Customer Behavioral Trends in Online Grocery Shopping During COVID-19

Abstract

The evolution of online shopping started when big players like Amazon began selling all types of merchandise. Customers understood the ease of shopping online, so the trend grew even stronger. It is therefore essential to conduct a study of online shopping usage and the perception of customers during COVID-19, especially in the grocery sector. In this study, approximately 28 respondents from 50 specifically targeted groups were surveyed, and data collection was undertaken through a structured questionnaire. The regression method was conducted to analyze the collected data. Additionally, 5 interviews were conducted to validate and support the findings. Customers definitely preferred online grocery shopping (OGS) services during COVID-19 due to safety, convenience, and government restrictions. The influential factors were very important in this case, like delivery times, good discounts, and the quality of products. Secondly, OGS services were more stable and alert during the pandemic situation, following the government’s rules and restrictions. Customers were extremely satisfied with the safety precautions during COVID-19, the assistance provided through helplines for support, and the increased customer reach to make groceries as accessible as other reputable online departments.

Divisions: College of Business and Social Sciences > Aston Business School
College of Business and Social Sciences > Aston Business School > Operations & Information Management
College of Business and Social Sciences
College of Business and Social Sciences > Aston Business School > Marketing & Strategy
Additional Information: This article published as an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and production in any medium, provided the author of the original work and original publication source are properly credited
Publication ISSN: 1533-7995
Last Modified: 29 Nov 2023 13:31
Date Deposited: 20 Feb 2023 17:26
Full Text Link: 10.4018/JGIM.317081
Related URLs: https://www.igi ... ay/issue/310086 (Publisher URL)
PURE Output Type: Article
Published Date: 2023-01-20
Accepted Date: 2022-12-20
Authors: Chang, Victor
Liu, O.
K.V. Barbole
Xu, Q. A.
Gao, X. J.
Tabrizi, Wendy

Download

[img]

Version: Published Version

License: Creative Commons Attribution

| Preview

Export / Share Citation


Statistics

Additional statistics for this record