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Artificial neural network in property valuation: application framework and research trend

Rotimi Boluwatife Abidoye (Department of Building and Real Estate, The Hong Kong Polytechnic University, Kowloon, Hong Kong)
Albert P.C. Chan (Department of Building and Real Estate, The Hong Kong Polytechnic University, Hung Hom, Hong Kong)

Property Management

ISSN: 0263-7472

Article publication date: 16 October 2017

2329

Abstract

Purpose

The predictive accuracy and reliability of artificial intelligence models, such as the artificial neural network (ANN), has led to its application in property valuation studies. However, a large percentage of such previous studies have focused on the property markets in developed economies, and at the same time, effort has not been put into documenting its research trend in the real estate domain. The purpose of this paper is to critically review the studies that adopted ANN for property valuation in order to present an application guide for researchers and practitioners, and also establish the trend in this research area.

Design/methodology/approach

Relevant articles were retrieved from online databases and search engines and were systematically analyzed. First, the background, the construction and the strengths and weaknesses of the technique were highlighted. In addition, the trend in this research area was established in terms of the country of origin of the articles, the year of publication, the affiliations of the authors, the sample size of the data, the number of the variables used to develop the models, the training and testing ratio, the model architecture and the software used to develop the models.

Findings

The analysis of the retrieved articles shows that the first study that applied ANN in property valuation was published in 1991. Thereafter, the technique received more attention from 2000. While a quarter of the articles reviewed emanated from the USA, the rest were conducted in mostly developed countries. Most of the studies were conducted by universities scholars, while very few industry practitioners participated in the research works. Also, the predictive accuracy of the ANN technique was reported in most of the papers reviewed, but a few reported otherwise.

Research limitations/implications

The articles that are not indexed in the search engines and databases searched and also not available in the public domain might not have been captured in this study.

Practical implications

The findings of this study reveal a gap between the valuation practice in developed and developing property markets and also the contributions of real estate practitioners and universities scholars to real estate research. A paradigm shift in the valuation practice in developing nations could lead to achieving a sustainable international valuation practice.

Originality/value

This paper presents the trend in this research area that could be useful to real estate researchers and practitioners in different property markets around the world. The findings of this study could also encourage collaboration between industry professionals and researchers domiciled in both developed and developing countries.

Keywords

Acknowledgements

The authors sincerely acknowledge the Research Grants Council of Hong Kong (SAR) and the Department of Building and Real Estate, The Hong Kong Polytechnic University, Hong Kong for providing financial and material support toward this research. The authors also appreciate the constructive comments of the anonymous reviewers during the review process.

Citation

Abidoye, R.B. and Chan, A.P.C. (2017), "Artificial neural network in property valuation: application framework and research trend", Property Management, Vol. 35 No. 5, pp. 554-571. https://doi.org/10.1108/PM-06-2016-0027

Publisher

:

Emerald Publishing Limited

Copyright © 2017, Emerald Publishing Limited

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