Review of Clustering Methods Used in Data-Driven Housing Market Segmentation

Skovajsa Štěpán ()
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Skovajsa Štěpán: Institute of Forensic Engineering, Brno University of Technology, Purkyňova 464/118, 612 00 Brno, Czech Republic

Real Estate Management and Valuation, 2023, vol. 31, issue 3, 67-74

Abstract: A huge effort has already been made to prove the existence of housing market segments, as well as how to utilize them to improve valuation accuracy and gain knowledge about the inner structure of the entire superior housing market. Accordingly, many different methods on the topic have been explored, but no universal framework is yet known. The aim of this article is to review some previous studies on data-driven housing market segmentation methods with a focus on clustering methods and their ability to capture market segments with respect to the shape of clusters, fuzziness and hierarchical structure.

Keywords: clustering algorithms; housing market analysis; housing market segmentation; data-driven segmentation (search for similar items in EconPapers)
JEL-codes: R31 (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:remava:v:31:y:2023:i:3:p:67-74:n:3

DOI: 10.2478/remav-2023-0022

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