Araştırma Makalesi
BibTex RIS Kaynak Göster

VERİ ZARFLAMA ANALİZİNDE ÖLÇEĞE GÖRE GETİRİ DURUMU: ÜNİVERSİTELERİN ETKİNLİK ÖLÇÜMÜ ÜZERİNE BİR UYGULAMA

Yıl 2021, Cilt: 10 Sayı: 2, 264 - 275, 31.12.2021

Öz

Girdi ile çıktı arasındaki ilişkinin bir yorumu olan ölçeğe göre getiri durumu, karar vericiler ve politika yapıcılar için önemli bir göstergedir. Çalışmanın temel amacı Veri Zarflama Analizi (VZA) yaklaşımında ölçeğe göre getiri durumunun belirlenmesinde kullanılabilecek yöntemlerin bir çerçevesini çizerek, literatüre göre getiri durumunu doğru şekilde belirlemenin yolunu göstermektir. Bu nedenle, VZA yaklaşımında ölçeğe göre getiri yönünü belirlemek için yaygın olarak kullanılan üç temel yöntem karşılaştırmalı olarak ele alınmıştır. Çalışmada ayrıca üç farklı VZA modeli kullanılarak 50 Türk üniversitenin göreli ekinlikleri ölçülmüştür. Bu üç model açısından bakıldığında üniversitelerin %50’den fazlasının etkin olduğu, %80’den fazlasının etkinlik skorlarının 0,8-1 arasında değer aldığı görülmüştür. Bununla birlikte yaklaşık olarak %40’nın ölçeğe göre sabit getiri (CRS), %34’nün ölçeğe göre artan getiri (IRS) ve %26’sının ölçeğe göre azalan getiri (DRS) altında faaliyet gösterdiği bulunmuştur.

Kaynakça

  • Abd Aziz, N. A., Janor, R. M. & Mahadi, R. (2013). Comparative Departmental Efficiency Analysis Within A University: A DEA Approach. Procedia-Social and Behavioral Sciences, 90, 540-548.
  • Aviles-Sacoto, S., Cook, W. D., Imanirad, R. & Zhu, J. (2015). Two-Stage Network DEA: When Intermediate Measures Can Be Treated as Outputs From the Second Stage. Journal of the Operational Research Society, 66(11), 1868-1877.
  • Aziz, N. A. A., Janor, R. M. & Mahadi, R. (2013). Comparative Departmental Efficiency Analysis Within A University: A DEA Approach. Procedia-Social and Behavioral Sciences, 90, 540-548.
  • Babacan, A. (2012). Organizasyon Performansında İyileştirmeler ve Referans Kümesi Üniversite Örneği. Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi, 13(2), 239-251.
  • Banker, R. D. (1984). Estimating Most Productive Scale Size Using Data Envelopment Analysis. European Journal of Operational Research, 17(1), 35-44.
  • Banker, R. D., Bardhan, I. & Cooper, W. W. (1996a). A Note on Returns to Scale in DEA. European Journal of Operational Research, 88(3), 583-585.
  • Banker, R. D., Chang, H. & Cooper, W. W. (1996b). Equivalence and Implementation of Alternative Methods For Determining Returns to Scale in Data Envelopment Analysis. European Journal of Operational Research, 89(3), 473-481.
  • 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.
  • Banker, R. D., Cooper, W. W., Seiford, L. M., Thrall, R. M. & Zhu, J. (2004). Returns to Scale in Different DEA Models. European Journal of Operational Research, 154(2), 345-362.
  • Banker, R. D. & Thrall, R. M. (1992). Estimation of Returns to Scale Using Data Envelopment Analysis. European Journal of Operational Research, 62(1), 74-84.
  • Baysal, M. E., ALÇILAR, B., Çerçioğlu, H. & Toklu, B. (2005). Türkiye'deki Devlet Üniversitelerinin 2004 Yılı Performanslarının, Veri Zarflama Analizi Yöntemiyle Belirlenip Buna Göre 2005 Yılı Bütçe Tahsislerinin Yapılması. Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 9(1), 67-73.
  • Beasley, J. E. (1990). Comparing university departments. Omega, 18(2), 171-183.
  • Charnes, A., Cooper, W. W. & Rhodes, E. (1978). Measuring The Efficiency of Decision Making Units. European Journal of Operational Research, 2(6), 429-444.
  • Cooper, W. W., Seiford, L. M. & Tone, K. (2006). Introduction to Data Envelopment Analysis and Its Uses: With DEA-Solver Software and References: Springer Science & Business Media.
  • Cooper, W. W., Seiford, L. M. & Zhu, J. (2011). Data Envelopment Analysis: History, Models, and Interpretations: Springer.
  • Debreu, G. (1951). The Coefficient of Resource Utilization. Econometrica: Journal of the Econometric Society, 273-292.
  • Essid, H., Ouellette, P. & Vigeant, S. (2014). Productivity, Efficiency, And Technical Change Of Tunisian Schools: A Bootstrapped Malmquist Approach With Quasi-Fixed Inputs. Omega, 42(1), 88-97.
  • Färe, R., & Grosskopf, S. (1985). A Nonparametric Cost Approach To Scale Efficiency. The Scandinavian Journal of Economics, 594-604.
  • Farrell, M. J. (1957). The Measurement of Productive Efficiency. Journal of the Royal Statistical Society. Series A (General), 120(3), 253-290.
  • Johnes, J. (2006). Data Envelopment Analysis and Its Application to the Measurement of Efficiency in Higher Education. Economics of Education Review, 25(3), 273-288.
  • Johnes, J. & Li, Y. (2008). Measuring The Research Performance Of Chinese Higher Education Institutions Using Data Envelopment Analysis. China Economic Review, 19(4), 679-696.
  • Koopmansa, T. (1951). An Analysis of Production as an Efficient Combination of Activities, Activity Analysis of Production and Allocation (TC Koopmans. Ed.). New York: Wiley.
  • Kuah, C. T. & Wong, K. Y. (2011). Efficiency Assessment of Universities Through Data Envelopment Analysis. Procedia Computer Science, 3, 499-506.
  • Seiford, L. M., & Zhu, J. (1999). An Investigation of Returns to Scale in Data Envelopment Analysis. Omega, 27(1), 1-11.
  • Thanassoulis, E. (2001). Introduction To The Theory and Application of Data Envelopment Analysis: Springer.
  • Zhu, J. (2014). Quantitative Models for Performance Evaluation and Benchmarking: Data Envelopment Analysis with Spreadsheets (Vol. 213): Springer.

THE SITUATION OF RETURNS TO SCALE IN DATA ENVELOPMENT ANALYSIS: AN APPLICATION ON THE EFFICIENCY MEASUREMENT OF UNIVERSITIES

Yıl 2021, Cilt: 10 Sayı: 2, 264 - 275, 31.12.2021

Öz

Estimation of return to scale, which is an interpretation of the relationship between input and output, is an important indicator for decision-makers and policymakers. The main purpose of the study is to show the way to correctly determine the returns to scale estimates according to the literature and to drawing a frame of the methods that can be used to determine the returns to scale situation in the Data Envelopment Analysis (DEA). For this reason, three basic methods commonly used to determine the direction of return to scale in the DEA approach are discussed comparatively. In the study, the relative efficiency of 50 Turkish universities was also measured using three different DEA models From the point of view of these three models, it was seen that more than 50% of the universities were efficient, and the efficiency scores of more than 80% were between 0.8 and 1. In addition, approximately 40% of them were found to have constant returns to scale (CRS), 34% to increasing returns to scale (IRS) and 40% to diminishing returns to scale (DRS).

Kaynakça

  • Abd Aziz, N. A., Janor, R. M. & Mahadi, R. (2013). Comparative Departmental Efficiency Analysis Within A University: A DEA Approach. Procedia-Social and Behavioral Sciences, 90, 540-548.
  • Aviles-Sacoto, S., Cook, W. D., Imanirad, R. & Zhu, J. (2015). Two-Stage Network DEA: When Intermediate Measures Can Be Treated as Outputs From the Second Stage. Journal of the Operational Research Society, 66(11), 1868-1877.
  • Aziz, N. A. A., Janor, R. M. & Mahadi, R. (2013). Comparative Departmental Efficiency Analysis Within A University: A DEA Approach. Procedia-Social and Behavioral Sciences, 90, 540-548.
  • Babacan, A. (2012). Organizasyon Performansında İyileştirmeler ve Referans Kümesi Üniversite Örneği. Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi, 13(2), 239-251.
  • Banker, R. D. (1984). Estimating Most Productive Scale Size Using Data Envelopment Analysis. European Journal of Operational Research, 17(1), 35-44.
  • Banker, R. D., Bardhan, I. & Cooper, W. W. (1996a). A Note on Returns to Scale in DEA. European Journal of Operational Research, 88(3), 583-585.
  • Banker, R. D., Chang, H. & Cooper, W. W. (1996b). Equivalence and Implementation of Alternative Methods For Determining Returns to Scale in Data Envelopment Analysis. European Journal of Operational Research, 89(3), 473-481.
  • 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.
  • Banker, R. D., Cooper, W. W., Seiford, L. M., Thrall, R. M. & Zhu, J. (2004). Returns to Scale in Different DEA Models. European Journal of Operational Research, 154(2), 345-362.
  • Banker, R. D. & Thrall, R. M. (1992). Estimation of Returns to Scale Using Data Envelopment Analysis. European Journal of Operational Research, 62(1), 74-84.
  • Baysal, M. E., ALÇILAR, B., Çerçioğlu, H. & Toklu, B. (2005). Türkiye'deki Devlet Üniversitelerinin 2004 Yılı Performanslarının, Veri Zarflama Analizi Yöntemiyle Belirlenip Buna Göre 2005 Yılı Bütçe Tahsislerinin Yapılması. Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 9(1), 67-73.
  • Beasley, J. E. (1990). Comparing university departments. Omega, 18(2), 171-183.
  • Charnes, A., Cooper, W. W. & Rhodes, E. (1978). Measuring The Efficiency of Decision Making Units. European Journal of Operational Research, 2(6), 429-444.
  • Cooper, W. W., Seiford, L. M. & Tone, K. (2006). Introduction to Data Envelopment Analysis and Its Uses: With DEA-Solver Software and References: Springer Science & Business Media.
  • Cooper, W. W., Seiford, L. M. & Zhu, J. (2011). Data Envelopment Analysis: History, Models, and Interpretations: Springer.
  • Debreu, G. (1951). The Coefficient of Resource Utilization. Econometrica: Journal of the Econometric Society, 273-292.
  • Essid, H., Ouellette, P. & Vigeant, S. (2014). Productivity, Efficiency, And Technical Change Of Tunisian Schools: A Bootstrapped Malmquist Approach With Quasi-Fixed Inputs. Omega, 42(1), 88-97.
  • Färe, R., & Grosskopf, S. (1985). A Nonparametric Cost Approach To Scale Efficiency. The Scandinavian Journal of Economics, 594-604.
  • Farrell, M. J. (1957). The Measurement of Productive Efficiency. Journal of the Royal Statistical Society. Series A (General), 120(3), 253-290.
  • Johnes, J. (2006). Data Envelopment Analysis and Its Application to the Measurement of Efficiency in Higher Education. Economics of Education Review, 25(3), 273-288.
  • Johnes, J. & Li, Y. (2008). Measuring The Research Performance Of Chinese Higher Education Institutions Using Data Envelopment Analysis. China Economic Review, 19(4), 679-696.
  • Koopmansa, T. (1951). An Analysis of Production as an Efficient Combination of Activities, Activity Analysis of Production and Allocation (TC Koopmans. Ed.). New York: Wiley.
  • Kuah, C. T. & Wong, K. Y. (2011). Efficiency Assessment of Universities Through Data Envelopment Analysis. Procedia Computer Science, 3, 499-506.
  • Seiford, L. M., & Zhu, J. (1999). An Investigation of Returns to Scale in Data Envelopment Analysis. Omega, 27(1), 1-11.
  • Thanassoulis, E. (2001). Introduction To The Theory and Application of Data Envelopment Analysis: Springer.
  • Zhu, J. (2014). Quantitative Models for Performance Evaluation and Benchmarking: Data Envelopment Analysis with Spreadsheets (Vol. 213): Springer.
Toplam 26 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Makaleler
Yazarlar

Akın Özkan 0000-0003-2862-2496

Yayımlanma Tarihi 31 Aralık 2021
Gönderilme Tarihi 6 Nisan 2021
Yayımlandığı Sayı Yıl 2021 Cilt: 10 Sayı: 2

Kaynak Göster

APA Özkan, A. (2021). VERİ ZARFLAMA ANALİZİNDE ÖLÇEĞE GÖRE GETİRİ DURUMU: ÜNİVERSİTELERİN ETKİNLİK ÖLÇÜMÜ ÜZERİNE BİR UYGULAMA. İnönü Üniversitesi Uluslararası Sosyal Bilimler Dergisi, 10(2), 264-275.

İnönü Üniversitesi Uluslararası Sosyal Bilimler Dergisi 

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.