Bilişim Sektöründeki Şirketlerin Etkinliklerinin Veri Zarflama Analizi ile Değerlendirilmesi(Evaluation Of The Efficiency Values Of The Companies In Information Technology Sector With Data Envelopment Analysis)

Year 2015, Volume: 22 Issue: 2, 331 - 340, 12.01.2016

Aşkın Aşkın Özdağoğlu

https://doi.org/10.18657/yecbu.61899

Cited By: 5

Abstract

Etkinlik değeri işletmelerin başarı düzeylerinin ölçülmesinde kullanılan önemli araçlardan biridir. Ancak etkinlik değerinin ölçülmesi sırasında çok sayıda girdi ve çıktının birlikte düşünülmesi gereklidir. Birçok girdi ve çıktının birlikte incelenmesine imkan sağlayan tekniklerden biri veri zarflama analizidir. Bu çalışmada sırasıyla, Veri Zarflama Analizi (VZA) hakkında bilgi verilmiş, yöntemin matematiksel işleyişi açıklanmış, konu ile ilgili yapılmış çalışmalara değinilmiş ve BIST Bilişim endeksinde yer alan oniki firmanın etkinlik değerleri veri zarflama analizi (VZA) ile belirlenerek sonuçlar değerlendirilmiştir. Buna göre bazı firmaların çok düşük yatırımla oldukça tatminkar kazanç elde ettiği bazı firmaların ise tam tersine yüksek yatırıma rağmen oransal olarak karının düşük olduğu görülmüştür.

Efficiency value is one of the important tools which is used for measuring success levels of the companies. However,many input and output factors must be taken into consideration for measuring the efficiency level. Data Envelopment Analysis (DEA) is one of the techniques that provides to evaluate many different input and output factors together. In this study, the information has been given about Data Envelopment Analysis, the mathematical process has been explained,the literature review has been made and the efficiency values of the twelve companies in BIST Information Index have been determined with data envelopment analysis and the results have been evaluated respectively. The results show that some companies have got satisfactory profit levels with low investment and some companies have got low profit in spite of huge investment.

Keywords

-

References

• Alberca-Oliver, P., Rodríguez-Oromendía, A., Parte-Esteban, L. (2015). Measuring The Efficiency Of Trade Shows: A Spanish Case Study. Tourism Management, 47, 127-137. doi:10.1016/j.tourman.2014.09.007
• Asandului, L., Roman, M., Fatulescu, P. (2014). The Efficiency of Healthcare Systems in Europe: A Data Envelopment Analysis Approach. Procedia Economics and Finance, 10, 261 – 268. doi:10.1016/S2212-5671(14)00301-3
• Aydın, İ. (2012). Bilişim Sektörü ve Türkiye’nin Sektördeki Potansiyeli. International Journal of New Trends in Arts, Sports & Science Education, 1(1), 180-200. http://ijtase.net/ijtase/v1_i1_article16.pdf
• Banker, R.D., Charnes, A., Cooper, W.W. (1984) Some Models For Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis. Management Science, 30(9), 1078-1092.
• http://pubsonline.informs.org/doi/abs/10.1287/mnsc.30.9.1078
• Charles, V., Kumar, M. (2014). Satisficing Data Envelopment Analysis: An Application To SERVQUAL Efficiency, Measurement, 51, 71–80. doi:10.1016/j.measurement.2014.01.023
• Charnes, A., Cooper, W. Rhodes, E. (1978). Measuring The Efficiency of Decision Making Units. European Journal of Operational Research, 2(6), 429-444. doi:10.1016/0377-2217(78)90138-8
• Costa, M. A., Lopes, A. L. M., Matos, G.B.B.D.P. (2015). Statistical evaluation of Data Envelopment Analysis versus COLS CobbeDouglas benchmarking models for the 2011 Brazilian tariff revision. Socio-Economic Planning Sciences, 49, 47-60. http://isiarticles.com/bundles/Article/pre/pdf/44427.pdf
• Dotoli, M. Epicoco, N., Falagario, M., Sciancalepore, F. (2015). A Cross-Efficiency Fuzzy Data Envelopment Analysis Technique For Performance Evaluation of Decision Making Units Under Uncertainty. Computers & Industrial Engineering, 79, 103–114. doi:10.1016/j.cie.2014.10.026
• Ederer, N. (2015). Evaluating Capital and Operating Cost Efficiency of Offshore Wind Farms: A DEA Approach. Renewable and Sustainable Energy Reviews, 42, 1034–1046. doi:10.1016/j.rser.2014.10.071
• Emrouznejad, A. Munisamy, S., Arabi, B. (2015). A New Slacks-Based Measure of Malmquist–Luenberger Index in The Presence of Undesirable Outputs. Omega, 51, 29–37. doi:10.1016/j.omega.2014.08.006
• -
• A. Özdağoğlu / Bilişim Sektöründeki Şirketlerin Etkinliklerinin Veri Zarflama Analizi ile Değerlendirilmesi
• Fuentes, R., Lillo-Bañuls, A. (2015). Smoothed Bootstrap Malmquist Index Based On DEA Model To Compute Productivity of Tax Offices. Expert Systems with Applications, 42, 2442–2450. doi:10.1016/j.eswa.2014.11.002
• http://www.srdrylmz.com/bilisim-sektorune-genel-bakis/, 19.08.2015
• Huguenin, J-M. (2015). Data Envelopment Analysis and Non-Discretionary Inputs: How To Select The Most Suitable Model Using Multi-Criteria Decision Analysis. Expert Systems with Applications, 42, 2570–2581. doi:10.1016/j.eswa.2014.11.004
• Iribarren, D., Marvuglia, A., Hild, P., Guiton, M., Popovici, E, Benetto, E. (2015). Life Cycle Assessment and Data Envelopment Analysis Approach For The Selection of Building Components According To Their Environmental Impact Efficiency: A Case Study For External Walls. Journal of Cleaner Production, 87, 707-716. doi:10.1016/j.jclepro.2014.10.073
• Khalili-Damghani, K., Tavana, M., Haji-Saami, E. (2015). A Data Envelopment Analysis Model with Interval Data and Undesirable Output For Combined Cycle Power Plant Performance Assessment. Expert Systems with Applications, 42, 760–773. doi:10.1016/j.eswa.2014.08.028
• Khoshnevisan, B., Bolandnazar, E., Shamshirband, S., Shariati, H. M., Anuar, N. B., Kiah, M.L.M. (2015). Decreasing Environmental Impacts of Cropping Systems Using Life Cycle Assessment (LCA) and Multi-Objective Genetic Algorithm. Journal of Cleaner Production, 86, 67-77. doi:10.1016/j.jclepro.2014.08.062
• Laplante, A.E., Paradi, J.C. (2015). Evaluation of Bank Branch Growth Potential Using Data Envelopment Analysis. Omega, 52, 33–41. doi:10.1016/j.omega.2014.10.009
• Lorenzo-Toja, Y., Vazquez-Rowe, I., Chenel, S., Marın-Navarro, D., Moreira, M. T., Feijoo, G. (2015). Eco-Efficiency Analysis of Spanish Wwtps Using The LCA - DEA Method. Water Research, 68, 651-666. doi:10.1016/j.watres.2014.10.040
• Omrani, H., Beiragh, R. G., Kaleibari, S.S. (2015). Performance Assessment of Iranian Electricity Distribution Companies By An Integrated Cooperative Game Data Envelopment Analysis Principal Component Analysis Approach. Electrical Power and Energy Systems, 64, 617–625. doi:10.1016/j.ijepes.2014.07.045
• Souza, G. D. S., Gomes, E.G. (2015). Management of Agricultural Research Centers in Brazil: A DEA Application Using A Dynamic GMM Approach. European Journal of Operational Research, 240, 819–824. doi:10.1016/j.ejor.2014.07.027
• Tavassoli, M., Faramarzi, G. R., Saen, R.F. (2015). Ranking Electricity Distribution Units Using Slacks-Based Measure, Strong Complementary Slackness Condition, and Discriminant Analysis. Electrical Power and Energy Systems, 64, 1214–1220. doi:10.1016/j.ijepes.2014.09.018
• Yılmaz, C., Özdil, T., Akdoğan, G. (2002). Seçilmiş İşletmelerin Toplam Etkinliklerinin Veri Zarflama Yöntemi ile Ölçülmesi. Manas Üniversitesi Sosyal Bilimler Dergisi, Kırgızistan Türkiye Manas Üniversitesi Yayınları : 20, Süreli Yayınlar Dizisi : 6, Sayı 4, Bişkek, 174-183. http://journals.manas.edu.kg/mjsr/oldarchives/Vol02_Issue04_2002/268.pdf
• Zhao, X., Zhou, C., Zhao, L., Zhang, S., Wen, P., Jiang, J. (2014). Condition Evaluation Model of Fluid Power System in Gradual Failure Based on Data Envelopment Analysis. Computers & Fluids, 110, 219-226. doi:10.1016/j.compfluid.2014.06.001