Geo-information modeling of retail areas using databases and a program-analytical approach
Abstract
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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Pomortseva, O., Kozyrenko, S., Pankiv, V. (2025). Tsyfrovyzatsiia u heomarketyngu: vykorystannia prohramuvannia ta baz danykh. [Digitalization in geomarketing: use of programming and databases]. Problemy suchasnykh transformatsii. Seriia: Ekonomika ta upravlinnia, 18. ( in Ukrainian).
Pomortseva, O., Kobzan, S., Kin, D., Pankiv, V. (2024). Some aspects of modelling a real estate decision-making expert system based on GIS. In International Conference of Young Professionals. GeoTerrace-2024. 1, pp. 1–5. European Association of Geoscientists & Engineers. Available at: https://doi.org/10.3997/2214-4609.2024510031
Kobzan S., Pomortseva O. (2023). Real Estate Market of Ukraine. Practical Aspects and Trends. SpringerBriefs in Geography 146 р. Available at: https://doi.org/10.1007/978-3-031-31248-9_1.
Takenova, K., & Guleva, V. Y. (2023). Determination of optimal locations for ATM network service points. Procedia Computer Science, 229, 198–207. Available at: https://doi.org/10.1016/j.procs.2023.12.021
Formánek, T., & Sokol, O. (2022). Location effects: Geo-spatial and socio-demographic determinants of sales dynamics in brick-and-mortar retail stores. Journal of Retailing and Consumer Services, 66, Article 102902. Available at: https://doi.org/10.1016/j.jretconser.2021.102902
Zhou, J., Yang, C., Liu, D., Wang, Y., Zhong, Z., & Wu, Y. (2025). A three-stage geospatial network optimal location decision model for urban green logistics centers from a sustainable perspective. Sustainable Cities and Society, 128, Article 106481. Available at: https://doi.org/10.1016/j.scs.2025.106481
Pomortseva, O. (2016). Design of geodatabases: Basic guide. Kharkiv National University of Urban Economy named A. N. Beketov. 140 p.
Chacón-García, J. (2017). Geomarketing techniques to locate retail companies in regulated markets. Australasian Marketing Journal (AMJ). 25(3), рр. 185–193. . Available at: https://doi.org/10.1016/j.ausmj.2017.06.001
Feizizadeh, B., Omarzadeh, D., Blaschke, T. (2024). Spatiotemporal mapping of urban trade and shopping patterns: A geospatial big data approach. International Journal of Applied Earth Observation and Geoinformation. 128, Article 103764. . Available at: https://doi.org/10.1016/j.jag.2024.103764
Azri, S., Ujang, U., Abdul Rahman, A. (2020). Voronoi classified and clustered data constellation: A new 3D data structure for geomarketing strategies. ISPRS Journal of Photogrammetry and Remote Sensing. 162, рр. 1–16. Available at: https://doi.org/10.1016/j.isprsjprs.2020.01.022
Verhetsel, A. (2005). Effects of neighbourhood characteristics on store performance: Supermarkets versus hypermarkets. Journal of Retailing and Consumer Services. 12 (2), рр. 141–150. Available at: https://doi.org/10.1016/j.jretconser.2004.11.004
Kobzan, S. M., Pomortseva, O. Y., Pankiv, V. V. (2024). Heoinformatsiinyi analiz vplyvu remontno-budivelnykh robit na investytsiinu pryvablyvist nerukhomosti [Geoinformation analysis of the impact of repair and construction work on the investment attractiveness of real estate]. Visnyk Kharkivskoho natsionalnoho universytetu imeni V. N. Karazina. Seriia: Mizhnarodni vidnosyny. Ekonomika. Krainoznavstvo. Turyzm. 20, рр. 32–40. Available at: https://doi.org/10.26565/2310-9513-2024-20-04 ( in Ukrainian).
OpenStreetMap. Available at: https://www.openstreetmap.org/#map=13/49.9 (accessed: 10.07.2025)
Overpass turbo. Available at: https://wiki.openstreetmap.org (accessed: 10.07.2025)
Поморцева О. Є., Козиренко С. І., Паньків В. В. Цифровізація у геомаркетингу: використання програмування та баз даних. Проблеми сучасних трансформацій. Серія: Економіка та управління. 2025. № 18.
Pomortseva O., Kobzan S., Kin D., Pankiv V. Some aspects of modelling a real estate decision-making expert system based on GIS. International Conference of Young Professionals. GeoTerrace-2024. 2024. № 1. с. 1–5. https://doi.org/10.3997/2214-4609.2024510031.
Kobzan S., Pomortseva O. Real Estate Market of Ukraine. Practical Aspects and Trends. SpringerBriefs in Geography, 2023. 146 р. https://doi.org/10.1007/978-3-031-31248-9_1.
Takenova K., Guleva V. Y. Determination of optimal locations for ATM network service points. Procedia Computer Science. 2023. 229. 198–207. https://doi.org/10.1016/j.procs.2023.12.021.
Formánek T., Sokol O. Location effects: Geo-spatial and socio-demographic determinants of sales dynamics in brick-and-mortar retail stores. Journal of Retailing and Consumer Services. 2022. 66. https://doi.org/10.1016/j.jretconser.2021.102902.
Zhou J., Yang C., Liu D., Wang Y., Zhong Z., Wu Y. A three-stage geospatial network optimal location decision model for urban green logistics centers from a sustainable perspective. Sustainable Cities and Society. 2025. 128. https://doi.org/10.1016/j.scs.2025.106481.
Поморцева Е. Е. Проектирование баз геоданных: учеб. пособие. Харьков. нац. ун-т гор. хоз-ва им. А. Н. Бекетова. 2016. 140 с.
Chacón-García J. Geomarketing techniques to locate retail companies in regulated markets. Australasian Marketing Journal (AMJ). 2017. 25 (3). 185–193. https://doi.org/10.1016/j.ausmj.2017.06.001.
Feizizadeh B., Omarzadeh D., Blaschke T. Spatiotemporal mapping of urban trade and shopping patterns: A geospatial big data approach. International Journal of Applied Earth Observation and Geoinformation. 2024. 128. https://doi.org/10.1016/j.jag.2024.103764.
Azri S., Ujang U., Abdul Rahman A. Voronoi classified and clustered data constellation: A new 3D data structure for geomarketing strategies. ISPRS Journal of Photogrammetry and Remote Sensing. 2020. 162. 1–16. https://doi.org/10.1016/j.isprsjprs.2020.01.022.
Verhetsel A. Effects of neighbourhood characteristics on store performance: Supermarkets versus hypermarkets. Journal of Retailing and Consumer Services. 2005. 12 (2). 141–150. https://doi.org/10.1016/j.jretconser.2004.11.004.
Кобзан С. М., Поморцева О. Є., Паньків В. В. Геоінформаційний аналіз впливу ремонтно-будівельних робіт на інвестиційну привабливість нерухомості. Вісник Харківського національного університету імені В. Н. Каразіна. Серія: Міжнародні відносини. Економіка. Країнознавство. Туризм. 2024. 20. с. 32–40. https://doi.org/10.26565/2310-9513-2024-20-04.
«OpenStreetMap»: web site. URL: https://www.openstreetmap.org/#map=13/49.9 (дата звернення: 10.07.2025).
«Overpass turbo»: web site. URL: https://wiki.openstreetmap.org (дата звернення: 10.07.2025).
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