The Evolution Of Theoretical Approaches To Real Estate Market Value Valuation And Contemporary Trends

Abstract

This article systematizes the evolution of theoretical approaches to the valuation of real estate market value and identifies the principal methodological trends shaping contemporary appraisal practice. The study traces the movement from classical cost, income and salescomparison logic toward hedonic pricing, spatial econometrics, automated valuation models (AVMs), machine learning, explainable artificial intelligence and hybrid human–algorithmic valuation systems. The methodological basis combines comparative analysis, historicallogical analysis, synthesis of international valuation concepts and a structured review of recent academic literature. The results show that the development of valuation theory is not characterized by the replacement of traditional approaches, but by their progressive integration with richer datasets, spatial information and computational techniques. Traditional models retain advantages in transparency and professional defensibility, whereas machine-learning models can capture nonlinearities and complex interactions with higher predictive accuracy in many empirical settings. The article proposes an integrated conceptual framework in which market value is interpreted as the outcome of property-specific, locational, market, institutional and temporal factors, while the choice of valuation technique is determined by data quality, market activity, purpose of valuation and the required level of explainability. The framework may be used as a theoretical foundation for further improvement of real estate valuation methodology in emerging property markets.