Evaluating the effectiveness of companies using the DEA method
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- Category: Content №6 2020
- Last Updated on 22 December 2020
- Published on 30 November -0001
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Authors:
A.Borodin, orcid.org/0000-0002-2872-1008, Plekhanov Russian University of Economics, Moscow, Russian Federation, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
I.Mityushina, orcid.org/0000-0003-3566-5654, Belgorod State National Research University, Belgorod, Russian Federation, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2020, (6): 187 - 193
https://doi.org/10.33271/nvngu/2020-6/187
Abstract:
Purpose. The paper assesses the effectiveness of Russian oil and gas companies. It is hypothesized that the DEA method for evaluating the effectiveness of companies gives the most accurate results compared to the method based on profitability coefficients and allows you to determine the individual and industry-wide effectiveness of companies.
Methodology. The research methodology for testing the hypothesis includes calculating the profitability of oil and gas companies in Russia, as well as classic DEA analysis.
Findings. The empirical base of the study consists of relative and absolute indicators for seven oil and gas companies with the highest revenue in the industry. The result of the study is to confirm the accepted hypothesis and determine the most effective of the studied companies.
Originality. Models for evaluating the performance of companies based on the DEA analysis were developed (at the output of the models there were adopted: revenue, capitalization and oil production). A rating for evaluating the performance of oil and gas companies has been developed, which allowed us to comprehensively characterize the performance of the largest oil and gas companies in Russia (based on the calculation of profitability and technical efficiency indicators), as well as to identify general trends in the industry.
Practical value. The models considered and the results of relative indicators allowed us to conclude that in order to assess the overall performance of companies, it is not enough to analyze individual indicators; moreover, the best result is achieved when building various models that allow a multi-sided approach to the study. The presented models can be recommended for evaluating the performance of companies that belong not only to the oil and gas industry, but also to other industries.
Keywords: company performance, DEA method, profitability indicator, return on equity, return on assets
References.
1. Fedorova, E.A., Korkmazova, B.K., & Muratov, M.A. (2015). Evaluating the effectiveness of companies with foreign direct investment: industry features in the Russian Federation. Prostranstvennaya ekonomika, 2, 47-63. https://doi.org/10.14530/se. 2015. 2. 047-063.
2. Kurepova, A.M., & Yuva, D.S. (2019). Justification of the choice of indicators for evaluating the performance of companies on the example of the oil and gas industry. Interekspo GEO Sibir, 2(5), 257-265. https://doi.org/10.33764/2618-981X-2019-2-5-257-265.
3. Kamande, M., & Lokina, R. (2013). Clean Production and Profitability: An Eco-efficiency Analysis of Kenyan Manufacturing Firms. Journal of Environment & Development, 22(2), 169-185. https://doi.org/10.1177/1070496512471948.
4. Tuskan, B., & Stojanovic, A. (2016). Measurement of cost efficiency in the European banking industry. Croatian Operational Research Review, 7(1), 47-66.
5. Dimitric, M., Tomas Zikovic, I., & Arbula Blecich, A. (2019). Profitability determinants of hotel companies in selected Mediterranean countries. Economic Research-Ekonomska Istrazivanja, 32(1), 1977-1993. https://doi.org/10.1080/1331677X.2019.1642785.
6. Filimonova, I.V., & Komarova, A.V. (2019). Factor analysis of the economic efficiency of the Russian oil and gas industry. Vestnik Permskogo nacionalnogo issledovatelskogo politehnicheskogo universiteta. Socialno-ekonomicheskie nauki, 4, 204-217. https://doi.org/10.15593/2224-9354/2019.4.16.
7. Bondarenko, T., Prodanova, N., Borodin, A., Kokorev, A., & Kairbekuly, A. (2020). The role of non-financial reporting in corporate sustainability of pharmaceutical industry. Systematic Reviews in Pharmacy, 11(12), 1514-1522. https://doi.org/10.13838/srp.2020.12.223.
8. Vasylieva, T., Jurgilewicz, O., Poliakh, S., Tvaronaviien,M., & Hydzik, P. (2020). Problems of measuring countrys financial security. Journal of International Studies, 13(2), 329-346. https://doi.org/10.14254/2071-8330.2020/13-2/22.
9. Grigoriev, A.N., & Otverchenko, L.F. (2016). Comprehensive assessment of the airlines performance. Voprosi studencheskoi nauki, 5(5), 19-25.
10. Borodin, A., Ziyadin, S., Islyam, G., & Panaedova, G. (2020). Impact of mergers and acquisitions on companies financial performance. Journal of International Studies, 13(2), 34-47. https://doi.org/10.14254/2071-8330.2020/13-2/3.
11. Chien, L., & Chi, S. (2019). An integrated data envelopment approach for evaluating the meat companies efficiency. Agricultural Economics, 65(10), 470-480. https://doi.org/10.17221/91/2019-AGRICECON.
12. Puertas Medina, R., Mart Selva, M.L., & Calafat Marzal,C. (2020). An analysis of innovation in textile companies: An efficiency approach. Bulletin of Economic Research, 72(1), 63-76. https://doi.org/10.1111/boer.12210.
13. Hosseinzadeh, A., Smyth, R., Valadkhani, A., & Le, V. (2016). Analyzing the Efficiency Performance of Major Australian Mining Companies Using Bootstrap Data Envelopment Analysis. Economic Modelling, 57, 26-35. https://doi.org/10.1016/j.econmod.2016.04.008.
14. Garg, M., & Garg, S. (2020). Efficiency Evaluation of Indian General Insurance Companies IUP. Journal of Management Research, 19(1), 7-26.
15. Chernov, S., & Kolkova, N. (2019). Determination of the economic efficiency index of electric grid companies based on DEA analysis. Biznes. Obrazovanie. Pravo, 1(46), 285-292. https://doi.org/10.25683/VOLBI.2019.46.115.
16. Chao, S.-L., Yu, M.M., & Hsieh, W.F. (2018). Evaluating the efficiency of major container shipping companies: A framework of dynamic network DEA with shared inputs. Transportation Research Part A: Policy and Practice, 117, 44-57. https://doi.org/10.1016/j.tra.2018.08.002.
17. Atris, A., & Goto, M. (2019). Vertical structure and efficiency assessment of the US oil and gas. Resources Policy, 63, 301-313. https://doi.org/10.1016/j.resourpol.2019.101437.
18. Kolesnev, I. (2018). Recommendations for improving the efficiency of export-oriented food industry enterprises. Agrarnaya ekonomika, 9(280), 32-42.
19. Alimkhanova, A.N., & Mizel, A.A. (2019). Evaluating the effectiveness of enterprises based on the DEA method. Dokladi Tomskogo gosudarstvennogo universiteta sistem upravleniya i radioelektroniki, 22(2), 104-108. https://doi.org/10.21293/1818-0442-2019-22-2-104-108.
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