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An exploratory analysis of spatial effects on freight trip attraction

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  • Iván Sánchez-Díaz
  • José Holguín-Veras
  • Xiaokun Wang

Abstract

This paper conducts an exploratory analysis of freight trip attraction and its relationship with key features of the urban environment. Using establishment level data, the authors explore the role of business attributes, as well as network and land use descriptors. The research uses data from 343 establishments from five different industry sectors in New York City. These establishments are geo-located, and spatial association indicators are estimated to assess the presence of spatial effects. Spatial econometric techniques are used to assess the role of spatial effects among establishments and the urban environment. The empirical evidence suggests that establishments’ location, such as land-value and front street width, play an important role on freight trip attraction (FTA), and that retail industries located in high employment zones tend to produce higher FTA per employee. Another key finding is that FTA is better modeled using non-linear models for all industry sectors. Specifically, the freight trip attraction of business establishments is concave with employment, flattening as employment increases. This is confirmed by the modeling results for which the range of coefficients estimated for employment reveals that, although larger establishments have higher FTA than small establishments, FTA increases at a diminishing marginal rate. These exploratory findings shed light on the use of locational variables, and nonlinear spatial effects specifications to enhance FTA models. Copyright Springer Science+Business Media New York 2016

Suggested Citation

  • 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.
  • Handle: RePEc:kap:transp:v:43:y:2016:i:1:p:177-196
    DOI: 10.1007/s11116-014-9570-1
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    References listed on IDEAS

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    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. 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.
    3. Wagner, Tina, 2010. "Regional traffic impacts of logistics-related land use," Transport Policy, Elsevier, vol. 17(4), pages 224-229, August.
    4. Hirotugu Akaike, 1987. "Factor analysis and AIC," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 317-332, September.
    5. 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.
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    Cited by:

    1. 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).
    2. 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.
    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. 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.
    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. Sonagnon Hounwanou & Natacha Gondran & Jesus Gonzalez-Feliu, 2016. "Retail location and freight flow generation: proposition of a method estimating upstream and downstream movements generated by city center stores and peripheral shopping centers," Post-Print hal-01357008, HAL.
    7. 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).
    8. Beckers, Joris & Cardenas, Ivan & Sanchez-Diaz, Ivan, 2022. "Managing household freight: The impact of online shopping on residential freight trips," Transport Policy, Elsevier, vol. 125(C), pages 299-311.
    9. 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).
    10. 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.
    11. 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).
    12. 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.
    13. 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.
    14. 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).
    15. 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.
    16. 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.
    17. 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.
    18. 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).
    19. 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.
    20. 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).
    21. 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).
    22. 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.
    23. 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.
    24. Chen, Yu & Lu, Yuqi & Jin, Cheng, 2024. "Spatiotemporal differentiation calendar for car and truck flow on expressways: A case study of Jiangsu, China," Journal of Transport Geography, Elsevier, vol. 116(C).

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