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Fátima Trindade Neves, Manuela Aparicio and Miguel de Castro Neto
In the rapidly evolving landscape of urban development, where smart cities increasingly rely on artificial intelligence (AI) solutions to address complex challenges, using AI to accurately predict real estate prices becomes a multifaceted and crucial tas...
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Margot Geerts, Seppe vanden Broucke and Jochen De Weerdt
Predicting house prices is a challenging task that many researchers have attempted to address. As accurate house prices allow better informing parties in the real estate market, improving housing policies and real estate appraisal, a comprehensive overvi...
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Yue Ying, Mila Koeva, Monika Kuffer and Jaap Zevenbergen
Increasing urbanisation has inevitably led to the continuous construction of buildings. Urban expansion and densification processes reshape cities and, in particular, the third dimension (3D), thus calling for a technical shift from 2D to 3D for property...
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José-Francisco Vergara-Perucich
This article presents the results of a bibliometric review of the study of real estate bubbles in the scientific literature indexed in Web of Science and Scopus, from 2007 to 2022. The analysis was developed using a sample of 2276 documents, which were r...
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Phuong Lan Le, Anh Tuan Do and Anh Ngoc Pham
This study focused on testing the existence of an apartment price bubble in Hanoi (Vietnam) and on determining the factors that affected it in the period between 2010 and 2021. Using the fundamental factor approach, the authors applied VAR regression usi...
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Peiheng Yu, Esther H. K. Yung, Edwin H. W. Chan, Shujin Zhang, Siqiang Wang and Yiyun Chen
Understanding how public service accessibility is related to housing prices is crucial to housing equity, yet the heterogeneous capitalisation effect remains unknown. This study aims to investigate the spatial effect of public service accessibility on ho...
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Maryam Mubarak, Ali Tahir, Fizza Waqar, Ibraheem Haneef, Gavin McArdle, Michela Bertolotto and Muhammad Tariq Saeed
The accessibility of spatial big data help real estate investors to make better judgement calls and earn additional profit. Since location is considered necessary for real estate and consequent decision-making, digital maps have become a prime resource f...
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Evert Guliker, Erwin Folmer and Marten van Sinderen
With the rapidly increasing house prices in the Netherlands, there is a growing need for more localised value predictions for mortgage collaterals within the financial sector. Many existing studies focus on modelling house prices for an individual city; ...
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Hugo Castro Noblejas, Jesús Vías Martínez and Matías F. Mérida Rodríguez
The landscape is a factor considered when choosing to purchase a dwelling, and, therefore, it influences the price of the real estate market. However, it is difficult to measure and assess its role, since it has a series of features that work in an integ...
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Zimo Wang, Yicheng Wang, Sensen Wu and Zhenhong Du
Confronted with the spatial heterogeneity of the real estate market, some traditional research has utilized geographically weighted regression (GWR) to estimate house prices. However, its predictive power still has some room to improve, and its kernel fu...
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