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The Theory of Fuzzy Logic and its Application to Real Estate Valuation

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Abstract

Fuzzy logic is based on the central idea that in fuzzy sets each element in the set can assume a value from 0 to 1, not just 0 or 1, as in classic set theory. Thus, qualitative characteristics and numerically scaled measures can exhibit gradations in the extent to which they belong to the relevant sets for evaluation. This degree of membership of each element is a measure of the element’s "belonging" to the set, and thus of the precision with which it explains the phenomenon being evaluated. Fuzzy sets can be combined to produce meaningful conclusions, and inferences can be made, given a specified fuzzy input function. The article demonstrates the application of fuzzy logic to an income-producing property, with a resulting fuzzy set output.

Suggested Citation

  • Carlo Bagnoli & Halbert C. Smith, 1998. "The Theory of Fuzzy Logic and its Application to Real Estate Valuation," Journal of Real Estate Research, American Real Estate Society, vol. 16(2), pages 169-200.
    • Handle: RePEc:jre:issued:v:16:n:2:1998:p:169-200
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    Cited by:

    1. d’Amato, Maurizio & Zrobek, Sabina & Renigier Bilozor, Malgorzata & Walacik, Marek & Mercadante, Giuseppe, 2019. "Valuing the effect of the change of zoning on underdeveloped land using fuzzy real option approach," Land Use Policy, Elsevier, vol. 86(C), pages 365-374.
    2. GLUMAC Brano & DES ROSIERS François, 2018. "Real estate and land property automated valuation systems: A taxonomy and conceptual model," LISER Working Paper Series 2018-09, Luxembourg Institute of Socio-Economic Research (LISER).
    3. Ching-Sen Hsieh & Yu-Wen Chen & Chih-Hung Wu & Tao Huang, 2012. "Characteristics of fuzzy synthetic decision methods for measuring student achievement," Quality & Quantity: International Journal of Methodology, Springer, vol. 46(2), pages 523-543, February.
    4. Caetano, José & Caleiro, António, 2005. "Corruption and Foreign Direct Investment. What kind of relationship is there?," EconStor Preprints 142738, ZBW - Leibniz Information Centre for Economics.
    5. Antonio Caleiro, 2006. "How is confidence related to unemployment in Portugal?," Applied Economics Letters, Taylor & Francis Journals, vol. 13(13), pages 887-890.
    6. Steven Peterson & Albert B. Flanagan, 2009. "Neural Network Hedonic Pricing Models in Mass Real Estate Appraisal," Journal of Real Estate Research, American Real Estate Society, vol. 31(2), pages 147-164.
    7. Katarzyna Kopczewska & Mateusz Kopyt & Piotr Ćwiakowski, 2021. "Spatial Interactions in Business and Housing Location Models," Land, MDPI, vol. 10(12), pages 1-25, December.
    8. Cankun Wei & Meichen Fu & Li Wang & Hanbing Yang & Feng Tang & Yuqing Xiong, 2022. "The Research Development of Hedonic Price Model-Based Real Estate Appraisal in the Era of Big Data," Land, MDPI, vol. 11(3), pages 1-30, February.
    9. Antipov, Evgeny & Pokryshevskaya, Elena, 2010. "Mass appraisal of residential apartments: An application of Random forest for valuation and a CART-based approach for model diagnostics," MPRA Paper 27645, University Library of Munich, Germany.
    10. António Caleiro, 2005. "How is Confidence Related to Unemployment in Europe? A fuzzy logic answer," Economics Working Papers 1_2005, University of Évora, Department of Economics (Portugal).
    11. Elena B. Pokryshevskaya & Evgeny A. Antipov, 2011. "Applying a CART-based approach for the diagnostics of mass appraisal models," Economics Bulletin, AccessEcon, vol. 31(3), pages 2521-2528.
    12. William Cheung & Lewen Guo & Yuichiro Kawaguchi, 2021. "Automated valuation model for residential rental markets: evidence from Japan," Journal of Spatial Econometrics, Springer, vol. 2(1), pages 1-34, December.
    13. Ünsal Özdilek, 2020. "Land and building separation based on Shapley values," Palgrave Communications, Palgrave Macmillan, vol. 6(1), pages 1-13, December.
    14. Bovkir, Rabia & Aydinoglu, Arif Cagdas, 2018. "Providing land value information from geographic data infrastructure by using fuzzy logic analysis approach," Land Use Policy, Elsevier, vol. 78(C), pages 46-60.
    15. Jasmina Ćetković & Slobodan Lakić & Marijana Lazarevska & Miloš Žarković & Saša Vujošević & Jelena Cvijović & Mladen Gogić, 2018. "Assessment of the Real Estate Market Value in the European Market by Artificial Neural Networks Application," Complexity, Hindawi, vol. 2018, pages 1-10, January.
    16. Pierluigi Morano & Paolo Rosato & Francesco Tajani & Benedetto Manganelli & Felicia Di Liddo, 2019. "Contextualized Property Market Models vs. Generalized Mass Appraisals: An Innovative Approach," Sustainability, MDPI, vol. 11(18), pages 1-28, September.
    17. M. Gordon Brown, 1999. "Design and Value: Spatial Form and the Economic Failure of a Mall," Journal of Real Estate Research, American Real Estate Society, vol. 17(2), pages 189-226.
    18. António Caleiro, 2003. "Subjective Versus Objective Economic Measures, A fuzzy logic exercise," Economics Working Papers 11_2003, University of Évora, Department of Economics (Portugal).
    19. Maurizio d'Amato, 2001. "Most Probable, most possible," ERES eres2001_140, European Real Estate Society (ERES).

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    JEL classification:

    • L85 - Industrial Organization - - Industry Studies: Services - - - Real Estate Services

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