Capurso, M, Hess, S and Dekker, T orcid.org/0000-0003-2313-8419 (2021) Stated consideration and attribute thresholds in mode choice models: a hierarchical ICLV approach. European Journal of Transport and Infrastructure Research, 21 (3). pp. 106-123. ISSN 1567-7133
Abstract
Consideration of alternatives, as many other aspects related to the decision-making process, is not observable and challenging to measure. Even when supplementary information is collected during stated choice experiments, its use as an additional explanatory variable is discouraged due to potential endogeneity issues, measurement error and limited suitability for forecasting. To overcome these limitations, we propose an Integrated Choice and Latent Variable model where consideration of an alternative is treated as a latent variable. The novelty of the presented model is that the latent variable for consideration of an alternative itself is a function of another set of latent variables that represent thresholds applied by the decision maker to individual attributes (such as travel time and cost). The proposed hierarchical relationship between latent thresholds and latent consideration enables us to explain a share of otherwise purely random heterogeneity, and identify the structural drivers of consideration. The latter is of interest to policymakers and private operators.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 Mauro Capurso, Stephane Hess, Thijs Dekker. This is an open access article under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0). |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Choice Modelling |
Depositing User: | Symplectic Publications |
Date Deposited: | 01 Oct 2021 12:19 |
Last Modified: | 25 Jun 2023 22:46 |
Status: | Published |
Publisher: | Delft University of Technology |
Identification Number: | 10.18757/ejtir.2021.21.3.3982 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:178520 |