Abstract

The paper addresses the problem of predicting the attractiveness of the commercial real estate market based on market valuation. The aim is to estimate market value, and models of the commercial real estate market need to be established. The complexity of the problem lies in accounting for market changes resulting from the COVID-19 pandemic and, more broadly, its variability in response to geopolitical shifts, which are reflected in the available data. To address this, a machine learning-based framework is proposed. The proposed models for solving the problem have been validated using data from recent years. Finally, a summary is provided.

Recommended Citation

Czarnowski, I. (2025). Estimating the value of commercial real estate using machine learning approachesIn I. Luković, S. Bjeladinović, B. Delibašić, D. Barać, N. Iivari, E. Insfran, M. Lang, H. Linger, & C. Schneider (Eds.), Empowering the Interdisciplinary Role of ISD in Addressing Contemporary Issues in Digital Transformation: How Data Science and Generative AI Contributes to ISD (ISD2025 Proceedings). Belgrade, Serbia: University of Gdańsk, Department of Business Informatics & University of Belgrade, Faculty of Organizational Sciences. ISBN: 978-83-972632-1-5. https://doi.org/10.62036/ISD.2025.47

Paper Type

Poster

DOI

10.62036/ISD.2025.47

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Estimating the value of commercial real estate using machine learning approaches

The paper addresses the problem of predicting the attractiveness of the commercial real estate market based on market valuation. The aim is to estimate market value, and models of the commercial real estate market need to be established. The complexity of the problem lies in accounting for market changes resulting from the COVID-19 pandemic and, more broadly, its variability in response to geopolitical shifts, which are reflected in the available data. To address this, a machine learning-based framework is proposed. The proposed models for solving the problem have been validated using data from recent years. Finally, a summary is provided.