Comparative modeling reveals consistent parameter rankings in residential real estate, indicating that Fuzzy SPOTIS provides rank-reversal-free valuation despite higher weight sensitivity.
The relationship between the property’s qualities and their perception of value impacts the effectiveness of real estate valuation models. Choosing the appropriate parameters (such as neighborhood, landscape view, property area) for property valuation is up to the subjectivity of the decision maker; therefore, it is difficult to apply an accurate method that justifies selecting these attributes. This research aims to propose an approach for ordering parameters in real estate valuations for residential buildings in large cities. Fuzzy TOPSIS and Fuzzy SPOTIS methods were applied for ranking, according to the criteria the property attractiveness for the client and associated property liquidity. The analysis used two scenarios: the first scenario focused on low-standard and the second on high-standard properties. The two multicriteria methods showed similar ranking efficiency in the scenarios. Fuzzy SPOTIS is a recently developed multiple criteria decision support method and stands out for usability because of its absence of order reversal and simpler axiomatics compared to Fuzzy TOPSIS. The sensitivity analysis showed that modelling with Fuzzy SPOTIS is more susceptible to changes in criterion weights, especially at extreme values, compared to Fuzzy TOPSIS. The paper highlights how fuzzy methods can assist decision-makers in determining the best parameters for real estate and construction valuation, incorporating specialist insights.
No takes yet. Share an insight, caveat, or question.
Barbosa et al. (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: