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Efficiency measurement in Turkish manufacturing sector using Data Envelopment Analysis (DEA) and Artificial Neural Networks (ANN)

Author

Listed:
  • Ömer Akgöbek

    (Department of Industry Engineering, Faculty of Engineering, Zirve University.)

  • Emre Yakut

    (Department of Management Information Systems, Osmaniye Korkut Ata University.)

Abstract

Data Envelopment Analysis (DEA) is a non-parametric measurement technique based on mathematical programming to measure the efficiency level of the firms by determining multiple input and output variables. Artificial neural network (ANN) is information processing system and computer program that imitates human brain’s neural network system. By entering the information from outside, ANN can be trained on examples related to the problem so that modeling of the problem can be provided. This study aims to examine the efficiency level of sectors operating in manufacturing industry in Turkey regarding the years between 1996-2008 via DEA and ANN to evaluate it from the financial aspect.

Suggested Citation

  • Ömer Akgöbek & Emre Yakut, 2014. "Efficiency measurement in Turkish manufacturing sector using Data Envelopment Analysis (DEA) and Artificial Neural Networks (ANN)," Journal of Economic and Financial Studies (JEFS), LAR Center Press, vol. 2(3), pages 35-45, June.
    • Handle: RePEc:lrc:lareco:v:2:y:2014:i:3:p:35-45
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    References listed on IDEAS

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    More about this item

    Keywords

    Artificial Neural Networks; Data Envelopment Analysis; Efficiency Measurement; Manufacture sector.;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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