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An Empirical Evaluation Of Parameter Sensitivity To Choice Set Definition In Shopping Destination Choice Models

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  • Pasquale A. Pellegrini
  • A. Stewart Fotheringham
  • Ge Lin

Abstract

ABSTRACT This paper empirically examines parameter sensitivity to choice set specification in the context of shopping destination choice, using supermarket choice data from Gainesville, Horida. We estimate parameters of the widely applied multinomial logit (MNL) discrete choice mode) multiple times. Each estimation uses, for all observations, a single randomly selected subset of the universal choice set. The distribution of parameter estimates is examined for specific market segments and choice subset sizes. The results indicate that the parameters of the model can be quite sensitive to the selection of the choice set used in the calibration. However, this sensitivity is not even across all parameters and there are some interesting variations. Distance deterrence and chain image parameters, for example, exhibit much more stability than parameters for store size and store competition. Li addition, model parameters show encouraging stability with relatively small choice sets of seven to ten stores.

Suggested Citation

  • Pasquale A. Pellegrini & A. Stewart Fotheringham & Ge Lin, 1997. "An Empirical Evaluation Of Parameter Sensitivity To Choice Set Definition In Shopping Destination Choice Models," Papers in Regional Science, Wiley Blackwell, vol. 76(2), pages 257-284, April.
    • Handle: RePEc:bla:presci:v:76:y:1997:i:2:p:257-284
    DOI: 10.1111/j.1435-5597.1997.tb00691.x
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    Cited by:

    1. Arthur (Yan) Huang & David Levinson, 2015. "Axis of travel: Modeling non-work destination choice with GPS data," Working Papers 000113, University of Minnesota: Nexus Research Group.
    2. Kang, Sanggyun, 2020. "Warehouse location choice: A case study in Los Angeles, CA," Journal of Transport Geography, Elsevier, vol. 88(C).
    3. Tsoleridis, Panagiotis & Choudhury, Charisma F. & Hess, Stephane, 2022. "Utilising activity space concepts to sampling of alternatives for mode and destination choice modelling of discretionary activities," Journal of choice modelling, Elsevier, vol. 42(C).
    4. Sylvia Y. He & Genevieve Giuliano, 2018. "School choice: understanding the trade-off between travel distance and school quality," Transportation, Springer, vol. 45(5), pages 1475-1498, September.
    5. Scott, Darren M. & He, Sylvia Y., 2012. "Modeling constrained destination choice for shopping: a GIS-based, time-geographic approach," Journal of Transport Geography, Elsevier, vol. 23(C), pages 60-71.
    6. Huang, Arthur & Levinson, David, 2017. "A model of two-destination choice in trip chains with GPS data," Journal of choice modelling, Elsevier, vol. 24(C), pages 51-62.
    7. Berjisian, Elmira & Habibian, Meeghat, 2019. "Developing a pedestrian destination choice model using the stratified importance sampling method," Journal of Transport Geography, Elsevier, vol. 77(C), pages 39-47.
    8. Wissam Qassim Al-Salih & Domokos Esztergár-Kiss, 2021. "Linking Mode Choice with Travel Behavior by Using Logit Model Based on Utility Function," Sustainability, MDPI, vol. 13(8), pages 1-18, April.
    9. Oshan, Taylor M., 2020. "The spatial structure debate in spatial interaction modeling: 50 years on," OSF Preprints 42vxn, Center for Open Science.
    10. Kurt Jörnsten & Inge Thorsen & Jan Ubøe, 2004. "Replication/Prediction Problems in the Journey to Work," Environment and Planning A, , vol. 36(2), pages 347-364, February.
    11. Jan Ubøe, 2004. "Aggregation of Gravity Models for Journeys to Work," Environment and Planning A, , vol. 36(4), pages 715-729, April.
    12. Jens P Gitlesen & Inge Thorsen, 2000. "A Competing Destinations Approach to Modeling Commuting Flows: A Theoretical Interpretation and An Empirical Application of the Model," Environment and Planning A, , vol. 32(11), pages 2057-2074, November.

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