A predictive methodology of rough set theory used to analyse market segmentation and competitive environment for super market

Abstract

Supermarket retailing has a desirable property of stability of segment structure. Due to the heterogeneous needs and purchase power of customers, it is difficult to predict the lifetime of segments for retail supermarkets. In today's competitive marketplace, segment identification needs a thorough study and analysis of the market. This paper proposes a Rough Set Theory (RST)-based method to define change in the customer segment based on the hybrid segmentation variables. Different customer segments of the retail market are classified into two distinct regions which may or may not change the retailer store based on some segmentation variables. Furthermore, for the boundary value segments, fuzzy logic modeling method was used to show their membership with defined regions of the segments.