Since 2014
Efficiency measurement in Turkish manufacturing sector using Data Envelopment Analysis (DEA) and Artificial Neural Networks (ANN)
Journal of Economic & Financial Studies
View Archive Info| Field | Value | |
| Title |
Efficiency measurement in Turkish manufacturing sector using Data Envelopment Analysis (DEA) and Artificial Neural Networks (ANN)
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| Creator |
Akgöbek, Ömer
Yakut, Emre |
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| Subject |
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Artificial Neural Networks; Data Envelopment Analysis; Efficiency Measurement; Manufacture sector. C45; C53; G17. |
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| Description |
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.
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| Publisher |
LAR Center Press
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| Contributor |
—
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| Date |
2014-06-20
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| Type |
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion Peer-reviewed Article |
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| Format |
application/pdf
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| Identifier |
http://journalofeconomics.org/index.php/site/article/view/138
10.18533/jefs.v2i02.138 |
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| Source |
Journal of Economic & Financial Studies; Vol 2, No 03 (2014): June; 35-45
2379-9471 2379-9463 |
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| Language |
eng
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| Relation |
http://journalofeconomics.org/index.php/site/article/view/138/230
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| Rights |
Copyright (c) 2015 Journal of Economic & Financial Studies
http://creativecommons.org/licenses/by-nc/4.0 |
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