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

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, em...

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Vydáno v:Sustainability Ročník 16; číslo 3; s. 1079
Hlavní autoři: Walacik, Marek, Chmielewska, Aneta
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.01.2024
Témata:
Algorithms
Artificial intelligence
Commodities
Computational linguistics
Decision making
Energy efficiency
Environmental stewardship
Feature selection
Hypotheses
Inclusion
Investment analysis
Language processing
Machine learning
Natural language interfaces
Real property
Sustainability
Sustainable development
Valuation
Poland
ISSN:2071-1050, 2071-1050
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Shrnutí: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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ISSN:2071-1050
2071-1050
DOI:10.3390/su16031079