首页|Study Results from Faculty of Economics and Management Broaden Understanding of Machine Learning (Analyzing and Forecasting ECommerce Adoption Drivers Among SM Es: A Machine Learning Approach)
Study Results from Faculty of Economics and Management Broaden Understanding of Machine Learning (Analyzing and Forecasting ECommerce Adoption Drivers Among SM Es: A Machine Learning Approach)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in artific ial intelligence. According to news originating from the Faculty of Economics an d Management by NewsRx correspondents, research stated, “This paper investigated the factors in the technology-organization-environment (TOE) framework that aff ect the decision of whether to adopt electronic commerce (EC) or not within smal l- and medium-sized enterprises (SMEs).” Our news editors obtained a quote from the research from Faculty of Economics an d Management: “To this end, a questionnaire-based survey was conducted to collec t data from 60 managers or owners of manufacturing SMEs in Tunisia. Unlike the t raditional regression approaches, we referred to novel machine learning (ML) tec hniques and reveal that ML techniques reach a higher level of performance in for ecasting driving factors to EC adoption compared to the traditional logistic reg ression approach.”
Faculty of Economics and ManagementCyb orgsEmerging TechnologiesMachine LearningTechnology
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