scholarly journals USING SVR AND MRA METHODS FOR REAL ESTATE VALUATION IN THE SMART CITIES

2021 ◽  
Vol XLVI-4/W5-2021 ◽  
pp. 21-26
Author(s):  
A. U. Akar ◽  
S. Yalpir
Keyword(s):  
Real Estate ◽  
Smart Cities ◽  
Critical Role ◽  
Support Vector ◽  
The Real Estate ◽  
Market Values ◽  
Systems Model ◽  
Real Estate Valuation ◽  
Real Estate Management ◽  
The Impact

Abstract. Determination of real estate value plays a very critical role in economic development and basic needs of people. Increasing demand for real estate together with population growth is making it difficult to determine real estate value. In applications where real estate is the main subject, such as urban activities, smart cities and urbanization, urban information system and valuation systems, model-based value estimations are essential for effective land/real estate policy. The type of real estate and impact degree of features depending on the type should be known as well as value estimation. It will be beneficial to follow a method that both determines the real estate value and factor impact degree. With the studies to be carried out using such methods, both region-specific valuation models can be created and the model is established with the optimum variable. This paper aimed to determine real estate value by using Support Vector Regression (SVR) and Multi Regression Analysis (MRA) methods for effective real estate management. Besides, both methods were examined by revealing the impact degrees of features that affect the value. The methods were applied to 319 parcels in Konya. For each parcel, 31 land features and market values were collected. The parcel data collected since 2018 were included in the models. From the results, the RBF-SVR model reached the highest R2 value with 0.88, while the MRA model reached 0.86.

scholarly journals Added value of sites suitable for sustainable office development

2021 ◽  
Vol 13 (2) ◽  
pp. 2465-2471
Author(s):  
Josef Kupec
Keyword(s):  
Real Estate ◽  
Free Market ◽  
Market Value ◽  
Commercial Real Estate ◽  
Added Value ◽  
The Real Estate ◽  
Real Estate Valuation ◽  
Valuation Methodology ◽  
The Impact ◽  
Office Development

Abstract Valuations of real estate are widely used for various purposes and it relied always upon the financial and other markets. Valuation methodology is based on the operation of the free market economy and the real estate properties. The issue of certified properties is relatively new in the field of real estate valuation and is not sufficiently explored. Certified buildings are preferred by major corporate tenants with international field of activity who often have ethical rules for sustainable development. Therefore, certified properties are attractive to international commercial real estate investors who have higher purchasing power and are willing to pay a higher purchase price. Sustainable property certification is an element affecting the market value of the property. The purpose of this presented research is to quantify the impact of property certification on the value of office properties in Prague and subsequently to determine the impact of sustainability certificates on the market value of the land by using basic valuation techniques. The outcome of the project could be used by real estate valuation experts as a guideline to consider the future project certification and its impact on the land market value.

scholarly journals Application of AHP Method in Assessment of the Influence of Attributes on Value in the Process of Real Estate Valuation

2019 ◽  
Vol 27 (4) ◽  
pp. 15-26
Author(s):  
Krzysztof Dmytrów ◽  
Sebastian Gnat
Keyword(s):  
Real Estate ◽  
Real Estate Market ◽  
Comparative Approach ◽  
Ahp Method ◽  
The Real ◽  
The Real Estate ◽  
Real Estate Valuation ◽  
The Impact ◽  
Hierarchy Process

Abstract Property valuation in the comparative approach requires the determination of the impact of market characteristics on the formation of prices on the local real estate market. Valuers have a variety of methods for determining weights. Some of them require the collection of a sufficiently large database of information on transactions. However, this is not always possible. In the absence of sufficient data, alternative approaches, including an expert approach, may be used. The goal of the article is the proposal of an expert approach at the stage of assessing the influence of attributes on the value of the real estate. The AHP (Analytical Hierarchy Process) method will be used. On its basis, pairwise comparisons of the importance of attributes will be done by experts (valuers). By means of the AHP method, the weights of each attribute will be obtained and, subsequently, the influence of each attribute on the real estate value will be assessed. Research will be done on the basis of 318 real estates in Szczecin.

iSpace: principles for a phenomenology of space user in smart real estate

2019 ◽  
Vol 38 (4) ◽  
pp. 271-290
Author(s):  
Patrick Lecomte
Keyword(s):  
Real Estate ◽  
Smart Cities ◽  
Hedonic Pricing ◽  
Future Research ◽  
Smart Environments ◽  
Content Type ◽  
The Real Estate ◽  
Real Estate Sector ◽  
Smart Technologies ◽  
The Impact

Purpose As smart technologies become an integral part of real estate in smart cities, the purpose of this paper is to explore the impact of ubiquitous computing on space users in smart real estate. Design/methodology/approach The analysis builds on two fields of knowledge rarely referenced in real estate studies: computer sciences and social sciences. The paper starts by analysing the idiosyncrasies of a new type of space user in smart real estate, known as the Cyber-dasein in reference to Heidegger’s phenomenology. The Cyber-dasein serves as an archetypical space user in smart environments. Findings The paper introduces digital-time as a new realm of real estate, and discusses the use of “experienced utility” in hedonic pricing models of smart real estate. It concludes by advocating a multidisciplinary collaborative approach for future research on real estate in smart environments. Practical implications There is a need for the real estate sector to decide on a metric for the new digital dimension of real estate owing to the implementation of smart technologies in the built environment. Originality/value This is the first research paper on this important topic. It is totally original and new.

Comparative analysis of the real estate taxation basics in the Russian Federation and foreign countries

2018 ◽  
Vol 941 (11) ◽  
pp. 61-64
Author(s):  
A.M. Lelyuhina ◽  
М.V. Litvinenko ◽  
O.V. Miklashevskaya
Keyword(s):  
Real Estate ◽  
Russian Federation ◽  
Tax System ◽  
The Real Estate ◽  
Foreign Countries ◽  
Real Estate Valuation ◽  
Real Estate Tax ◽  
The Russian Federation ◽  
Rational Construction ◽  
The Uk

The current issues of reforming the current tax system in the Russian Federation in the context of the transition to determining the amount of real estate taxes based on the cadastral value of real estate objects are discussed. The decision on adopting elements of a tax system in practice should be scientifically and methodologically based. The rational construction of the tax system of Russia contributes to the study of foreign tax systems’ models. In the article, the systems for calculating real estate tax established in the foreign countries under consideration are highlighted. Everything is based on analyzing the practice of real estate valuation in the UK, France, Belgium, Latvia, Finland, USA and Chile. A comparison is made of the grounds for calculating the property tax, their distinctive features. The main approaches to determining the cadastral value taking place in the cadastral systems of foreign countries are summarized. The conducted studies provide grounds for identifying trends in real estate valuation, which are being introduced into modern Russian cadastral valuation practice.

scholarly journals Pricing ESG Equity Ratings and Underlying Data in Listed Real Estate Securities

2021 ◽  
Vol 13 (4) ◽  
pp. 2037 ◽  
Author(s):  
Dirk Brounen ◽  
Gianluca Marcato ◽  
Hans Op ’t Veld
Keyword(s):  
Real Estate ◽  
Best Practices ◽  
Stock Returns ◽  
The Real Estate ◽  
Public Property ◽  
European Public ◽  
Property Companies ◽  
Real Estate Securities ◽  
The Impact ◽  
European Markets

By analyzing the adoption of the European Public Real Estate Association’s (EPRA) Sustainability Best Practices Recommendations (sBPR), we examine and discuss the application of transparent environmental, social and governance (ESG) ratings and their interaction with public real estate performance across European markets. Due to increasing concerns about the environment and the impact of investment on society at large, public property companies have made significant progress in improving transparency and enhancing the protection of shareholder value by sharing and reporting ESG best practices. We explore and review the EPRA sBPR database, which is highly useful for investors who are already screening listed real estate companies. Hence, in this project, we carefully study the diffusion process of this new ESG metric as a tool to enhance informational transparency regarding public real estate investment management and assess the effects of this transparency and ESG performance for the real estate stock returns. We find evidence of a sustainability premium that investors are willing to pay to access companies with better sustainable ratings.

Sozialimmobilien

2021 ◽  
Keyword(s):  
Energy Efficiency ◽  
Life Cycle ◽  
Real Estate ◽  
Social Economy ◽  
Balance Sheets ◽  
Legal Problems ◽  
Real Estate Valuation ◽  
Political Cost ◽  
Real Estate Management ◽  
Climate Neutrality

Social real estate does not only shape the balance sheets of social economy enterprises, but also the concerns and agendas of boards, management and real estate managers. This book addresses aspects of financing, real estate management, the organisation of real estate portfolios, real estate valuation and the life cycle of buildings, plus the numerous legal problems associated with social real estate. It presents current technical concepts of energy efficiency, climate neutrality and the digital maturity of real estate in a practical manner, along with concepts for economically viable neighbourhood models and warnings against political cost drivers in the construction of social real estate. With contributions by Michael Amann, Maximilian Bergdolt, Hartmut Clausen, Oliver Errichiello, Harald Frei, Alfred Gangel, Bernd Halfar, Ingrid Hastedt, Jens Hesselbach, Mark Junge, Joel B. Münch, Markus Neubauer, Aleksandar Nikolic, George Salden, Bertram Schultze, Hubert Soyer, Hans von Gehlen, Niklas Wiesweg and Michael Winter.

scholarly journals Deep Learning Classification of Building Types in Northern Cyprus

2021 ◽  
Vol 10 (3) ◽  
Author(s):  
Mubarak Muhammad ◽  
Sertan Serte
Keyword(s):  
Deep Learning ◽  
Real Estate ◽  
Smart Cities ◽  
House Price ◽  
Training Dataset ◽  
The Real Estate ◽  
Real Estate Sector ◽  
Northern Cyprus ◽  
Second Category

Among the areas where AI studies centered on developing models that provide real-time solutions for the real estate industry are real estate price forecasting, building age, and types and design of the building (villa, apartment, floor number). Nevertheless, within the ML sector, DL is an emerging region with an Interest increases every year. As a result, a growing number of DL research are in conferences and papers, models for real estate have begun to emerge. In this study, we present a deep learning method for classification of houses in Northern Cyprus using Convolutional neural network. This work proposes the use of Convolutional neural networks in the classification of houses images. The classification will be based on the house age, house price, number of floors in the house, house type i.e. Villa and Apartment. The first category is Villa versus Apartments class; based on the training dataset of 362 images the class result shows the overall accuracy of 96.40%. The second category is split into two classes according to age of the buildings, namely 0 to 5 years Apartments 6 to 10 years Apartments. This class is to classify the building based on their age and the result shows the accuracy of 87.42%. The third category is villa with roof versus Villa without roof apartments class which also shows the overall accuracy of 87.60%. The fourth category is Villa Price from 10,000 euro to 200,000 Versus Villa Price from 200,000 Euro to above and the result shows the accuracy of 81.84%. The last category consists of three classes namely 2 floor Apartment versus 3 floor Apartment, 2 floor Apartment versus 4 floor Apartment and 2 floor Apartment versus 5 floor Apartment which all shows the accuracy of 83.54%, 82.48% and 84.77% respectively. From the experiments carried out in this thesis and the results obtained we conclude that the main aims and objectives of this thesis which is to used Deep learning in Classification and detection of houses in Northern Cyprus and to test the performance of AlexNet for houses classification was successful. This study will be very significant in creation of smart cities and digitization of real estate sector as the world embrace the used of the vast power of Artificial Intelligence, machine learning and machine vision.

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