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The Use of Artificial Neural Networks (ANN) in Forecasting Housing Prices in Ankara, Turkey

Author

Listed:
  • 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)

Abstract

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.

Suggested Citation

  • Olgun Kitapci & Ömür Tosun & Murat Fatih Tuna & Tarik Turk, 2017. "The Use of Artificial Neural Networks (ANN) in Forecasting Housing Prices in Ankara, Turkey," Journal of Marketing and Consumer Behaviour in Emerging Markets, University of Warsaw, Faculty of Management, vol. 1(5), pages 4-14.
    • Handle: RePEc:sgm:jmcbem:v:1:i:5:y:2017:p:4-14
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    References listed on IDEAS

    as
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    More about this item

    Keywords

    Housing; artificial neural networks; forecasting; prices; Turkey;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • D14 - Microeconomics - - Household Behavior - - - Household Saving; Personal Finance
    • R31 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location - - - Housing Supply and Markets

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