منوچهر انصاری - Associate Professor/ University of Tehran
علی حیدری - Assistant Professor/ University of Tehran
علی ستاره گوران اباد - None

The choice of which products to stock among numerous competing products and how much space to allocate to those products are central decisions for retailers. This study aimed to apply data mining approach so that, we got needed information from large datasets of sale transactions to find the relations between products and to make product assortments. Thus, we represented a model for product assortment and space allocation. Research population was transactional data of a store, the sample included transactional data of one-month period in the time series. Data were collected in October and November, ۲۰۱۵ from Shaghayegh store. ۵۲۵ transactions with regard to ۷۹ different products were analyzed. Based on the result ۱۰ product assortments formed although some products were allocated to more than ۱ product category. By solving profit equation and finding volume increase indices we allocated spaces for each product assortment.

Data Mining, maximizing profit, product assortment, shelf space allocation