The novelty hybrid model development proposal for mass appraisal of real estates in sustainable land management

Sisman, Suleyman; Akar, Ali Utku; Yalpır, Şükran

doi:10.1080/00396265.2021.1996797

Cited by 10 publications

(4 citation statements)

References 45 publications

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“…Another approach could be combining multiple techniques to create a hybrid model. The same approach was used in the study where the Cobb-Douglas and linear regression models were combined to form a mathematical model [24]. GIS was an additional tool to organise the regional data of the area under study.…”

Section: Discussionmentioning

confidence: 99%

A Map-Based Recommendation System and House Price Prediction Model for Real Estate

Mubarak

Tahir

Waqar³

et al. 2022

IJGI

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In 2015, global real estate was worth $217 trillion, which is approximately 2.7 times the global GDP; it also accounts for roughly 60% of all conventional global resources, making it one of the key factors behind any country’s economic growth and stability. The accessibility of spatial big data will help real estate investors make better judgement calls and earn additional profit. Since location is deemed necessary for real estate and consequent decision-making, digital maps have become a prime resource for real estate purchases, planning and development. Personalisation can assist in making judgments by identifying user desires and inclinations, which can then be recorded or captured as a user performs some interactions with a digital map. A personalised real estate portal can use this information to suggest properties, assist homeowners and provide valuable real estate analytics. This article presents a novel framework for recommending real estate to users. By monitoring user interactions through an online real estate portal, the framework can make personalised recommendations of real estate based on content, collaboration and location. The effectiveness of the recommendations was tested by the user feedback mechanism through a method of mean absolute precision, and the results show that 79% precise suggestions were generated, i.e., out of 5 recommendations produced, users were interested in at least 3. Along with that, a separate house price prediction model based on neural networks and classical regression techniques was also implemented to assist users in making an informed decision regarding prospects of real estate purchase.

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Section: Discussionmentioning

confidence: 99%

A Map-Based Recommendation System and House Price Prediction Model for Real Estate

Mubarak

Tahir

Waqar³

et al. 2022

IJGI

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“…In another paper [85], a hybrid mathematical model was developed to predict property values suitable for mass appraisal by combining a Cobb-Douglas regression with a linear regression. Property value criteria were grouped and weighted in a hierarchical structure using the analytic hierarchy process (AHP), and geographic information systems (GIS) were used to organize the spatiality of the data.…”

Section: Mathematical Appraisal Modelsmentioning

confidence: 99%

A Comprehensive Overview Regarding the Impact of GIS on Property Valuation

Droj,

Kwartnik-Pruc,

Droj

2024

IJGI

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In the face of pressing global challenges such as climate change, socioeconomic inequalities, and rapid urbanization, ensuring sustainable development in the regions has become essential. The COVID-19 pandemic has highlighted how vulnerable cities are to unforeseen crises and underscored the urgent need for proactive urban planning strategies capable of navigating dynamic and unpredictable futures. In this context, the use of geographic information systems (GIS) offers researchers and decision makers a distinct advantage in the study of spatial data and enables the comprehensive study of spatial and temporal patterns in various disciplines, including real estate valuation. Central to the integration of modern technology into real estate valuation is the need to mitigate the inherent subjectivity of traditional valuation methods while increasing efficiency through the use of mass appraisal techniques. This study draws on extensive academic literature comprising 103 research articles published between 1993 and January 2024 to shed light on the multifaceted application of GISs in real estate valuation. In particular, three main areas are addressed: (1) hedonic models, (2) artificial intelligence (AI), and mathematical appraisal models. This synthesis emphasizes the interdependence of numerous societal challenges and highlights the need for interdisciplinary collaboration to address them effectively. In addition, this study provides a repertoire of methodologies that underscores the potential of advanced technologies, including artificial intelligence, GISs, and satellite imagery, to improve the subjectivity of traditional valuation approaches and thereby promote greater accuracy and productivity in real estate valuation. By integrating GISs into real estate valuation methodologies, stakeholders can navigate the complexity of urban landscapes with greater precision and promote equitable valuation practices that are conducive to sustainable urban development.

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“…Models based on fuzzy logic and rough sets performed at over 90% accuracy [54]. Models proposed for forced sale value estimation based on fuzzy logic or OLS provide an accuracy of over 80% [55], models based on geostatistic techniques provide more than 85% accuracy, and models based on machine learning achieve over 89% [56,57]. This short literature review shows that the research on the applicability of modern market analysis techniques has intensified recently, and that such techniques offer high accuracy results (up to 96%).…”

Section: Modern Technologies As Tools In the Hands Of A Property Appr...mentioning

confidence: 99%

Modern Technologies in the Real Estate Market—Opponents vs. Proponents of Their Use: Does New Category of Value Solve the Problem?

Renigier‐Biłozor

Źróbek²,

Walacik³

2022

Sustainability

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The scientific literature and practical studies show that one of the main challenges facing the ongoing development of sustainable real estate markets is the understanding of the specifics of real estate as an object of increasing importance in the global economy. Misinterpretation of the principles of modern valuation models causes conflict between opponents and proponents of their use. To reconcile the two sides, the authors of this study propose the possibility of extending the methodology with new solutions—hybrid automated valuation models—and introducing a new value called the rough value. The study mostly draws on monographic and deductive reasoning methods, which includes an analysis of the basic principles of real estate appraisal (as described by internationally recognized professional standards) and valuation methods. The introduction of proposed solutions to valuation practice should be preceded by the development of unified standards and the principles of their application.

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The novelty hybrid model development proposal for mass appraisal of real estates in sustainable land management

Cited by 10 publications

References 45 publications

A Map-Based Recommendation System and House Price Prediction Model for Real Estate

A Map-Based Recommendation System and House Price Prediction Model for Real Estate

A Comprehensive Overview Regarding the Impact of GIS on Property Valuation

Modern Technologies in the Real Estate Market—Opponents vs. Proponents of Their Use: Does New Category of Value Solve the Problem?

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