Finding Hidden Location Patterns of Two Competitive Supermarkets in Thailand

Abstract

There are two famous supermarkets in Thailand: Big C and Lotus. They are the highest competitive supermarkets whose hold the most market share by lots of promotions and also gather all convenience services including banking, restaurant, and others. In recent years, they gradually expand their stores and they take a similar strategy to determine where to locate a store. It is important for them to consider store allocation to obtain new customers efficiently. To consider this, we gather geographical locations of these supermarkets from Twitter using Twitter API. We gathered tweets having these supermarket names and geotags for seven months. To extract hidden location patterns from gathered data, we introduce location motif which is a directed subgraph whose edges are linked to every pair of the shortest-distance opponent node. We investigate every possible configuration of location motif when they have a small number of nodes and find that the configuration increases exponentially. We also visualize location motifs generated from gathered data on the map of Thailand and count the frequency of observed location motifs. As a result, we find that even if the possible location motifs exponentially increase as the number of nodes grows, limited location motifs can be observed. Using location motif, we successfully find an evidence of biased store allocation in reality.