Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/311486 
Year of Publication: 
2017
Citation: 
[Journal:] Journal of Marketing and Consumer Behaviour in Emerging Markets (JMCBEM) [ISSN:] 2449-6634 [Issue:] 1 [Year:] 2017 [Pages:] 4-14
Publisher: 
University of Warsaw, Faculty of Management, Warsaw
Abstract: 
The purpose of this paper is to forecast housing prices in Ankara, Turkey using the artificial 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 artificial neural networks (ANN) proposed here will serve as a reference for countries that develop artificial 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 field of housing economics. Moreover, this is the first study that uses the artificial neural networks (ANN) approach for analyzing the housing market in Ankara/Turkey.
Subjects: 
Housing
artificial neural networks
forecasting
prices
Turkey
JEL: 
C15
D14
R31
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article

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