The Research Development of Hedonic Price Model-Based Real Estate Appraisal in the Era of Big Data

Cankun Wei, Meichen Fu, Li Wang, Hanbing Yang, Feng Tang and Yuqing Xiong
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Cankun Wei: School of Land Science and Technology, China University of Geosciences (Beijing), Beijing 100083, China
Meichen Fu: School of Land Science and Technology, China University of Geosciences (Beijing), Beijing 100083, China
Li Wang: State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Hanbing Yang: School of Land Science and Technology, China University of Geosciences (Beijing), Beijing 100083, China
Feng Tang: School of Land Science and Technology, China University of Geosciences (Beijing), Beijing 100083, China
Yuqing Xiong: School of Land Science and Technology, China University of Geosciences (Beijing), Beijing 100083, China

Land, 2022, vol. 11, issue 3, 1-30

Abstract: In the era of big data, advances in relevant technologies are profoundly impacting the field of real estate appraisal. Many scholars regard the integration of big data technology as an inevitable future trend in the real estate appraisal industry. In this paper, we summarize 124 studies investigating the use of big data technology to optimize real estate appraisal through the hedonic price model (HPM). We also list a variety of big data resources and key methods widely used in the real estate appraisal field. On this basis, the development of real estate appraisal moving forward is analyzed. The results obtained in the current studies are as follows: First, the big data resources currently applied to real estate appraisal include more than a dozen big data types from three data sources; the internet, remote sensing, and the Internet of things (IoT). Additionally, it was determined that web crawler technology represents the most important data acquisition method. Second, methods such as data pre-processing, spatial modeling, Geographic information system (GIS) spatial analysis, and the evolving machine learning methods with higher valuation accuracy were successfully introduced into the HPM due to the features of real estate big data. Finally, although the application of big data has greatly expanded the amount of available data and feature dimensions, this has caused a new problem: uneven data quality. Uneven data quality can reduce the accuracy of appraisal results, and, to date, insufficient attention has been paid to this issue. Future research should pay greater attention to the data integration of multi-source big data and absorb the applications developed in other disciplines. It is also important to combine various methods to form a new united evaluation model based on taking advantage of, and avoiding shortcomings to compensate for, the mechanism defects of a single model.

Keywords: real estate appraisal; big data; hedonic price model; valuation method (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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