Representing a Model Using Data Mining Approach for Maximizing Profit with Considering Product Assortment and Space Allocation Decisions

• Main Authors: Manoochehr Ansari, Ali Heidari, Ali Setareh Gooran Abad
• Format: Article
• Language: fas
• Published: University of Tehran 2016-12-01
• Series: Journal of Information Technology Management
• Subjects: Data Mining; maximizing profit; product assortment; shelf space allocation
• Online Access: https://jitm.ut.ac.ir/article_59945_f15dbec16ef2f3c61b6b06ce12042170.pdf

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, 2015 from Shaghayegh store. 525 transactions with regard to 79 different products were analyzed. Based on the result 10 product assortments formed although some products were allocated to more than 1 product category. By solving profit equation and finding volume increase indices we allocated spaces for each product assortment.