A Quantitative Spatial Exploratory Analysis on Fast Consumer Goods, Shopping Trips, and Discount Supermarket Revenues: The Case of Istanbul

In response to changing consumer behaviors, innovative retail chains have begun offering consumers higher value and a higher quality experience than competitors. For successful diffusion in a country, innovators must establish a competitive position by creating better value for consumers offering a more appropriate product and quality of service compared to competitors. Consumers adapt the structure, cost, and frequency of their shopping baskets and visits to the changing spatial conditions, cultural norms, and time costs in order to maintain their living standards. A better understanding of the temporal behavioral changes of spatially segregated consumer groups opens the way for econometric studies that can inform what strategic decisions will help the successful development and diffusion of innovative store formats. Spatial data exist in abundance, and examining new retail potentials and analyzing current performance have become easier. However, the literature has thoroughly criticized the insufficiency of existing business intelligence applications regarding their theoretical foundations and empirical findings, as well as their ignorance of the exceptional conditions of emerging market economies. Another limitation concerns data confidentiality. This article demonstrates how open-source secondary and primary data collected through surveys are helpful in generating new spatial and non-spatial variables for further use in econometric and statistical studies. Within this scope, the study analyzes the annual change in demand for fast-moving consumer goods in terms of middle- and lower-income groups originating from residential areas in Istanbul within shopping basins using geographic information systems. The study then identifies the changes in the number of planned and unplanned shopping visits and the local potential for discount markets. These comparisons using officially announced data reveal the method to be successful. The study’s findings have the potential to guide statistical and econometric business intelligence applications in developing innovative retail formats in Türkiye and similar countries.