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Development of a Geodemographic System for Attica, Greece

Thomas Hatzichristos | Athanasia Darra | Anastasia Kostellou Downloads: 108

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Published: 2022/10/06 DOI:

Open Access

Keywords: Geodemographics, GIS, AI, Fuzzy clustering, Fuzzy C-Means


Recent years have witnessed fundamental changes in the financial and retail service sector, with competition among companies intensifying as a result of changing markets. The need to address the specific requirements of the customer groups has become the guiding principle behind the business strategies adopted by companies. These customer needs and, subsequently, the provision of the appropriate products and services to the customer, are dependent on where they live, their personal characteristics (e.g., age, education, income, households etc.). Geodemographic systems take advantage of information technology to analyze these types of data for a better understanding of the consumer characteristics and improved performing of marketing strategies. In the present study, a geodemographic system is implemented utilizing geographic information systems (GIS) technology and artificial intelligence (AI). GIS technology offers a powerful set of tools for the input, management, and visualization of data, while AI provides advanced analytical tools such as the unsupervised fuzzy classification through the Fuzzy C-Means algorithm. The proposed methodology is applied to the Attica region in Greece. It uses the official socioeconomic data of the Hellenic Statistical Authority. The relevant database uses 78 socio-economic variables. The study area consists of 2500 area units, each one with more than 1000 inhabitants. The results, ten socio-economic classes, are analyzed and discussed. The project is funded by the Athens Chamber of Commerce and Industry (ACCI) and the results of the analysis are open to all users by the official site of ACCI.

- State of the art multivariable geographical analysis for enterprises

- Implementation of AI and Fuzzy C means to analyze and understanding the underlying consumer characteristics

- Methodological framework for improved performing of marketing strategies for enterprises

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