The Use of Artificial Neural Networks (ANN) in Forecasting Housing Prices in Ankara, Turkey
Olgun Kitapci (),
Murat Fatih Tuna () and
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Olgun Kitapci: Akdeniz University, Uygulamali Bilimler Fakultesi Department of Marketing
Ömür Tosun: Akdeniz University, Uygulamali Bilimler Fakultesi Uluslararasi Ticaret ve Lojistik Bolumu
Murat Fatih Tuna: Cumhuriyet University, Iktisadi ve Idari Bilimler Fakultesi Yonetim Bilisim Sistemleri Bolumu
Tarik Turk: Cumhuriyet University, Muhendislik Fakultesi Geomatik Muhendisligi
Journal of Marketing and Consumer Behaviour in Emerging Markets, 2017, vol. 1, issue 5, 4-14
The purpose of this paper is to forecast housing prices in Ankara, Turkey using the artifi cial neural networks (ANN) approach. The data set was collected from one of the biggest real estate web pages during April 2013. A three-layer (input layer – one hidden layer – output layer) neural network is designed with 15 different inputs to forecast the future housing prices. The proposed model has a success rate of 78%. The results of this paper would help property investors and real estate agents in developing more effective property pricing management in Ankara. We believe that the artifi cial neural networks (ANN) proposed here will serve as a reference for countries that develop artifi cial neural networks (ANN) method-based housing price determination in future. Applying the artifi cial neural networks (ANN) approach for estimation of housing prices is relatively new in the fi eld of housing economics. Moreover, this is the fi rst study that uses the artifi cial neural networks (ANN) approach for analyzing the housing market in Ankara/Turkey.
Keywords: Housing; artificial neural networks; forecasting; prices; Turkey (search for similar items in EconPapers)
JEL-codes: C15 D14 R31 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:sgm:jmcbem:v:1:i:5:y:2017:p:4-14
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