Identifying the Current Status of Real Estate Appraisal Methods

Numan Jamal A. A. () and Yusoff Izham Mohamad ()
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Numan Jamal A. A.: Universiti Sains Malaysia (USM), Main Campus, Penang, Malaysia
Yusoff Izham Mohamad: Universiti Sains Malaysia (USM), Main Campus, Penang, Malaysia

Real Estate Management and Valuation, 2024, vol. 32, issue 4, 12-27

Abstract: Real estate appraisal, also known as property valuation, plays a crucial role in numerous economic activities and financial decisions, such as taxation assessment, bank lending, and insurance, among others. However, the current methods used in real estate appraisal face several challenges related to fundamental aspects such as accuracy, interpretation, data availability, and evaluation metrics. Therefore, the purpose of this research is to identify the current status of real estate appraisal methods, highlighting challenges and providing guidance for scholars to undertake further research in addressing them. The methodology retrieves the most recent papers published in the Scopus database over the past five years, covering the period from 2019 to the end of 2023, with an emphasis on empirical studies. These retrieved papers serve as references to capture the current status of real estate appraisal methods. The research findings confirm a clear trend towards increased utilization of artificial intelligence techniques, especially machine learning, but with unfinished work regarding related challenges. Artificial intelligence techniques enhance the accuracy of real estate appraisal, paving the way for improved decision support systems in business, financial, and economic sectors.

Keywords: real estate appraisal; property valuation; machine learning; accuracy; interpretability; data availability; evaluation metrics; automatic valuation methods; and mass valuation housing; experiment; Poland (search for similar items in EconPapers)
JEL-codes: Y90 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:remava:v:32:y:2024:i:4:p:12-27:n:1002

DOI: 10.2478/remav-2024-0032

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