Modelling and Simulation of Selected Real Estate Market Spatial Phenomena

Kobylińska, Katarzyna; Cellmer, Radosław

doi:10.3390/ijgi8100446

Cited by 7 publications

(3 citation statements)

References 37 publications

(35 reference statements)

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“…One of the key problems in real estate market analyses is the identification of real estate characteristics (their occurrence, extent, and relevance) affecting the reasoning [13][14][15][16][17]. The accurate identification of problems and limitations in the area of real estate information analyses determines the direction of the search for solutions that better reflect market reality.…”

Section: The Problem Of Real Estate Feature Significance Assessmentmentioning

confidence: 99%

Real Estate Industry Sustainable Solution (Environmental, Social, and Governance) Significance Assessment—AI-Powered Algorithm Implementation

Walacik,

Chmielewska

2024

Sustainability

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As the global imperative for sustainable development intensifies, the real estate industry stands at the intersection of environmental responsibility and economic viability. This paper presents a comprehensive exploration of the significance of sustainable solutions within the real estate sector, employing advanced artificial intelligence (AI) algorithms to assess their impact. This study focuses on the integration of AI-powered tools in a decision-making process analysis. The research methodology involves the development and implementation of AI algorithms capable of analyzing vast datasets related to real estate attributes. By leveraging machine learning techniques, the algorithm assesses the significance of energy efficiency solutions along with other intrinsic and extrinsic attributes. This paper examines the effectiveness of these solutions in relation to the influence on property prices with a framework based on an AI-driven algorithm. The findings aim to inform real estate professionals and investors about the tangible advantages of integrating AI technologies into sustainable solutions, promoting a more informed and responsible approach to industry practices. This research contributes to the growing interest in the connection of the real estate sector, sustainability, and AI, offering insights that can guide strategic decision making. By implementing the random forest method in the real estate feature significance assessment original methodology, it has been shown that AI-powered algorithms can be a useful tool from the perspective of real estate price prediction. The methodology’s ability to handle non-linear relationships and provide insights into feature importance proved advantageous in comparison to the multiple regression analysis.

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Section: The Problem Of Real Estate Feature Significance Assessmentmentioning

confidence: 99%

Real Estate Industry Sustainable Solution (Environmental, Social, and Governance) Significance Assessment—AI-Powered Algorithm Implementation

Walacik,

Chmielewska

2024

Sustainability

View full text Add to dashboard Cite

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“…One of most important stages, regardless of the type of valuation, is the collection and provision of reliable information that is related to the elaboration of the dataset. The definition of the data that influence the establishment of the prices is one of most crucial aspects of the property valuation procedure and market analyses (Guo et al, 2012;Hwang et al, 2013;Kauškale & Geipele, 2017;Kobylińska & Cellmer, 2019;Wei-Xing & Sornette, 2008). However, the type and scope of the attributes that determine property values are not universal and may differ from one valuation to another.…”

Section: Literature Reviewmentioning

confidence: 99%

Human emotion recognition in the significance assessment of property attributes

Renigier‐Biłozor

Janowski

Walacik

et al. 2021

J Hous and the Built Environ

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One of the largest problems in the real estate market analysis, which includes valuation, is determining the significance of individual property attributes that may affect value or attractiveness perception. The study attempts to assess the significance of selected attributes of real estate based on the detection and analysis of the emotions of potential investors. Human facial expression is a carrier of information that can be recorded and interpreted effectively via the use of artificial intelligence methods, machine learning and computer vision. The development of a reliable algorithm requires, in this case, the identification and investigation of factors that may affect the final solution of the problem, from behavioural aspects through technological possibilities. In the presented experiment, an approach that correlates the emotional states of buyers with the visualization of selected attributes of properties is utilized. The objective of this study is to develop an original method for assessing the significance of property attributes based on emotion recognition technology as an alternative to the commonly used methods in the real estate analysis and valuation, which are usually based on surveys. The empirical analysis enabled determination of the mainstream property attributes significance from evoked emotions intensity within the group of property clients (represented by 156 respondents). The significance ranking determined on the basis of the unconscious expressed facial emotions was verified and compared to the answers given in a form of questionnaire. The results have shown that the conscious declaration of the attribute ranking differs from the emotion detection conclusions in several cases.

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“…The core of the argument lies in the definition of sustainable local property markets based on precise defined indicators enables it analyzes. Sustainability involves much more than the “green” issue, and that when measuring such factors, we can create an added value for real estate analysis (Boulanger, 2007; de Vries & Voß, 2018; Gross & Wolny‐Kucińska, 2017; Kobylińska & Cellmer, 2019; Lyytimäki et al, 2020; McCord et al, 2018; Sajnóg, Sobolewska‐Mikulska, & Wójcik‐Leń, 2019; Trojanek, Gluszak, & Tanaś, 2018; Wójcik‐Leń, Sobolewska‐Mikulska, Sajnóg, & Leń, 2018).…”

Section: Introductionmentioning

confidence: 99%

Property sustainable value versus highest and best use analyzes

Walacik

Renigier‐Biłozor

Chmielewska

et al. 2020

Sustainable Development

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Sustainable development of all the urban environment elements (including properties) is a very information requiring decision making process that absorbs data from many different fields. Since economic aspects of that kind of development are one the fundaments of the concept, property assessment procedures quite often support sustainable development. The current market value definition interpretation provided by valuation standards of international rage (EVS, IVS) and highest and best use of property (H&BU) have also become widely discussed and troublesome issues. The discussion is vital due to the fact of H&BU consideration in wider context, including sustainable development and sustainable value. The authors in order to improve clarity of the paper proposed a definition of sustainable value. The use of modified methods of sensitivity and scenario combined analysis as a solution enabling sustainable value quantification with the use of H&BU property assessment theory and practice was proposed. The obtained sustainable value coefficient, determined according to proposed methodology, enabled consideration of all the highest and best use tests. Additionally, it enabled consideration of sustainability context. It was described by maximal productivity of property strongly correlated with socioeconomic and socio-cultural phenomena. Highlights 1. The concept of sustainable development involves much more than the "green" issue, thus can create an added value for real estate analysis (especially based on "highest and best use" assumptions). 2. Even though the "highest and best use" notion has been defined its' interpretation causes many ambiguities and problems. 3. "Highest value" is a condition that requires taking into account all the circumstances (physical, legal, financial and productivity) with maximum: return rate/ developed area/increase of build-up area. 4. Maximal productivity in highest and best use context means directly not to give any decreases in sustainable value or/and give possibility to increases the sustainable value in the future. 5. "Sustainable value" can reflect not only economic issues (reflected directly by property value) but can exceed its' meaning to a broader sense including

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Modelling and Simulation of Selected Real Estate Market Spatial Phenomena

Cited by 7 publications

References 37 publications

Real Estate Industry Sustainable Solution (Environmental, Social, and Governance) Significance Assessment—AI-Powered Algorithm Implementation

Real Estate Industry Sustainable Solution (Environmental, Social, and Governance) Significance Assessment—AI-Powered Algorithm Implementation

Human emotion recognition in the significance assessment of property attributes

Property sustainable value versus highest and best use analyzes

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