The use of food delivery apps during the COVID-19 pandemic in Brazil: The role of solidarity, perceived risk, and regional aspects

Food Res Int. 2021 Nov:149:110671. doi: 10.1016/j.foodres.2021.110671. Epub 2021 Aug 28.

Abstract

This study aimed to evaluate the use of food delivery apps (FDA) during the COVID-19 pandemic in Brazil. A total of 950 questionnaires were collected, covering four Brazilian regions: Southeast, Central-West, Northeast, and South. The data was collected during the peak of the second wave of the pandemic. A questionnaire with 39 measurement items was applied using an online survey. These items were evaluated using a five-point Likert scale covering the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). The data was analyzed using covariance-based structural equation modeling. About 47% of consumers use FDA weekly. The continuance intention of FDA during the pandemic in Brazil was affected by performance expectancy (β = 0.496; p < 0.001), social influence (β = 0.094; p < 0.001), hedonic motivation (β = 0.068; p = 0.026), price value (β = 0.103; p < 0.001), habit (β = 0.305; p < 0.001), frequency of using FDA (β = 0.051; p = 0.039), and solidarity with the foodservice sector (β = 0.090; p < 0.001). It was also observed that the continuance intention reduces risk perception (β = -0.403; p < 0.001), and risk perception reduces the frequency of using FDA (β = -0.178; p < 0.001). The results indicate that the UTAUT2 strongly explains consumers' continuance intention. Differences in path estimates among Brazilian regions were observed, indicating some regional differences. It was possible to observe a tendency of using FDA during and after the pandemic, motivated by several factors. The FDA developers and foodservice managers could use this data to improve their services. Policies must be established to increase consumer and employee safety during the delivery service.

Keywords: Consumer behavior; Continuance intention; Foodservice; SARS-CoV-2; Structural equation modeling; UTAUT.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Brazil / epidemiology
  • COVID-19*
  • Humans
  • Intention
  • Pandemics* / prevention & control
  • SARS-CoV-2