IDEAS home Printed from https://ideas.repec.org/a/eee/retrec/v99y2023ics0739885923000367.html
   My bibliography  Save this article

Modelling the effect of spatial determinants on freight (trip) attraction: A spatially autoregressive geographically weighted regression approach

Author

Listed:
  • Reda, Abel Kebede
  • Tavasszy, Lori
  • Gebresenbet, Girma
  • Ljungberg, David

Abstract

This paper investigates the effect of spatial and locational characteristics of establishments on freight (trip) attraction (FA/FTA) models. The authors estimated econometric models of FA and FTA as a function of the establishment attributes as well as the spatial and locational determinant variables, using establishment-level data collected from Addis Ababa City, Ethiopia. The interconnected issues of spatial dependency and spatial heterogeneity, together with nonlinear specifications, were incorporated with the application of spatial techniques, including spatial error models (SEM), spatial autoregressive model (SAR), geographically weighted regression (GWR), multiscale-GWR (MGWR), and the combination GWR-SAR/MGWR-SAR. Regarding the explanatory variables, the empirical results revealed that firms in the manufacturing, wholesale and retail sectors located on the wider streets tend to receive more FA and FTA. The closeness to the primary road network and the city entry gate influences the FTA of manufacturing and construction firms. Moreover, retail establishments near the major market tend to receive more tonnage. The models also confirm that FA and FTA are the results of two different processes. Overall, the use of spatial regression techniques improves the accuracy of both FA and FTA models. MGWR-SAR exhibits superior performance by jointly addressing spatial dependency and heterogeneity. The MGWR-SAR model also uncovers the local variability of the variables representing the spatial and locational effects on freight attraction. The methodological analysis and empirical findings of the study could provide useful insights to support urban freight modelling, planning, and decision-making.

Suggested Citation

  • Reda, Abel Kebede & Tavasszy, Lori & Gebresenbet, Girma & Ljungberg, David, 2023. "Modelling the effect of spatial determinants on freight (trip) attraction: A spatially autoregressive geographically weighted regression approach," Research in Transportation Economics, Elsevier, vol. 99(C).
  • Handle: RePEc:eee:retrec:v:99:y:2023:i:c:s0739885923000367
    DOI: 10.1016/j.retrec.2023.101296
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0739885923000367
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.retrec.2023.101296?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. Iding, Mirjam H.E. & Meester, Wilhelm J. & Tavasszy, Lóri, 2002. "Freight trip generation by firms," ERSA conference papers ersa02p453, European Regional Science Association.
    2. Gonzalez-Feliu, Jesus & Sánchez-Díaz, Iván, 2019. "The influence of aggregation level and category construction on estimation quality for freight trip generation models," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 121(C), pages 134-148.
    3. David Novak & Christopher Hodgdon & Feng Guo & Lisa Aultman-Hall, 2011. "Nationwide Freight Generation Models: A Spatial Regression Approach," Networks and Spatial Economics, Springer, vol. 11(1), pages 23-41, March.
    4. Griffith, Daniel A. & Layne, Larry J., 1999. "A Casebook for Spatial Statistical Data Analysis: A Compilation of Different Thematic Data Sets," OUP Catalogue, Oxford University Press, number 9780195109580.
    5. Luc Anselin & Daniel Arribas-Bel, 2013. "Spatial fixed effects and spatial dependence in a single cross-section," Papers in Regional Science, Wiley Blackwell, vol. 92(1), pages 3-17, March.
    6. Iván Sánchez-Díaz & José Holguín-Veras & Xiaokun Wang, 2016. "An exploratory analysis of spatial effects on freight trip attraction," Transportation, Springer, vol. 43(1), pages 177-196, January.
    7. Prasanta K. Sahu & Aitichya Chandra & Agnivesh Pani & Bandhan Bandhu Majumdar, 2020. "Designing freight traffic analysis zones for metropolitan areas: identification of optimal scale for macro-level freight travel analysis," Transportation Planning and Technology, Taylor & Francis Journals, vol. 43(6), pages 620-637, August.
    8. Agnivesh Pani & Prasanta K. Sahu & Furqan A. Bhat, 2021. "Assessing the Spatial Transferability of Freight (Trip) Generation Models across and within States of India: Empirical Evidence and Implications for Benefit Transfer," Networks and Spatial Economics, Springer, vol. 21(2), pages 465-493, June.
    9. A. Stewart Fotheringham & Wenbai Yang & Wei Kang, 2017. "Multiscale Geographically Weighted Regression (MGWR)," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 107(6), pages 1247-1265, November.
    10. Pani, Agnivesh & Sahu, Prasanta K. & Chandra, Aitichya & Sarkar, Ashoke K., 2019. "Assessing the extent of modifiable areal unit problem in modelling freight (trip) generation: Relationship between zone design and model estimation results," Journal of Transport Geography, Elsevier, vol. 80(C).
    11. Iván Sánchez-Díaz & José Holguín-Veras & Xiaokun Wang, 2016. "An exploratory analysis of spatial effects on freight trip attraction," Transportation, Springer, vol. 43(1), pages 177-196, January.
    12. Mounisai Siddartha Middela & Gitakrishnan Ramadurai, 2021. "Incorporating spatial interactions in zero-inflated negative binomial models for freight trip generation," Transportation, Springer, vol. 48(5), pages 2335-2356, October.
    13. Pani, Agnivesh & Sahu, Prasanta K. & Patil, Gopal R. & Sarkar, Ashoke K., 2018. "Modelling urban freight generation: A case study of seven cities in Kerala, India," Transport Policy, Elsevier, vol. 69(C), pages 49-64.
    14. Basile, Roberto & Durbán, María & Mínguez, Román & María Montero, Jose & Mur, Jesús, 2014. "Modeling regional economic dynamics: Spatial dependence, spatial heterogeneity and nonlinearities," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 229-245.
    15. Garrido, Rodrigo A. & Mahmassani, Hani S., 2000. "Forecasting freight transportation demand with the space-time multinomial probit model," Transportation Research Part B: Methodological, Elsevier, vol. 34(5), pages 403-418, June.
    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. 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).
    2. Middela, Mounisai Siddartha & Ramadurai, Gitakrishnan, 2024. "Effect of the measurement period and spatial dependence on the accuracy of urban freight trip generation models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
    3. 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.
    4. 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).
    5. Pani, Agnivesh & Sahu, Prasanta K. & Chandra, Aitichya & Sarkar, Ashoke K., 2019. "Assessing the extent of modifiable areal unit problem in modelling freight (trip) generation: Relationship between zone design and model estimation results," Journal of Transport Geography, Elsevier, vol. 80(C).
    6. Agnivesh Pani & Prasanta K. Sahu & Furqan A. Bhat, 2021. "Assessing the Spatial Transferability of Freight (Trip) Generation Models across and within States of India: Empirical Evidence and Implications for Benefit Transfer," Networks and Spatial Economics, Springer, vol. 21(2), pages 465-493, June.
    7. Sanchez-Diaz, Ivan, 2020. "Assessing the magnitude of freight traffic generated by office deliveries," Transportation Research Part A: Policy and Practice, Elsevier, vol. 142(C), pages 279-289.
    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. Krisztin, Tamás, 2018. "Semi-parametric spatial autoregressive models in freight generation modeling," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 121-143.
    11. Leise Kelli de Oliveira & Gracielle Gonçalves Ferreira de Araújo & Bruno Vieira Bertoncini & Carlos David Pedrosa & Francisco Gildemir Ferreira da Silva, 2022. "Modelling Freight Trip Generation Based on Deliveries for Brazilian Municipalities," Sustainability, MDPI, vol. 14(16), pages 1-18, August.
    12. Sowjanya Dhulipala & Gopal R. Patil, 2023. "Regional freight generation and spatial interactions in developing regions using secondary data," Transportation, Springer, vol. 50(3), pages 773-810, June.
    13. Holguín-Veras, José & Ramirez-Rios, Diana & Pérez-Guzmán, Sofía, 2021. "Time-dependent patterns in freight trip generation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 423-444.
    14. Regal, Andrés & Gonzalez-Feliu, Jesús & Rodriguez, Michelle, 2023. "A spatio-functional logistics profile clustering analysis method for metropolitan areas," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).
    15. Rivera-Gonzalez, Carlos & Amaral, Julia C., 2024. "Assessment of freight accessibility in New York City: A spatial-temporal approach," Journal of Transport Geography, Elsevier, vol. 114(C).
    16. Mounisai Siddartha Middela & Gitakrishnan Ramadurai, 2021. "Incorporating spatial interactions in zero-inflated negative binomial models for freight trip generation," Transportation, Springer, vol. 48(5), pages 2335-2356, October.
    17. Gonzalez-Calderon, Carlos A. & Moreno-Palacio, Diana Patricia & Posada-Henao, John Jairo & Quintero-Giraldo, Ricardo & Múnera, César Chavarría, 2022. "Service trip generation modeling in urban areas," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 160(C).
    18. Iván Sánchez-Díaz & José Holguín-Veras & Xiaokun Wang, 2016. "An exploratory analysis of spatial effects on freight trip attraction," Transportation, Springer, vol. 43(1), pages 177-196, January.
    19. Balla, Bhavani Shankar & Sahu, Prasanta K., 2023. "Assessing regional transferability and updating of freight generation models to reduce sample size requirements in national freight data collection program," Transportation Research Part A: Policy and Practice, Elsevier, vol. 175(C).
    20. Iván Sánchez-Díaz & José Holguín-Veras & Xiaokun Wang, 2016. "An exploratory analysis of spatial effects on freight trip attraction," Transportation, Springer, vol. 43(1), pages 177-196, January.

    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:retrec:v:99:y:2023:i:c:s0739885923000367. 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: http://www.elsevier.com/wps/find/journaldescription.cws_home/620614/description#description .

    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.