Determinants of E-Commerce Demand, Travel Behavior, and Travel-Related Expenditures Among U.S. Households

This research investigates how rapid growth in e-commerce and consumer travel-related expenditure influences household travel demand, their mode choice, and transportation spending behavior in the United States. The time frame of the dataset focuses on the post-COVID-19 era. It uses the data from the 2022 U.S. National Household Travel Survey (NHTS) and the first quarter of 2019 - 2024 American Consumer Expenditure Survey (ACES). NHTS, a national data source that allows analysis of people's characteristics and household travel, including daily non-commercial travel across all modes. ACES collects detailed information on consumers' incomes and purchasing habits. For travel-related expenditures, the survey reports spending amounts by travel mode and trip-related categories. The research examines the interaction and factors influencing online shopping and consumer purchasing habits, along with their corresponding mode-choice behavior, using Negative Binomial (NB), Zero-Inflated Binomial Regression (ZINB), a Joint Bayesian Bivariate model, and a Log-Transformed Cobb-Douglas Demand function. The results from online shopping reveal that several socio-demographic variables, such as household members, car ownership, number of workers, adults, and young children in the households, education, and income, significantly influence the frequency of online shopping and mode preference. The results also show that households with more drivers make fewer online purchases, whether for goods, food, or groceries. However, larger households tend to make more online purchases. Due to COVID-19, individuals who order online less are more likely to use public transit or ride share and less likely to drive. Also, individuals who use public transit more often than before the COVID-19 pandemic is less likely to have goods delivered to them. Regarding the ACES, the result shows that transportation and lodging expenditure consistently accounted for the largest share of total trip spending, followed by food, entertainment, and alcoholic beverages. Public transportation use and gas and oil expenditures emerged as the most significant predictors of total trip spending. Another result suggests that during the COVID-19 pandemic, spending on public transportation decreased as a proportion of total trip expenditures, but spending on leased autos, trucks, and vans increased, likely due to safety concerns. People who spend more on vehicle insurance tend to reduce their travel activity and trip-related spending in response to uncertainty at the start of the pandemic in 2020. This research provides insight into how e-commerce and consumer spending behavior would affect mode choice, travel demand, and transportation expenditure, and how policyholders can use it as a resource to improve transportation policy.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Civil Engineering

Department dc:contributor.department

Civil and Environmental Engineering

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2025

Author dc:creator

• Chen, Xiaomin

Chair dc:contributor.committeechair

• HASNINE, MD SAMI

Committee members dc:contributor.committeemember

• Brand, Alexander S.
• Chowdhury, Sudipta

• E-commerce
• Delivery Frequency
• Mode Frequency
• Travel Behavior
• Count Data model
• Bayesian Bi-variate model
• Transportation Expenditures
• Cobb-Douglas Production Function

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language.iso

en

Dc Identifier Other

vt_gsexam:45171

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/139879