Geo-information modeling of retail areas using databases and a program-analytical approach
DOI:
https://doi.org/10.26565/2310-9513-2025-22-13Keywords:
Geographic Information System (GIS), database, routing, chain store, geomarketing, service areaAbstract
This article explores the important issue of finding the best location for a retail store. The study focuses on using geographic information system (GIS) modeling to choose a location for an «Epicentr» chain store in Kharkiv, Ukraine, by applying two-dimensional geospatial models. The aim of the article is to find the most suitable place for a chain store using GIS tools. Since this task requires analyzing many different factors, it cannot be done without a database, GIS software, and programming tools to create custom queries and get accurate location-based data. The main goal is to analyze the service areas – also known as «trade zones» – of existing and destroyed «Epicentr» stores in Kharkiv. The study identifies so-called «white spots», or areas where people have limited access to these stores. General scientific methods of system analysis and geostatistics were used to convert data from a discrete to a continuous form during processing. A combination of geographic and probability models was applied using the Huff model. This helped measure the distance that customers need to travel to reach the shopping area. The study focused on how far potential customers would be willing to go, assuming that for a large chain store, close distance alone is not enough to attract buyers. The research analyzed medium and long-range trade zones, considering the urban layout of Kharkiv. As a result, the optimal location for a new store was identified to replace two that had been destroyed. The study also evaluated the methods used – such as transport accessibility analysis and isochrone mapping (areas reachable within a set time or distance). Both methods gave nearly the same results. The results can help business owners make better decisions when opening new stores. This can reduce risks and support the sustainable and balanced development of the city.
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