Please use this identifier to cite or link to this item:
https://ruomo.lib.uom.gr/handle/7000/630
Title: | A novel network data envelopment analysis model for performance measurement of Turkish electric distribution companies |
Authors: | Petridis, Konstantinos Ünsal, Mehmet Güray Dey, Prasanta Kumar Örkcü, H. Hasan |
Type: | Article |
Subjects: | FRASCATI::Engineering and technology::Environmental engineering FRASCATI::Natural sciences::Mathematics::Applied Mathematics |
Keywords: | Network DEA Profit efficiency Directional distance function Electric distribution |
Issue Date: | 1-May-2019 |
Source: | Energy |
Volume: | 174 |
First Page: | 985 |
Last Page: | 998 |
Abstract: | Electric distribution companies have a significant role for both households and industries. Benchmarking of the electric distribution companies in the energy sector has become a subject that is studied widely nowadays due to the effect of privatization policies for developing countries. Since there are multiple production stages regarding the generation and supply procedures of electric power, Network DEA technique is used. Directional Distance Function is also integrated into Network DEA technique. Electric distribution companies are organizations that are aiming at maximizing profit while minimizing the expenses. The main problem is how the profit idea can be integrated into the evaluation process. The aim of the proposed model is to evaluate profit efficiency of electric distribution companies while taking into account expansion cost for additional energy supply. This two stage approach is applied to Turkish electric distribution companies. Results are presented based on radial and profit efficiency measures. The proposed model is demonstrates realistic results by considering the expenses and incomes of distribution companies. |
URI: | https://doi.org/10.1016/j.energy.2019.01.051 https://ruomo.lib.uom.gr/handle/7000/630 |
ISSN: | 0360-5442 |
Other Identifiers: | 10.1016/j.energy.2019.01.051 |
Appears in Collections: | Department of Applied Informatics |
Files in This Item:
File | Description | Size | Format | |
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ENERGY_paper.pdf | 757,28 kB | Adobe PDF | View/Open |
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