Finite mixture (or latent class) modeling in transportation: Trends, usage, potential, and future directions
Sung Hoo Kim and
Patricia Mokhtarian
Transportation Research Part B: Methodological, 2023, vol. 172, issue C, 134-173
Abstract:
Accounting for some types of heterogeneity has been an important pathway to improving our models in the transportation domain, specifically in travel behavior research. This study examines the finite mixture modeling (latent class modeling) framework, which has been an appealing approach to that end. Through a comprehensive and systematic review, the paper aims to provide a broader understanding of the usage landscape and also insights into detailed elements. We firstly set up the mixture modeling framework; outline an arena of various relevant research fields; and explain how it is connected to transportation analyses. Then, by using the Scopus database, we explore relevant papers to investigate macroscopic trends in usage of the methodology (yearly trends and research topics). We identify six subdomains in transportation with the aid of nonnegative matrix factorization. We examine several components of the mixture modeling framework in detail. Each subsection covers certain elements of the framework and thus illuminates the landscape of usage and related issues: eight types of heterogeneity; two modeling approaches (exploratory and confirmatory); types of problems (supervised and unsupervised learning); membership model; outcome model; selecting the number of classes; comparisons with competing models; and software and estimation. At the end, we present a few current frontiers and potential directions for future research, and offer further discussion on several issues that arise in the context of mixture models.
Keywords: Mixture model; Finite mixture; Latent class model; Heterogeneity; Market segmentation; Nonnegative matrix factorization (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations: View citations in EconPapers (8)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S019126152300036X
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:transb:v:172:y:2023:i:c:p:134-173
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01
DOI: 10.1016/j.trb.2023.03.001
Access Statistics for this article
Transportation Research Part B: Methodological is currently edited by Fred Mannering
More articles in Transportation Research Part B: Methodological from Elsevier
Bibliographic data for series maintained by Catherine Liu ().