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Alternative approaches to trip distribution modelling: A retrospective review and suggestions for combining different approaches

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  • Ennio Cascetta
  • Francesca Pagliara
  • Andrea Papola

Abstract

. Various alternative approaches are available in the literature for modelling trip distribution. The objective of this paper is to provide a review of this literature with the view of summarising the general nature of the current state of practise and what is now available for practical modelling work. Both aggregate and disaggregate destination choice models are considered, a classification of them will be proposed and suggestions for further research will be given as well. One outcome of this review is that significant contributions are emerging from mixed models (e.g., gravity‐opportunity, random utility, intervening opportunities models, etc). In particular, the review will highlight the benefit of integrating different approaches like the introduction of intervening opportunities factors within random utility models.

Suggested Citation

  • Ennio Cascetta & Francesca Pagliara & Andrea Papola, 2007. "Alternative approaches to trip distribution modelling: A retrospective review and suggestions for combining different approaches," Papers in Regional Science, Wiley Blackwell, vol. 86(4), pages 597-620, November.
    • Handle: RePEc:bla:presci:v:86:y:2007:i:4:p:597-620
    DOI: 10.1111/j.1435-5957.2007.00135.x
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    References listed on IDEAS

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    1. Marcellino, Massimiliano & Banerjee, Anindya & Masten, Igor, 2005. "Forecasting macroeconomic variables for the new member states of the European Union," Working Paper Series 482, European Central Bank.
    2. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, September.
    3. John R. Roy, 2004. "Spatial Interaction Modelling," Advances in Spatial Science, Springer, number 978-3-540-24807-1.
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    1. Tim Schlaich & Abigail L. Horn & Marcel Fuhrmann & Hanno Friedrich, 2020. "A Gravity-Based Food Flow Model to Identify the Source of Foodborne Disease Outbreaks," IJERPH, MDPI, vol. 17(2), pages 1-20, January.
    2. De Valck, Jeremy & Broekx, Steven & Liekens, Inge & Aertsens, Joris & Vranken, Liesbet, 2014. "Testing the influence of substitutes in nature valuation by using spatial discounting factors," Working Papers 182808, Katholieke Universiteit Leuven, Centre for Agricultural and Food Economics.
    3. Javier Rubio-Herrero & Jesús Muñuzuri, 2021. "Indirect estimation of interregional freight flows with a real-valued genetic algorithm," Transportation, Springer, vol. 48(1), pages 257-282, February.
    4. S. Veenstra & T. Thomas & S. Tutert, 2010. "Trip distribution for limited destinations: a case study for grocery shopping trips in the Netherlands," Transportation, Springer, vol. 37(4), pages 663-676, July.
    5. Piyapong Suwanno & Chaiwat Yaibok & Noriyasu Tsumita & Atsushi Fukuda & Kestsirin Theerathitichaipa & Manlika Seefong & Sajjakaj Jomnonkwao & Rattanaporn Kasemsri, 2023. "Estimation of the Evacuation Time According to Different Flood Depths," Sustainability, MDPI, vol. 15(7), pages 1-23, April.
    6. Oshan, Taylor M., 2022. "Spatial Interaction Modeling," OSF Preprints m3ah8, Center for Open Science.
    7. Cordera, Rubén & Sañudo, Roberto & dell’Olio, Luigi & Ibeas, Ángel, 2018. "Trip distribution model for regional railway services considering spatial effects between stations," Transport Policy, Elsevier, vol. 67(C), pages 77-84.

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