Inverse Discrete Choice Modelling (IDCM): Theoretical and Practical Considerations for Imputing Respondent Attributes from the Patterns of Observed Choices

Title: Inverse Discrete Choice Modelling (IDCM): Theoretical and Practical Considerations for Imputing Respondent Attributes from the Patterns of Observed Choices
Authors: Zhao, Y
Pawlak, J
Polak, J
Item Type: Journal Article
Abstract: The growing availability of geotagged big data has stimulated substantial discussion regarding their usability in detailed travel behaviour analysis. Whilst providing a large amount of spatio-temporal information about travel behaviour, these data typically lack semantic content characterising travellers and choice alternatives. The inverse discrete choice modelling (IDCM) approach presented in this paper proposes that discrete choice models (DCMs) can be statistically inverted and used to attach additional variables from observations of travel choices. Suitability of the approach for inferring socioeconomic attributes of travellers is explored using mode choice decisions observed in London Travel Demand Survey. Performance of the IDCM is investigated with respect to the type of variable, the explanatory power of the imputed variable, and the type of estimator used. This method is a significant contribution towards establishing the extent to which DCMs can be credibly applied for semantic enrichment of passively collected big data sets while preserving privacy.
Issue Date: 14-Nov-2017
Date of Acceptance: 15-Sep-2017
URI: http://hdl.handle.net/10044/1/52590
DOI: https://dx.doi.org/10.1080/03081060.2018.1402745
ISSN: 0308-1060
Publisher: Taylor & Francis
Start Page: 58
End Page: 79
Journal / Book Title: Transportation Planning and Technology
Volume: 41
Issue: 1
Copyright Statement: © 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/ licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Sponsor/Funder: Engineering & Physical Science Research Council (EPSRC)
EPSRC
Cisco International Ltd CIL
Funder's Grant Number: EP/I038837/1
EP/I038837/1
PO No T5200023365
Keywords: 0905 Civil Engineering
1205 Urban And Regional Planning
1507 Transportation And Freight Services
Logistics & Transportation
Publication Status: Published
Appears in Collections:Faculty of Engineering
Civil and Environmental Engineering



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