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

Rotimi Boluwatife Abidoye, Ping Chuen Chan

Research output: Journal article publicationReview articleAcademic researchpeer-review

16 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)554-571
Number of pages18
JournalProperty Management
Volume35
Issue number5
DOIs
Publication statusPublished - 1 Jan 2017

Keywords

  • Artificial neural network
  • Developed countries
  • Developing countries
  • Property market
  • Property valuation
  • Review

ASJC Scopus subject areas

  • Tourism, Leisure and Hospitality Management

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