Journal of Property Research
Published by Taylor & Francis
ISSN : 0959-9916 eISSN : 1466-4453
Abbreviation : J. Prop. Res.
Aims & Scope
Journal of Property Research is an international journal of research, particularly applied research, into property investment and development.
Journal of Property Research welcomes original papers on any area of real estate investment and development.
These may be theoretical, empirical, case studies or critical literature surveys.
There are two major areas of focus: 1.Property investment and finance.
This covers topics such as the characteristics of property as an investment class, forecasting of markets and property portfolio construction.
Much of this research will be an application to property of techniques developed in other investment markets. 2.Land development.
This covers a wide range of issues surrounding the development and redevelopment of property.
The focus may be financial, economic or environmental; urban or rural; public or private sector.
View Aims & ScopeMetrics & Ranking
Impact Factor
Year | Value |
---|---|
2025 | 2.3 |
2024 | 2.10 |
Journal Rank
Year | Value |
---|---|
2024 | 10294 |
Journal Citation Indicator
Year | Value |
---|---|
2024 | 236 |
SJR (SCImago Journal Rank)
Year | Value |
---|---|
2024 | 0.565 |
Quartile
Year | Value |
---|---|
2024 | Q2 |
h-index
Year | Value |
---|---|
2024 | 40 |
Impact Factor Trend
Abstracting & Indexing
Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.
Subjects & Keywords
Journal’s research areas, covering key disciplines and specialized sub-topics in Social Sciences, designed to support cutting-edge academic discovery.
Most Cited Articles
The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.
-
Hedonic modelling, housing submarkets and residential valuation
Citation: 207
Authors: A. S., J. N., W. S.
-
Predicting property prices with machine learning algorithms
Citation: 205
Authors: Winky K.O., Bo-Sin, Siu Wai
-
Prediction accuracy in mass appraisal: a comparison of modern approaches
Citation: 135
Authors: W.J., M., P.T., M., D.
-
Metrics for evaluating the performance of machine learning based automated valuation models
Citation: 107
Authors: Miriam, Robert J., Norbert
-
Re use potential and vacant industrial premises: revisiting the regeneration issue in Stoke-on-Trent
Citation: 86
Authors: R.M.
-
House price diffusion and interâ€regional and crossâ€border house price dynamics
Citation: 85
Authors: Simon