Investigating the Impact of COVID-19 on the Online Food Purchasing Behaviour of University Students Using TAM Model

Abstract

The coronavirus epidemic has transformed the daily lives of people around the world. COVID-19 has also had a significant impact on digital behavior, as strict government measures and restrictions due to the virus have pushed consumers towards safer shopping alternatives. This has led to an unprecedented and dynamic growth in online grocery shopping alongside other leading product categories (clothes, shoes, electronics) (McKinsey & Company, 2021). The primary research was conducted through a questionnaire survey (quantitative method) involving Hungarian and foreign students studying Economics and Business Administration at the University of Debrecen. To reach a higher number of foreign students, we also shared the questionnaire with the Debrecen branch of the International Student Union (ISU) and the International Students in Debrecen group with the permission of the administrators. This research was based on the Technology Acceptance Model (TAM model) and primarily investigated how the attitudes of Hungarian and foreign university students toward online food shopping changed as a result of the COVID-19 outbreak.
The students rated the 18 statements on which the research was based on a Likert scale, taken from Radka and Martin's research. Cronbach's Alpha value proved that the scale was measured correctly, and then data reduction was performed using factor analysis. Further principal component analysis was performed on the statements belonging to three factors to generate cleaner latent variables. This helped to improve technical understanding. Finally, we sorted Hungarian and foreign students into relatively homogeneous groups using the K-means clustering procedure. Thus, four clusters were created within each of the Hungarian and foreign student datasets.