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Modeling urban freight generation: A study of commercial establishments’ freight needs

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  • Sánchez-Díaz, Iván

Abstract

Increasing urbanization, and the environmental and liveability impacts associated with urban activity, have directed attention to the need for sustainable cities. Achieving sustainable urban development requires including freight systems in strategic urban development plans. In this context, joint efforts involving academia and public- and private sector to collect the right data and develop suitable models, can contribute toward a better understanding of establishments’ freight needs, the quantification of freight’s traffic impacts and the development of appropriate methods to support decision making and strategic plans. This paper studies urban commercial establishments’ freight needs and impacts on traffic using data collected from establishments in the City of Gothenburg (Sweden). The data cover different zones of the city and include commercial sectors found typically in urban cores (e.g., retailers, food services, health care, public sector offices and education). The paper introduces a set of statistical models—developed based on regression analyses and discrete choice models—to estimate the number of freight trips produced and attracted per week, and the attraction of weight and volumes of freight. In addition to shed light on the factors determining establishments’ freight- and freight trips generation, the models are designed with the purpose of assisting planning and policy design efforts, thus the explanatory variables are selected based on suitability and availability. The results show that retailers of perishable goods have the highest freight trip generation per establishment, followed by public sector offices and education establishments, retailers of non-perishable goods and restaurants. The results also reveal a heterogeneity between sectors, and a differential business size effect across commercial sectors.

Suggested Citation

  • Sánchez-Díaz, Iván, 2017. "Modeling urban freight generation: A study of commercial establishments’ freight needs," Transportation Research Part A: Policy and Practice, Elsevier, vol. 102(C), pages 3-17.
  • Handle: RePEc:eee:transa:v:102:y:2017:i:c:p:3-17
    DOI: 10.1016/j.tra.2016.06.035
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    References listed on IDEAS

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    Cited by:

    1. 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.
    2. Vasco Silva & António Amaral & Tânia Fontes, 2023. "Sustainable Urban Last-Mile Logistics: A Systematic Literature Review," Sustainability, MDPI, vol. 15(3), pages 1-27, January.
    3. 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).
    4. Pani, Agnivesh & Sahu, Prasanta K., 2019. "Planning, designing and conducting establishment-based freight surveys: A synthesis of the literature, case-study examples and recommendations for best practices in future surveys," Transport Policy, Elsevier, vol. 78(C), pages 58-75.
    5. 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.
    6. 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).
    7. Pani, Agnivesh & Sahu, Prasanta K., 2022. "Modelling non-response in establishment-based freight surveys: A sampling tool for statewide freight data collection in middle-income countries," Transport Policy, Elsevier, vol. 124(C), pages 128-138.
    8. Prasanta K. Sahu & Agnivesh Pani, 2020. "Freight generation and geographical effects: modelling freight needs of establishments in developing economies and analyzing their geographical disparities," Transportation, Springer, vol. 47(6), pages 2873-2902, December.

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