A random intercept latent transition analysis (RI-LTA) of consumer spending across online and in-person channels through the pandemic

Divyakant Tahlyan; Hani Mahmassani; Amanda Stathopoulos; Maher Said; Joan Walker; Susan Shaheen

doi:10.1016/j.trc.2025.105010

A random intercept latent transition analysis (RI-LTA) of consumer spending across online and in-person channels through the pandemic

Divyakant Tahlyan, Hani Mahmassani^*, Amanda Stathopoulos, Maher Said, Joan Walker, Susan Shaheen

^*Corresponding author for this work

Civil and Environmental Engineering

Research output: Contribution to journal › Article › peer-review

Abstract

In this study, we utilize a latent transition analysis with random intercept (RI-LTA) framework to understand the changes to consumer spending landscape through the pandemic across various product categories and acquisition channels. Using data from 785 individuals from across United States at four different time points (pre-COVID, December 2020, March 2021, and March 2022), the presented model revealed five different behavioral classes of consumer spending and the dynamics of movement between classes as a result of the pandemic. The results from the model also revealed that the pandemic's single biggest impact was in terms of suppression of demand for dine-in and take-out of food − potentially due to it being a high-risk activity. However, over time a reversal of this behavior is seen, back to an increased dine-in and food take-out activity. The second significant behavioral transition was of movement towards delivery and pick-up services where about 2–3-fold increase in their usage is visible — a large portion of which appears to be stable over time, more so in the case of delivery than pick-up.

Original language	English (US)
Article number	105010
Journal	Transportation Research Part C: Emerging Technologies
Volume	171
DOIs	https://doi.org/10.1016/j.trc.2025.105010
State	Published - Feb 2025

Funding

Partial funding for the research on which this paper is based is provided the U.S Department of Transportation Tier I University Transportation Center on Telemobility awarded to Northwestern University in partnership with University of California, Berkeley and the University of Texas, Austin. Partial support received by the first author through Northwestern University Transportation Center's Dissertation Year Fellowship is gratefully acknowledged. The contents remain the sole responsibility of the authors and do not necessarily reflect the position of the sponsoring agency.

Keywords

Consumer spending
Delivery services
E-commerce
Hybrid shopping
Latent transitions analysis
Online channels
Pandemic
Random intercept
Telemobility

ASJC Scopus subject areas

Civil and Structural Engineering
Automotive Engineering
Transportation
Management Science and Operations Research

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10.1016/j.trc.2025.105010

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title = "A random intercept latent transition analysis (RI-LTA) of consumer spending across online and in-person channels through the pandemic",

abstract = "In this study, we utilize a latent transition analysis with random intercept (RI-LTA) framework to understand the changes to consumer spending landscape through the pandemic across various product categories and acquisition channels. Using data from 785 individuals from across United States at four different time points (pre-COVID, December 2020, March 2021, and March 2022), the presented model revealed five different behavioral classes of consumer spending and the dynamics of movement between classes as a result of the pandemic. The results from the model also revealed that the pandemic's single biggest impact was in terms of suppression of demand for dine-in and take-out of food − potentially due to it being a high-risk activity. However, over time a reversal of this behavior is seen, back to an increased dine-in and food take-out activity. The second significant behavioral transition was of movement towards delivery and pick-up services where about 2–3-fold increase in their usage is visible — a large portion of which appears to be stable over time, more so in the case of delivery than pick-up.",

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author = "Divyakant Tahlyan and Hani Mahmassani and Amanda Stathopoulos and Maher Said and Joan Walker and Susan Shaheen",

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AU - Said, Maher

AU - Walker, Joan

AU - Shaheen, Susan

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A random intercept latent transition analysis (RI-LTA) of consumer spending across online and in-person channels through the pandemic

Abstract

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Keywords

ASJC Scopus subject areas

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