A Systematic Review of Hybrid Models in Market Basket Analysis: Methods, Trends, and Future Research Directions

A Systematic Review of Hybrid Models in Market Basket Analysis: Methods, Trends, and Future Research Directions | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review A Systematic Review of Hybrid Models in Market Basket Analysis: Methods, Trends, and Future Research Directions Uduak Umoh, Imo Eyoh, Nkeseabasi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9650079/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Understanding consumer behaviour is crucial in today’s competitive market. Market Basket Analysis (MBA) is a key technique in data mining that reveals consumer purchasing patterns. This systematic review follows PRISMA 2020 guidelines to conduct article search across ACM, IEEE Xplore, Springer Link, and Google Scholar from January 2010 to June 2024 publications. Articles focusing on intelligent hybrid models in MBA were selected based on defined inclusion and exclusion criteria. It explores the evolution of Market Basket Analysis (MBA) methodologies, focusing on traditional techniques such as Apriori and FP-Growth, alongside advanced methods including Recurrent Neural Networks (RNN) and Genetic Algorithms (GA). Out of 250 articles identified, 134 were excluded during screening, and 70 studies were included in the review. Key findings include the importance of data preprocessing techniques and evaluation metrics in improving MBA performance. The review identifies trends such as the integration of real-time data processing, explainable AI, and cross-domain applications. Additionally, emerging research directions in handling sparse data, ethical analysis, and cross-domain applications are discussed. This review provides a comprehensive foundation for optimizing business decision-making and customer satisfaction through more effective consumer product purchasing pattern discovery in dynamic market environments. These trends are poised to transform MBA, enhancing its precision and business utility. FP-Growth Hybrid Models Market Basket Analysis PRISMA Systematic Review Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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