Journal of Korean Society of Industrial and Systems Engineering (산업경영시스템학회지)

Society of Korea Industrial and System Engineering (한국산업경영시스템학회)
권호 표지
DOI QR코드

DOI QR Code

The Performance Evaluation of Universities using DEA and AHP Model

DEA와 AHP를 이용한 대학의 성과 평가

  • Han, Yu-Jung (School of Management Consulting, Hanyang University) ;
  • Han, Chang-Hee (School of Business Administration, Hanyang University)
  • 한유정 (한양대학교 일반대학원 경영컨설팅학과) ;
  • 한창희 (한양대학교 경상대학 경영학부)
  • Received : 2014.08.07
  • Accepted : 2014.08.24
  • Published : 2014.09.30
Download PDF
⟨ Previous Next ⟩

Abstract

Because of the changing educational environments, Korean universities have to stand up to the challenge of enhancing their performances in educational activities. Therefore, Korean universities should seek ways to improve its competitiveness. The evaluation of Korean universities has been conducted by the Government and other media agencies like JoongAng's Daily to promote the development of universities. The purpose of this study is to evaluate and compare the relative efficiency of Korean universities using DEA (Data Envelopment Analysis) and AHP (Analytic Hierarchy Process) models. To produce reasonable results, major input and output variables have been determined in a step using a Profiling method, Spearman correlation analysis and AHP model. Also, this study shows that the relative efficiency for Korean universities is obtained not only based on quantity of output, but also on the basis of the quality of the output. Drawing upon the results of the analysis, this study provides a comprehensive and practical method for evaluating the performance of universities in terms of efficiency.

Keywords

References

  1. Abbott, M. and Doucouliagos, C., The Efficiency of Australian Universities : A Data Envelopment Analysis. Economics of Education Review, 2003, Vol. 22, No.2, p 89-97. https://doi.org/10.1016/S0272-7757(01)00068-1
  2. Ahn, T., Charnes, A., and Cooper, W., Using Data Envelopment Analysis to Measure the Efficiency of Not-for-Profit Organizations : A Critical Evaluation- Comment. Managerial and Decision Economics, 1998, Vol. 9, No. 3, p 251-253.
  3. Ahn, T.S., Cho, K.J., and Park, T.J., Korea University's educational efficiency behavior and the Influencing Factors. Journal of Accounting Research, 1998, Vol. 23, No. 2, p 183-215.
  4. Banker, R.D., Charnes, A., and Cooper, W.W., Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis. Management Science, 1984, Vol. 30, No. 9, p 1078-1092. https://doi.org/10.1287/mnsc.30.9.1078
  5. Charnes, A., Cooper, W.W., and Rhodes, E., Measuring the Efficiency of Decision Making Units. European Journal of Operational Research, 1978, Vol. 2, p 429-444. https://doi.org/10.1016/0377-2217(78)90138-8
  6. Jyoti, Banwet, D.K. and Deshmukh, S.G., Evaluating Performance of National R&D Organizations using Integrated DEA-AHP technique. International Journal of productivity and Performance Management, 2008, Vol. 57, No. 5, p 370-388. https://doi.org/10.1108/17410400810881836
  7. Jang, H.D. and Lee, J.H., An Efficient Selection of Promising Technology using DEA and AHP. International Business Journal, 2011, Vol. 18, No. 2, p 67-85.
  8. Kang, M.S., Performance Analysis in Korean higher education : Concept Establishment and Assessment Indicators. Educational development, 1985, Vol. 38, p 76- 81.
  9. Kim, K.S. and Hwang, K.S., Efficiency Evaluation of General Hospitals Using DEA and AHP Model. Journal of The Korean Production And Operations Management, 2010, Vol. 21, No. 3, p 251-267.
  10. Kim, S.H. and Lee, H.S., A Comparison Between University Evaluation and Its Efficiency as Measured by DEA. Educational Evaluation Research, 2007, Vol. 1, No. 21, p 1-26.
  11. Lee, D.J., Bae, S.S., and Kang, J.S., Development of R&D Project Selection Model and Web-based R&D Project Selection System using Hybrid DEA/AHP Model. Journal of the Korea Institute of Industrial Engineers, 2006, Vol. 32, No. 1, p 18-28.
  12. Min, J.H. and Kim, J.H., A Selection Process of Input and Output Factors Using Partial Efficiency in DEA. Journal of The Korean Operations Research and Management Science, 1998, Vol. 23, No. 3, p 75-90.
  13. Min, H.K., Kim, T.Y. and Hwang, S.J., Open Innovation R&D Efficiency Evaluation by Integrated AHP-DEA. Society of Korea Industrial and Systems Engineering, 2012, Vol. 35, No. 4, p 149-161. https://doi.org/10.11627/jkise.2012.35.4.149
  14. O, D.I., A Study on the discriminating of the hospitals based on the efficient insurance conversion factor by AHP and DEA. Journal of academia-industrial technology, 2009, Vol. 10, No. 6, p 1304-1316.
  15. Park, Y.G. and Lee, Y.H., The study on efficiency of private university : Using DEA analysis and tobit regression analysis. The Journal of Educational Administration, Vol. 28, No. 3, p 27-53.
  16. Park, T.J., A Study on the Factors Affecting the Organizational Efficiency of Universities in Korea, [dissertation]. [Seoul, Korea] : Changwon university; 1997.
  17. Rhim, H.S., Yoo, S.C., and Kim S.Y., A DEA/AHP Hybrid Model for Evaluation and Selection of R&D Projects. Journal of The Korean Operations Research and Management Science, 1999, Vol. 24, No. 4, p 1-12.
  18. Saaty, T., An Eigenvalue Allocation Model for Prioritization and Planning, Energy management and Policy Center, University of Pennsylvania, 1972.
  19. Sinuany-Stern, Z., Mehrez, A., and Hadad, Y., An AHP/ DEA Methodology for Ranking Decision Making Units. International Transactions in Operational Research, 2000, Vol. 7, No. 2, p 109-124. https://doi.org/10.1111/j.1475-3995.2000.tb00189.x
  20. Seo, H.C., Oh, J.K., and Kim, J.J., Education Efficiency Analysis of Architectural Design Firms Using a Combined AHP and DEA Model. Journal of Korea Institute of Construction Engineering and Management, 2013, Vol. 14, No. 3, p 78-87.
  21. Tofallis, C., Improving Discernment in DEA Using Profiling, OMEGA-International Journal of Management Science, 1996, Vol. 24, No. 3, p 361-364. https://doi.org/10.1016/0305-0483(95)00065-8

Cited by

  1. Evaluating Performance of Telecommunication Branch : Application of DEA with Non-Discretionary Factor vol.40, pp.4, 2017, https://doi.org/10.11627/jkise.2017.40.4.021