Determination of Drivers of Stock-Out Performance of Retail Stores using Data Mining Techniques
Research Fest 2008
This project utilizes data mining techniques to determine the drivers of stock-out performance. Best performing and worst performing clusters of stores were identified using data clustering techniques. Furthermore, Logistic regression and multiple ordinary-least-squares regression were used to gain further insights and quantify the drivers of stock-outs.
22-May-08, Session 1 (8:30-9:30)
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