Complexity

Computational Methods Applied to Data Analysis for Modeling Complex Real Estate Systems


Publishing date
01 May 2020
Status
Published
Submission deadline
03 Jan 2020

Lead Editor

1Sapienza University of Rome, Rome, Italy

2Polytechnic University of Bari, Bari, Italy


Computational Methods Applied to Data Analysis for Modeling Complex Real Estate Systems

Description

Over the last few decades, as a result of the serious economic and financial crisis that has affected the USA and most European countries there has been an increasing need for tools that provide reliable mass appraisals. The crisis was triggered by the drastic price reduction of properties as securities for credit exposures, characterized by values that, at the time of the sale due to the debtor’s default, had revealed a real market price that made it impossible for the banks to recover the capital borrowed. This was both down to the failure to update the property market values over time when compared to the actual trend of prices and from the inadequacy of the methodologies used to determine the market values which were mostly identified through approaches which required a long processing time and lead to results affected by significant approximations.

This contingence has outlined the global connections of the real estate markets and has highlighted on the one hand the complex relationship between the real economy and property finance and on the other hand the need for multidisciplinary models that are able to appropriately interpret the available data, identify space-time interactions, and forecast real estate cycles. The complexity of real estate systems concerns the numerous social, economic, and environmental implications that are related to property valuations and regional economic growth, as well as the reciprocal interdependencies between the territorial transformations and their socioeconomic factors.

These complex systems, comprised of inherent dynamical structures that evolve over time by means of interactions between their components, are unpredictable and multidimensional. In this context, automated valuation methods, which are machine learning tools applied to the mass appraisals for nonperforming and unlikely to pay loans, as well as the periodic value updates of the real estate investment trusts, can allow for us to effectively analyze market phenomena and predict their temporal evolution.

The aim of this special issue is to collate both original research and review articles that contribute to the development of new tools for modeling, optimizing, and simulating complex real estate systems and are related to the applications of data analysis models that take into account the continuous changes of the economic boundary conditions and are able to automatically capture the causal relationships among the variables involved as well as predict property values in the short term.

Potential topics include but are not limited to the following:

  • Mass appraisal methods applied to the interpretation of the real estate markets
  • Multicriteria decision systems as support for valuations in uncertain contexts
  • Big data analysis for modeling and control approaches
  • Econometric analysis for the forecasting of real estate trends
  • GIS-based systems for the identification of spatial correlations among real estate factors
  • Artificial intelligence implemented for the automated valuation model
  • Genetic algorithms for the investigation of complex real estate systems

Articles

  • Special Issue
  • - Volume 2020
  • - Article ID 8519060
  • - Editorial

Computational Methods Applied to Data Analysis for Modeling Complex Real Estate Systems

Marco Locurcio | Francesco Tajani | Pierluigi Morano
  • Special Issue
  • - Volume 2020
  • - Article ID 8752865
  • - Research Article

Real Estate Asset Management Companies’ Economies of Scale: Is It a Dream or Reality? The Italian Case

Evita Allodi | Claudio Cacciamani | ... | Simona Sanfelici
  • Special Issue
  • - Volume 2020
  • - Article ID 1079024
  • - Research Article

GIS-Based Spatial Autocorrelation Analysis of Housing Prices Oriented towards a View of Spatiotemporal Homogeneity and Nonstationarity: A Case Study of Guangzhou, China

Shaopei Chen | Dachang Zhuang | Huixia Zhang
  • Special Issue
  • - Volume 2020
  • - Article ID 5287263
  • - Research Article

A Fully Automated Adjustment of Ensemble Methods in Machine Learning for Modeling Complex Real Estate Systems

José-Luis Alfaro-Navarro | Emilio L. Cano | ... | Beatriz Larraz
  • Special Issue
  • - Volume 2020
  • - Article ID 4603190
  • - Research Article

Predicting Days on Market to Optimize Real Estate Sales Strategy

Mauro Castelli | Maria Dobreva | ... | Leonardo Vanneschi
  • Special Issue
  • - Volume 2020
  • - Article ID 2791352
  • - Research Article

Efficiency of Chinese Real Estate Market Based on Complexity-Entropy Binary Causal Plane Method

Yan Chen | Ya Cai | Chengli Zheng
  • Special Issue
  • - Volume 2019
  • - Article ID 8710138
  • - Research Article

Grey Spectrum Analysis of Air Quality Index and Housing Price in Handan

Kai Zhang | Yan Chen | Lifeng Wu
  • Special Issue
  • - Volume 2019
  • - Article ID 4053970
  • - Research Article

Developing Statistical Optimization Models for Urban Competitiveness Index: Under the Boundaries of Econophysics Approach

Cem Çağrı Dönmez | Abdulkadir Atalan
Complexity
Publishing Collaboration
More info
Wiley Hindawi logo
 Journal metrics
Acceptance rate43%
Submission to final decision64 days
Acceptance to publication35 days
CiteScore3.200
Impact Factor2.462
 Submit