freight movement models for New South Wales," Journal of Transport Geography, Elsevier, vol. 80(C).
    11. Al Hajj Hassan, Lama & Mahmassani, Hani S. & Chen, Ying, 2020. "Reinforcement learning framework for freight demand forecasting to support operational planning decisions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 137(C).
    12. Gatta, Valerio & Marcucci, Edoardo, 2014. "Urban freight transport and policy changes: Improving decision makers' awareness via an agent-specific approach," Transport Policy, Elsevier, vol. 36(C), pages 248-252.
    13. Kalahasthi, Lokesh & Holguín-Veras, José & Yushimito, Wilfredo F., 2022. "A freight origin-destination synthesis model with mode choice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    14. Joseph Chow & Choon Yang & Amelia Regan, 2010. "State-of-the art of freight forecast modeling: lessons learned and the road ahead," Transportation, Springer, vol. 37(6), pages 1011-1030, November.
    15. Comi, Antonio & Delle Site, Paolo & Filippi, Francesco & Nuzzolo, Agostino, 2012. "Urban Freight Transport Demand Modelling: a State of the Art," European Transport \ Trasporti Europei, ISTIEE, Institute for the Study of Transport within the European Economic Integration, issue 51, pages 1-8.
    16. Dhulipala, Sowjanya & Patil, Gopal R., 2020. "Freight production of agricultural commodities in India using multiple linear regression and generalized additive modelling," Transport Policy, Elsevier, vol. 97(C), pages 245-258.
    17. Chow, Joseph Y.J. & Ritchie, Stephen G. & Jeong, Kyungsoo, 2014. "Nonlinear inverse optimization for parameter estimation of commodity-vehicle-decoupled freight assignment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 67(C), pages 71-91.
    18. Demostenis Ramos Cassiano & Bruno Vieira Bertoncini & Leise Kelli de Oliveira, 2021. "A Conceptual Model Based on the Activity System and Transportation System for Sustainable Urban Freight Transport," Sustainability, MDPI, vol. 13(10), pages 1-13, May.
    19. Zhao, Dongfang & Balusu, Suryaprasanna Kumar & Sheela, Parvathy Vinod & Li, Xiaopeng & Pinjari, Abdul Rawoof & Eluru, Naveen, 2020. "Weight-categorized truck flow estimation: A data-fusion approach and a Florida case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    20. Gomez, Juan & Vassallo, José Manuel, 2015. "Evolution over time of heavy vehicle volume in toll roads: A dynamic panel data to identify key explanatory variables in Spain," Transportation Research Part A: Policy and Practice, Elsevier, vol. 74(C), pages 282-297.

    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:eee:jotrge:v:54:y:2016:i:c:p:102-111. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/journal-of-transport-geography .

    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.