Empirical investigation of the key machine learning elements promoting e-business using an SEM framework

The paper’s research goal is to identify the crucial elements of putting machine learning (ML) techniques into practice in order to improve electronic commerce (E-business) within the organization. In order to improve e-business and achieve sustainable growth, studies have focused on taking into account important determinants of ML impacted demand forecasting, implementation of ML in purchase behavior, improving consumer interaction, and endorse in ultimate cross-selling of the goods. The firm has been able to achieve additional benefits, assist in properly predicting client needs, encourage interaction, and cross-sell more items as a result of the introduction of novel and sophisticated ML technologies. This research will employ a closed-ended questionnaire to collect information from almost 343 business managers of retail E-business firms. It will then employ structural equation modelling (SEM) and SPSS to conduct an initial descriptive study using the data gathered. The article’s major goal is to give readers a detailed and thorough grasp of how ML techniques are used to improve e-business. organizations are forced to implement novel techniques by the volatile business climate in order to boost sales, interact with customers, and improve brand values. Therefore, the focus of this research is mostly on comprehending the ML strategies used by the administration to assist their online business. According to the data, it can be concluded that ML-driven research helps improve user interaction, helps analyze consumer behavior, and keeps track of the goods as they travel from suppliers to buyers. This study concentrates on determining the critical factors that can be used to improve e-business in order to achieve long-term expansion and competitive advantage. E-commerce companies used ML to monitor general consumer behavior and connect customers in a way that would better serve their requirements. The research will be distinctive since it emphasizes examining the influence of ML in E-business in order to give businesses greater guidance on how to utilize the different ML components to achieve their aims and purposes.