Perception of market characteristics by appraisers, realtors and property buyers

Kokot, Sebastian; Bas, Marcin

doi:10.18276/sip.2016.45/1-28

Cited by 5 publications

(2 citation statements)

References 1 publication

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“…The literature often cites sets of real estate characteristics most often used in analyses, but due to the dynamically changing market reality, they are often inadequate or do not fully correspond to the realities of the market. The legitimacy of the search for new solutions in this area, which are an extension of currently used methods and techniques, has been repeatedly addressed in scientific studies by many researchers involved in the analysis of information in the real estate market [19][20][21][22][23][24][25][26][27][28][29].…”

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

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“…The determination of attribute significance in a broadly understood real estate market analysis is a highly complex and difficult topic according to multiple scientific studies on this subject (Kauko, 2007;Foryś & Kokot, 2008;Renigier-Biłozor & Biłozor, 2009;Luoma et al, 2010;Hurtubia et al, 2010;Opoku & Abdul-Muhmin, 2010;Jackson & Orr, 2011;Tan, 2012;Zydroń & Walkowiak, 2013;Renigier-Biłozor, 2013;García et al, 2014;Saw & Tan, 2014;Moghimi & Jusan, 2015;Kokot & Bas, 2016;Abidoye & Chan, 2016;Głuszak & Małkowska, 2017;Sarif et al, 2018;Nilsson, 2019;Ghumare, 2019). The complexity of the issue increases the necessity of economic, behavioural and analytical analysis.…”

Section: Research Limitations and Possible Areas Of Future Research Omentioning

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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Analysis of the impact of market characteristics on the prices of undeveloped land in Szczecin: application of an econometric model to estimate market feature weights

Frej

2024

Procedia Computer Science

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Perception of market characteristics by appraisers, realtors and property buyers

Cited by 5 publications

References 1 publication

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

Analysis of the impact of market characteristics on the prices of undeveloped land in Szczecin: application of an econometric model to estimate market feature weights

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