As part of the customer relationship management (CRM) strategy, many researchers have been analyzing ‘why’ customers decide to switch. However, despite its practical relevance, few studies have investigated how companies can react to defection prone customers by offering the right set of products. Consumer insight has been captured in the work, but not used for inventory replenishment. In the present research paper, a data mining model has been proposed which can be used for multi-item inventory management in retail sale stores. The model has been illustrated with an example database.
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Bala, P.K. (2009). Data Mining for Retail Inventory Management. In: Ao, SI., Gelman, L. (eds) Advances in Electrical Engineering and Computational Science. Lecture Notes in Electrical Engineering, vol 39. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-2311-7_50
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DOI: https://doi.org/10.1007/978-90-481-2311-7_50
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