The Internet is widely acknowledged as a platform for international communication and is increasingly used as the most crucial tool for all businesses engaged in international trade. According to estimates, 52.58 million people in Bangladesh are using the internet in the year 2022. In spite of the fact that online shopping is not nearly as common in Bangladesh as it is in other c ountries, businesses are investing in business-to-consumer (B2C) online shopping. As a result, it is essential to have an understanding of the factors that influence the online purchasing behavior of Bangladeshi consumers. The goal of this study is to create a theoretical research model that will serve as a f ramework for determining the major variables affecting Bangladeshi consumers’ choice to shop online or not. Specifically, this research focuses on the shopping habits of Bangladeshi consumers. In order to collect data, 331 people in Dhaka, Bangladesh, filled out a questionnaire that they had to administer to themselves. Validity and reliability of a measurement model were evaluated with the help of Structural Equation Modelling (SEM) analyses. The measurement model that best fits the data was approved for use based on the suitability index (fit indices). It has been shown to be a reliable instrument, and it has also satisfied the requirements set forth by psychometrics. The analysis of real-generation Multiple Linear Regression (MLR) data analysis identifies important decision-making considerations such as service quality & responsiveness, price, consumer resource, perceived risk, trialability & generational gap, website factor, payment procedure, and demographic consideration. The adoption of online shopping by Bangladeshi consumers is impacted in various ways by each of these factors. In addition to that, some recommendations and suggestions for decision-making are included in this article for researchers in the future.
KeywordsOnline Buying BehaviorTheoretical Research ModelExperiential AnalysisMultiple Linear Regression (MLR)Structural Equation Modelling (SEM)
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