Document Type : Original Article
Authors
1
Ph.D. Student in Business Administration, Islamic Azad University, Birjand Branch, Birjand, Iran
2
Assistant professor of marketing, Department of Management, Islamic Azad University, Birjand Branch, Birjand, Iran
3
Department of Public Administration, Birjand Branch, Islamic Azad University, Birjand, Iran
10.22034/cbsj.2024.63063
Abstract
Due to the ever-increasing demand for consumers to buy products from chain stores online and the increase in repeat purchases of these products during the Corona crisis and after, as well as chain stores’ efforts to increase the market share of online sales of their products, the role of this issue has become more prominent. The purpose of this study is to formulate a pattern of online repurchase intention in chain stores using a meta-composite analysis method. For this purpose, through the seven-step model of Sandelowski and Barroso (2006), all research articles on online repurchase intention in chain stores from 2010 to 2022 have been investigated using MAXQDA software. The research findings were presented in the form of five main dimensions, 14 components, and 47 indicators as a conceptual framework of the research. To measure reliability and quality control, the Kappa index was used, which is 0.87 for the constituent factors, which is more than the acceptable value. Based on the findings of this research, firstly, customer characteristics, information and communication technology, product characteristics, marketing activities, and characteristics of chain stores have been identified as the main dimensions to better understand the concept of online repurchase intention in chain stores. Second, developing and integrating knowledge in this field will help future researchers upgrade their online repurchase intention models. Third, it helps chain store managers better understand the main dimensions that increase online sales and create a competitive advantage.
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