A bibliometric analysis of property valuation research

Author:

Binoy B .V,Naseer M. A,Anil Kumar P.P,Lazar Nina

Abstract

Purpose Real estate valuation studies gained popularity with the availability of large-scale property transaction data in the latter part of the twentieth century. Hedonic price modeling (HPM) was the most popular method in the initial years until it was taken over by advanced modeling methods in the twenty-first century. Even though there exist a few literature reviews on this topic, no comprehensive bibliometric analysis is conducted in this area. In view of gaining a better understanding of the dynamics of property valuation studies, this paper aims to conduct a bibliometric analysis. Design/methodology/approach A comprehensive search in the Scopus database, followed by detailed screening resulted in 1,400 articles. The identified research articles spanning over five decades (1964–2019) are analyzed using the open-source R package “bibliometrix.” Findings The study found the USA to be the most productive country in various aspects, such as number of publications, number of authors and publication hotspots. The findings also demonstrate assessments on the publication trends, journals, citations, keywords, co-citation and collaboration networks. It was observed that there exists an upsurge in the number of publications after the year 2000 owing to improved data availability and better modeling techniques. Research limitations/implications This study is significant in understanding the major research areas and modeling techniques used in property valuation. Future studies can incorporate multiple database sources and include more articles. Originality/value The current study is one of the first bibliometric studies on property valuation. Previous studies have not explored the possibilities of geographic information system in bibliometric research. Spatial mapping and analysis of publications provide a geographical perspective of valuation research.

Publisher

Emerald

Subject

General Economics, Econometrics and Finance

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