Date of Graduation

12-2023

Document Type

Thesis

Degree Name

Master of Science in Civil Engineering (MSCE)

Degree Level

Graduate

Department

Civil Engineering

Advisor/Mentor

Suman Mitra

Committee Member

Hernandez, Sarah

Second Committee Member

Sasidharan, Lekshmi

Keywords

Arkansas, COVID-19 Pandemic, Mode Usage, Travel Behavior, Machine Learning

Abstract

The objective of the study was to investigate the impact of the COVID-19 pandemic on the activity participation and mode usage of older adults residing in Arkansas, a predominantly rural state. Leveraging primary data collected from 1,017 older adult participants, the study employed Latent Class Analysis (LCA) to capture older adults’ heterogeneity in travel behavior and found three distinct classes: Frequent Traveler, Moderate Traveler, and Non-Traveler, based on their activity participation, mode usage during the pandemic and the pandemic’s impact on their trips. Subsequently, a Multinomial Logit Model (MNL) was employed to examine how socio-demographic attributes, residential locations, and health perceptions influence these distinct travel behavior patterns. Results from MNL and descriptive analysis revealed that among the identified classes, Moderate Travelers (Class 2) and Non-Travelers (Class 3), characterized by factors such as being female, having low socio-demographics, and having poor health perceptions, experienced a greater pandemic impact on their activity participation and mode usage compared to the Frequent Traveler class, which had more favorable conditions. Moderate Travelers (Class 2) experienced the most pronounced disruption in activity participation for shopping and civic trips, followed by Non-Travelers (Class 3), and Frequent Travelers (Class 1). Regarding mode usage, car usage was significantly impacted across all classes, with Moderate Travelers (Class 2) showing a particularly notable decrease. Active modes and non-driving transportation alternatives experienced minimal usage across all classes. These findings can offer several policy insights, including addressing the unique needs of different groups of older adults, establishing connections between policies addressing the gender gap, health, transportation, rural-urban disparity, promoting alternative transportation options, and raising awareness among older adults for making plans after their driving cessation.

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