Abstract

During the past two to three decades, and especially during the Covid-19 pandemic, e-shopping has become increasingly popular, changing the way people shop and travel. With increasing concerns about the environmental impacts of transportation, particularly on regional air quality and on emissions of greenhouse gases (GHG), it is important to understand how e-shopping has affected household travel behavior. In this dissertation, I investigated the influence of e-shopping before, during, and after the pandemic by analyzing data from the 2009 and the 2017 U.S. National Household Travel Surveys (NHTS), from the 2017 American Time Use Survey (ATUS), and from an IPSOS survey of Californians conducted in late May 2021. Understanding changes in shopping is essential to business owners, logistics managers (for adapting supply chains), transportation planners (for mitigating the impacts of warehousing and of additional residential freight deliveries), and policymakers (for helping at-risk and underserved groups). This dissertation has three parts. In the first part, I estimated zero-inflated negative binomial models to analyze factors that affected residential deliveries before the pandemic based on the 2009 and 2017 NHTS. I found that e-shoppers in the U.S. were more varied in 2017 than in 2009. Households with more females, higher incomes, and more education, received more deliveries. I also analyzed the 2017 ATUS to explore factors that influence grocery shopping. I found that in-store grocery shoppers were more likely to be female and unemployed but less likely to be younger, to have less than a college education, and to be African American. In contrast, online grocery shoppers were more likely to be female. In the second part, I studied the impact of e-shopping on household travel using propensity score matching. My analysis of 2017 NHTS data showed that before the pandemic, greater online shopping was associated with more frequent trips and slightly more travel. Furthermore, the extent to which an increase in the number of activities translated into more travel depends on population density, the day of the week, the frequency of online shopping, and the type of activity. In the third part, I analyzed the impact of the Covid-19 pandemic on grocery shopping frequency in-store, and online with home delivery (e-grocery) or pickup (click-and-pick), to understand how they changed due to the pandemic, and how they may change after, using ordered models and structural equation models. My results showed that Californians kept shopping for groceries in brick-and-mortar stores during the pandemic but less frequently than before. The pandemic accelerated the adoption of e-grocery and click-and-pick with some strong generation effects: younger generations were more likely to experiment with e-grocery and click-and-pick, while older generations relied more on in-store shopping. Education also made a difference, but thankfully race did not impact the use of e-grocery and click-and-pick, and intentions to use e-grocery and click-and-pick (but it did affect in-store grocery shopping before). My results also illustrated the heterogeneity of Hispanics. As expected, tech-savvy households were much more likely to embrace e-grocery and click-and-pick.