Files
Abstract
With the development of technology and e-commerce, consumers’ online shopping behavior is a popular field being explored by many researchers, especially regarding its factors involving social environments, features of products, merchants activities and customers’ own characteristics. As the outbreak of COVID-19 pandemic, the online grocery sales shows an increasing trend. Regarding the driving force of the increase, how have different consumer groups’ online grocery shopping behavior been affected by the pandemic differently? The paper investigates the question using the first-hand data obtained from a survey with 905 responses via Amazon Mechanical Turk platform. The survey is designed concerning customers’ demographic features including age, gender, education and income, and also shopping behavior including shopping frequency, spending and choice of channel. The analysis relies on methods including descriptive statistics, Spearman Correlation Coefficient, McNemar test, Logistic regression and OLS regression. Results suggest that customers’ age, gender and household plays a role in the heterogeneity in the influence of the pandemic on online grocery shopping.