Cobb-Douglas Hybrid Modelling Approach with Fuzzy-AHP Indexing for Residential Land Value Determining: A Case Study of Konya/Turkey

Authors

DOI:

https://doi.org/10.15320/ICONARP.2022.206

Keywords:

Fuzzy Analytic Hierarchy Process (FAHP), Cobb-Douglas Hybrid Model (C-DHM), local and spatial indexing, mass real estate appraisal, geographic information systems (GIS)

Abstract

In this study, for mass real estate appraisal forecasting, the hybrid mathematical model has been developed by combining Cobb-Douglas one of the nonlinear regression models, and linear modeling. The real estate attributes that create the model were grouped under four main-title: local, spatial, physical and legal features. While Cobb-Douglas was used for the value forecast based on the real estate attributes in each part of the model, an integrated model was created with a linear approach. As a different approach, local and spatial features, which are among the real estate attributes, were used as indexes for reasons such as preventing data confusion in the model and using according to the spatial analysis results of distances. Local and spatial index were prepared with the Fuzzy Analytic Hierarchy Process (FAHP) method to use within the model. For indexes, in the central districts of Konya, 10 local-specific attributes were used, while 12 spatial-specific attributes. The data set has been prepared using legal and physical attributes with market values collected from 457 parcels in the study area. Local and spatial attributes were added as indexes to the data set used in the hybrid model. In addition, modeling was done with the data set used in the Cobb-Douglas Hybrid Model (C-DHM) according to the Linear Multiple Regression Analysis (Linear MRA) method.  The developed C-DHM’s results was integrated with Geographical Information Systems (GIS). The performance values between the hybrid model and market values were examined. Results showed that R2 value for C-DHM and Linear MRA used as indexes was found to be 0,85 and 0,80. When the values obtained from C-DHM and market value are compared, it is seen that model gives successful results.

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Author Biographies

Şükran Yalpır, Konya Technical University

Assoc. Prof. Dr. Sukran Yalpir completed her master in 2001 and her doctorate in 2007 from the Institute of Science and Technology of Selçuk University on Land Management program. She is currently working as the Assoc Prof. Dr. at Department of Geomatics Engineering of Faculty of Engineering and Natural Sciences in Konya Technical University. Specializations: Land management, GIS, mass appraisal, real estate valuation, MCDA, model development and conceptualization.

Suleyman Sisman, Gebze Technical University

Res. Assist. Suleyman Sisman graduated from the Department of Geomatics Engineering of Engineering and Architecture Faculty of Selçuk University in 2018 in Konya. He completed his master in 2021 from the Institute of Science and Technology of Gebze Technical University on Geodesy and Geographical Information Technology program. He is currently working as the Res. Assistant at Department of Geomatics Engineering of Faculty of Engineering in Gebze Technical University”. Specializations: GIS, mass real estate valuation and MCDA and Machine-Learning Technique.

Ali Utku Akar, Konya Technical University

Res. Assist. Ali Utku Akar graduated from the Department of Geomatics Engineering of Engineering and Architecture Faculty of Selçuk University in 2018 in Konya. He completed his master in 2021 from the Institute of Graduate Education in Konya Technical University on Geomatics Engineering program. He is currently working as the Res. Assistant at Department of Geomatics Engineering of Faculty of Engineering in Konya Technical University”. Specializations: GIS, mass real estate valuation, MCDA, Machine-Learning Technique.

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30-06-2022

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Yalpır, Şükran, Sisman, S., & Akar, A. U. (2022). Cobb-Douglas Hybrid Modelling Approach with Fuzzy-AHP Indexing for Residential Land Value Determining: A Case Study of Konya/Turkey. ICONARP International Journal of Architecture and Planning, 10(1), 349–378. https://doi.org/10.15320/ICONARP.2022.206

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