Throughout the COVID-19 pandemic, online and in-store shopping behaviors changed significantly. As the pandemic subsides, key questions are why those changes happened, whether they are expected to stay, and, if so, to what extent. We answered those questions by analyzing a quasi-longitudinal survey dataset of the Puget Sound residents (Washington, U.S.). We deployed structural equation modeling (SEM) to build separate models for food, grocery, and other items shopping to explore the factors affecting such changes. The results revealed that people’s online and in-store shopping frequencies during the pandemic were affected by their perceived health risks, attitudes toward shopping, and pre-pandemic shopping frequencies. Similarly, it was shown that how frequently people expect to shop post pandemic is influenced by their attitudes toward shopping, changes during the pandemic, and their pre-pandemic frequencies. We also classified respondents into five groups, based on their current and expected future shopping behavior changes, and performed a descriptive analysis. The five groups—Increasers, Decreasers, Steady Users, Returnees, and Future Changers—exhibited different trends across online and in-store activities for shopping different goods. The analysis results showed that, while 25% of the respondents increased their online shopping, only 8% to 13% decreased their in-store activities, implying that online shopping did not completely substitute in-store shopping. Moreover, we found that online shopping is a substitution for in-store shopping for groceries, while it complements in-store shopping for food and other items. Additionally, more than 75% of new online shoppers expect to keep purchasing online, while 63%–85% of in-store Decreasers plan to return to their pre-pandemic frequencies.

The rise of e-commerce, busy lifestyles, and the convenience of next- and same-day home deliveries have resulted in exponential growth of online shopping in the U.S., rising from 5% of the total retail in 2011 to 15% in 2020, and it is expected to grow even further in the future. Worldwide, spending on e-commerce passed $4.9 trillion in 2021 and it is projected to surge to $7 trillion by 2025.

In the past few years, there has been ongoing research on how this growth would change people’s travel patterns and whether its effect on in-person activities would be substitution, complementing, or modification. However, there is no single answer to this question, given different product types, regions, demographics, and primary travel modes.

While online purchasing had already been experiencing a growth every year before 2020, the pandemic accelerated this trend. In 2020, online shopping constituted more than 20% of total spending on consumer goods worldwide in comparison to 16.4% in 2019 and 14.4% in 2018. Before COVID-19, it was predicted that total e-commerce sales in the U.S. would grow up to $674.88 billion, yet the actual number turned out to be $799.18 billion. With a 15.9% growth, the U.S. is among the top 10 countries with the highest growth rate in online retail shopping in 2022.

Embracing digital technologies and bringing shops into homes are among the immediate impacts of the pandemic restrictions and lockdowns, with the majority of people reducing their frequency of going to stores and adopting alternative shopping approaches such as curbside pick-up and home delivery. Based on the reports by the U.S. Bureau of Transportation Statistics (BTS), in Nov–Dec 2020, when the penetration of the coronavirus reached its first peak in the U.S., the percentage of people who decided to shop online instead of going to stores increased by up to 10%. During the early pandemic, about 35% of U.S. workers switched to remote working, and from March to April 2020, the average daily number of people staying home increased by 32 million and the total number of trips decreased by 2.5B. Dining-in restaurants were also banned in half of the U.S. states for several months in 2020, which resulted in a significant drop in the restaurant dine-in demand and shifted people toward online food delivery services, and buying groceries online rather than going to store.

These changes were also influenced by socio-demographic characteristics. For instance, according to the BTS, the percentage of people with an annual income close to $125,000 who replaced their in-store shopping by online shopping in Nov–Dec 2020 was twice those with an annual income of $25,000. People in the neighborhoods with higher number of positive COVID-19 cases or higher spread rate of positive new cases were more likely to change their in-store shopping to online-shopping. Senior people were also shown to have higher tendency to shop online compared with younger generations, perhaps because of health and safety concerns. It is worth noting that these changes were not the same across all products; for example, online sales of food and beverage in the U.S. doubled in 2020, while home furniture online sales only increased by about 50%.

Another factor that is proved to have a major effect on people’s shopping behaviors and travel patterns during the pandemic is their risk perception and fears for their health. Irawan et al. found that perceiving COVID-19 as a severe disease decreased people’s tendency to do in-store grocery shopping. Similarly, Moon et al. found out that, during the pandemic, people who considered themselves less vulnerable to the infection were less likely to use online channels for shopping. Several studies have mentioned that the perceived health risk varies among different groups of population and depends on region, age, gender, education, race, and marital status.

Moreover, people’s online and in-store shopping behaviors are affected by their socio-demographic factors and their attitudes toward the activity. The advantages and disadvantages of online shopping over in-store shopping play a role in attitudes toward the activity. The advantages, such as receiving goods without leaving home, having access to a wider variety of products and information, and being able to compare them easily and efficiently, result in a positive attitude toward online shopping, especially during the pandemic given high perceived health risk, formal penalties, or both. On the other hand, online shopping has some disadvantages, such as transaction security concerns and long delivery times, and in-store shopping offers specific benefits, such as the ability to see, touch, feel, and try the products, ensuring the store’s environment quality, immediate possession of the product, social interaction, and entertainment. Therefore, even during the pandemic, some people maintained frequent in-store shopping trips.

Whether the pandemic-induced changes in online and in-store shopping are permanent is still debatable. Sheth discussed that people may find the new routine more convenient, affordable, and accessible, and therefore stick to it even after the pandemic is over. On the contrary, Dannenberg et al. argued that people’s motives to shop online only hold for the time of crisis, and online retailing will decline when circumstances change. Watanabe and Omori showed that most people used to shop online long before the pandemic, and they merely increased their frequency because of infection risk. So, the reasons behind the surge in online shopping might dissipate as COVID-19 recedes.

In this paper, we study how online and in-store shopping behaviors for different goods were affected during COVID-19, and whether those changes are expected to stay post pandemic. We analyze a quasi-longitudinal survey dataset from the Puget Sound region in Washington State, U.S., that includes data on people’s shopping behavior before and during pandemic, as well as their expected shopping behavior after pandemic. The dataset also contains information on socio-demographic characteristics, as well as psychometric questions about COVID-19 risk perception and attitudes toward shopping. Through descriptive analysis and structural equation modeling (SEM), we explore the factors that directly or indirectly affected people’s three shopping activities (online and in-store), for food, grocery, and other items (clothing, home goods, etc.), and investigate the similarities and differences amongst them.

This study is distinguished in several ways from the previous ones that investigated the impacts of COVID-19 on people’s shopping behavior: (1) it applies a unique descriptive analysis by classifying respondents based on their current and expected future shopping trends and studies how socio-demographic characteristics (directly and indirectly) influence people’s shopping behaviors by analyzing the similarities and differences between those groups; (2) it models online and in-store shopping jointly, considering covariations and dependencies between those two modes; (3) it applies the same methodology and set of variables to three different shopping activities (for food, grocery, and other items) and compares and contrasts their observed/expected trends and influencing factors; and (4) in addition to socio-demographic and attitudinal variables, it considers people’s baseline shopping behaviors (how frequently they shopped online and in-store before the pandemic) as factors affecting their expected post-pandemic shopping behaviors.