Computerized Decision Aid for First-Time Homebuyers

Sarif, Siti Mahfuzah; Mohamed, Shafinah Farvin Packeer; Khalid, Mohamad Sukeri

doi:10.1007/978-3-030-33582-3_89

Cited by 2 publications

(2 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…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

View full text Add to dashboard Cite

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.

show abstract

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

show abstract

“…Several prior studies have endeavoured to establish and evaluate the relationship between sociocultural factors and home purchasing decisions. Sarif et al (2018) have discovered that social and cultural factors, including superstitions and numerology, can significantly influence a buyer's property purchase decision. Sociocultural factors also extend to lifestyle preferences and neighbourhood design, encompassing concepts like Feng Shui in the Asian social system.…”

Section: Sociocultural Factormentioning

confidence: 99%

Navigating First-Time Home Buyer Dilemmas: Generation Z's Perspective

Abdullah,

Ibrahim,

Arshad

et al. 2024

IJARBSS

View full text Add to dashboard Cite

The concept of 'home' is a cornerstone of living standards, providing not only a residence but also safety, security, and privacy. It acts as a shield against external threats and is essential for personal well-being. The decision to purchase a home holds immense significance, especially for Generation Z (Gen Z). As they aspire to own their dream homes, the choice they make can significantly impact their quality of life, productivity, and self-worth. However, buying a home is a complex endeavor, far more intricate than choosing a pair of shoes. Various factors must be considered before making such a significant investment. This research aims to identify the factors influencing the decisions of first-time homebuyers. The study collected data through questionnaires distributed to first-time homebuyers aged 18-29, representing Gen Z. A review of literature and prior research revealed six prominent factors. Financial considerations emerged as the most influential, with a mean rating of 4.44. This research highlights the pivotal role of financial factors in shaping the decisions of first-time homebuyers and contributes to a deeper understanding of the housing market dynamics.

show abstract

Computerized Decision Aid for First-Time Homebuyers

Cited by 2 publications

References 15 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

Navigating First-Time Home Buyer Dilemmas: Generation Z's Perspective

Contact Info

Product

Resources

About