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Title: Representing heterogeneity in structural relationships among multiple choice variables using a latent segmentation approach

Abstract

Travel model systems often adopt a single decision structure that links several activity-travel choices together. The single decision structure is then used to predict activity-travel choices, with those downstream in the decision-making chain influenced by those upstream in the sequence. The adoption of a singular sequential causal structure to depict relationships among activity-travel choices in travel demand model systems ignores the possibility that some choices are made jointly as a bundle as well as the possible presence of structural heterogeneity in the population with respect to decision-making processes. As different segments in the population may adopt and follow different causal decision-making mechanisms when making selected choices jointly, it would be of value to develop simultaneous equations model systems relating multiple endogenous choice variables that are able to identify population subgroups following alternative causal decision structures. Because the segments are not known a priori, they are considered latent and determined endogenously within a joint modeling framework proposed in this paper. The methodology is applied to a national mobility survey data set to identify population segments that follow different causal structures relating residential location choice, vehicle ownership, and car-share and mobility service usage. It is found that the model revealing three distinctmore » latent segments best describes the data, confirming the efficacy of the modeling approach and the existence of structural heterogeneity in decision-making in the population. Future versions of activity-travel model systems should strive to incorporate such structural heterogeneity to better reflect varying decision processes across population subgroups.« less

Authors:
; ; ; ;
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
U.S. Department of Transportation (DOT)
OSTI Identifier:
1441173
Report Number(s):
NREL/JA-5400-71683
Journal ID: ISSN 0049-4488
DOE Contract Number:  
AC36-08GO28308
Resource Type:
Journal Article
Journal Name:
Transportation
Additional Journal Information:
Journal Volume: none; Journal Issue: none; Journal ID: ISSN 0049-4488
Publisher:
Springer
Country of Publication:
United States
Language:
English
Subject:
30 DIRECT ENERGY CONVERSION; causal relationships; structural heterogeneity; simultaneous equations models; latent segmentation; joint estimation; vehicle ownership; residential location choice; mobility service usage

Citation Formats

Astroza, Sebastian, Garikapati, Venu M., Pendyala, Ram M., Bhat, Chandra R., and Mokhtarian, Patricia L. Representing heterogeneity in structural relationships among multiple choice variables using a latent segmentation approach. United States: N. p., 2018. Web. doi:10.1007/s11116-018-9882-7.
Astroza, Sebastian, Garikapati, Venu M., Pendyala, Ram M., Bhat, Chandra R., & Mokhtarian, Patricia L. Representing heterogeneity in structural relationships among multiple choice variables using a latent segmentation approach. United States. doi:10.1007/s11116-018-9882-7.
Astroza, Sebastian, Garikapati, Venu M., Pendyala, Ram M., Bhat, Chandra R., and Mokhtarian, Patricia L. Sat . "Representing heterogeneity in structural relationships among multiple choice variables using a latent segmentation approach". United States. doi:10.1007/s11116-018-9882-7.
@article{osti_1441173,
title = {Representing heterogeneity in structural relationships among multiple choice variables using a latent segmentation approach},
author = {Astroza, Sebastian and Garikapati, Venu M. and Pendyala, Ram M. and Bhat, Chandra R. and Mokhtarian, Patricia L.},
abstractNote = {Travel model systems often adopt a single decision structure that links several activity-travel choices together. The single decision structure is then used to predict activity-travel choices, with those downstream in the decision-making chain influenced by those upstream in the sequence. The adoption of a singular sequential causal structure to depict relationships among activity-travel choices in travel demand model systems ignores the possibility that some choices are made jointly as a bundle as well as the possible presence of structural heterogeneity in the population with respect to decision-making processes. As different segments in the population may adopt and follow different causal decision-making mechanisms when making selected choices jointly, it would be of value to develop simultaneous equations model systems relating multiple endogenous choice variables that are able to identify population subgroups following alternative causal decision structures. Because the segments are not known a priori, they are considered latent and determined endogenously within a joint modeling framework proposed in this paper. The methodology is applied to a national mobility survey data set to identify population segments that follow different causal structures relating residential location choice, vehicle ownership, and car-share and mobility service usage. It is found that the model revealing three distinct latent segments best describes the data, confirming the efficacy of the modeling approach and the existence of structural heterogeneity in decision-making in the population. Future versions of activity-travel model systems should strive to incorporate such structural heterogeneity to better reflect varying decision processes across population subgroups.},
doi = {10.1007/s11116-018-9882-7},
journal = {Transportation},
issn = {0049-4488},
number = none,
volume = none,
place = {United States},
year = {2018},
month = {5}
}

Works referenced in this record:

Exploring the relationship between vehicle type choice and distance traveled: a latent segmentation approach
journal, February 2017


A new generalized heterogeneous data model (GHDM) to jointly model mixed types of dependent variables
journal, September 2015


A simultaneous model of household activity participation and trip chain generation
journal, June 2000


On allowing a general form for unobserved heterogeneity in the multiple discrete–continuous probit model: Formulation and application to tourism travel
journal, April 2016

  • Bhat, Chandra R.; Astroza, Sebastian; Bhat, Aarti C.
  • Transportation Research Part B: Methodological, Vol. 86
  • DOI: 10.1016/j.trb.2016.01.012

Investigation of Heterogeneity in Vehicle Ownership and Usage for the Millennial Generation
journal, January 2017

  • Lavieri, Patrícia S.; Garikapati, Venu M.; Bhat, Chandra R.
  • Transportation Research Record: Journal of the Transportation Research Board, Vol. 2664, Issue 1
  • DOI: 10.3141/2664-10

An Exploration of the Relationship between Timing and Duration of Maintenance Activities
journal, November 2004


A comprehensive analysis of built environment characteristics on household residential choice and auto ownership levels
journal, June 2007

  • Bhat, Chandra R.; Guo, Jessica Y.
  • Transportation Research Part B: Methodological, Vol. 41, Issue 5
  • DOI: 10.1016/j.trb.2005.12.005

Hypothesis Testing with Scanner Data: The Advantage of Bayesian Methods
journal, November 1990

  • Allenby, Greg M.
  • Journal of Marketing Research, Vol. 27, Issue 4
  • DOI: 10.2307/3172624

An Endogenous Segmentation Mode Choice Model with an Application to Intercity Travel
journal, February 1997


The maximum approximate composite marginal likelihood (MACML) estimation of multinomial probit-based unordered response choice models
journal, August 2011


Analysis of Lifestyle Choices: Neighborhood Type, Travel Patterns, and Activity Participation
journal, January 2002

  • Krizek, Kevin J.; Waddell, Paul
  • Transportation Research Record: Journal of the Transportation Research Board, Vol. 1807, Issue 1
  • DOI: 10.3141/1807-15

Are Millennials Really the “Go-Nowhere” Generation?
journal, April 2015


Activity patterns, time use, and travel of millennials: a generation in transition?
journal, June 2016


An exploration of the relationship between mode choice and complexity of trip chaining patterns
journal, January 2007

  • Ye, Xin; Pendyala, Ram M.; Gottardi, Giovanni
  • Transportation Research Part B: Methodological, Vol. 41, Issue 1
  • DOI: 10.1016/j.trb.2006.03.004

The impact of residential neighborhood type on travel behavior: A structural equations modeling approach
journal, August 2002

  • Bagley, Michael N.; Mokhtarian, Patricia L.
  • The Annals of Regional Science, Vol. 36, Issue 2
  • DOI: 10.1007/s001680200083

Do changes in neighborhood characteristics lead to changes in travel behavior? A structural equations modeling approach
journal, June 2007


A mathematical theory of traffic hysteresis
journal, February 1999


Modeling children’s school travel mode and parental escort decisions
journal, November 2007


Modeling Interdependence in Household Residence and Workplace Choices
journal, January 2007

  • Waddell, Paul; Bhat, Chandra; Eluru, Naveen
  • Transportation Research Record: Journal of the Transportation Research Board, Vol. 2003, Issue 1
  • DOI: 10.3141/2003-11

Hypothesis Testing with Scanner Data: The Advantage of Bayesian Methods
journal, November 1990