نوع مقاله : مقاله علمی - پژوهشی
نویسندگان
1 برنامه ریزی درسی،دانشکده روانشناسی و علوم تربیتی،تهران جنوب،تهران، ایران
2 دانشجوی دکترای مدیریت آموزش عالی، دانشگاه آزاد اسلامی، واحد تهران جنوب، ایران
چکیده
چکیده: ارزیابی کارایی دانشگاه‌ها، بررسی علل کارایی و ناکارایی آنها برای اصلاح واحدهای ناکارا اهمیت زیادی دارد. در این تحقیق برای ارزیابی کارایی دانشکده‌های دانشگاه خلیج فارس بوشهر، از رویکرد تحلیل پوششی داده‌ها و مدل برنامه‌ریزی آرمانی استفاده می‌شود. این روش یکی از فنون ناپارامتریک تحقیق در عملیات است و با نگاهی جامع و یکپارچه و با در نظر داشتن تمامی عوامل مؤثر بر عملکرد واحدها، امکان تشخیص واحدهای ناکارا را فراهم می‌کند. به‌طورکلی ارزیابی دانشگاه‌ها و تشخیص واحدهای ناکارا، به‌علت پیچیدگی و گستردگی ورودی‌ها و خروجی‌ها به کمک روش‌های کلاسیک دشوار است لذا بهره‌گیری از رویکرد تحلیل پوششی داده‌ها، می‌تواند دست‌یابی به این مهم را آسان کند. در اینجا، یک مطالعه موردی برای ارزیابی کارایی نسبی دانشکده‌های فنی مهندسی، علوم انسانی و مدیریت و اقتصاد در سال تحصیلی 99-98 از دانشگاه خلیج فارس بوشهر انجام شده است. ابتدا با بررسی پیشینه تحقیقات مشابه، ورودی‌ها و خروجی‌های مرتبط با عملکرد دانشکده‌ها شناسایی شد. سپس با جمع‌آوری داده‌های مربوط از بانک اطلاعاتی دانشگاه خلیج فارس، زمینه مدل‌سازی ریاضی مبتنی بر رویکرد تحلیل پوششی داده‌ها با کمک نرم افزار لینگو، مهیا گردید. نتایج حاکی از سطوح کارایی متفاوت و برتری دانشکده اقتصاد و مدیریت نسبت به سایر دانشکده‌ها است.
کلیدواژه‌ها
عنوان مقاله [English]
APPLICATION OF DATA ENVELOPMENT ANALYSIS APPROACH FOR CURRENCY EDUCATION IN THE FACULTIES OF BUSHEHR PERSIAN GULF UNIVERSITY: A CASE STUD
نویسندگان [English]
- Mohammad Nourian 1
- Mohammad Ghalehgolabi 2
1 Curriculum,Faculty of Psychology and Educational Sciences,Tehran jonoob,Tehran,Iran
2
چکیده [English]
Evaluating the proficiency of universities, examining the causes of their efficiency and inefficiency are very important for revising inefficient units. In this research, for efficiency evaluation of the faculties of Persian Gulf University, data envelopment analysis approach and the ideal planning model are used. This method is one of the non-parametric techniques of operations research with a comprehensive and integrated view, which taking into account all the factors affecting the performance of units, it is possible to identify inefficient units. In general, it is difficult to evaluate universities and identify inefficient units due to the complexity and breadth of inputs and outputs using classical methods. Here, a case study has been conducted to evaluate the relative efficiency of the faculties of engineering, humanities, management and economics in the 99-98 academic year of Bushehr Persian Gulf University. First, by examining the background of similar research, inputs and outputs related to the performance of the faculties were identified. Then, by collecting the relevant data from the database of Persian Gulf University, field of mathematical modeling based on the data envelopment analysis approach was prepared with help of Lingo. The results indicate different levels of efficiency and superiority of the Faculty of Economics.
کلیدواژه‌ها [English]
- Data envelopment analysis
- deal planning model
- relative efficiency
- evaluation
- Persian Gulf University
Adler, N., & Volta, N. (2019). Ranking Methods Within Data Envelopment Analysis. In The Palgrave Handbook of Economic Performance Analysis (pp. 189-224). Palgrave Macmillan, Cham.
Afonso, A., & Santos, M. (2008). A DEA approach to the relative efficiency of Portuguese public universities. Portuguese Journal of Management Studies, 13(1), 67-87.
Agasisti, T., & Gralka, S. (2019). The transient and persistent efficiency of Italian and German universities: A stochastic frontier analysis. Applied Economics, 51(46), 5012-5030.
Alam Tabriz, A., Razieh, F., & Hesam, S. (2010). Evaluating the efficiency of Shahid Beheshti University faculties with an integrated approach of data envelopment analysis and ideal planning model, Industrial Management Studies, 8(19), 1-22.
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.
Charnes, A., & Cooper, W. W. (1957). Management models and industrial applications of linear programming. Management Science, 4(1), 38-91.
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). A data envelopment analysis approach to evaluation of the program follow through experiment in US public school education (No. MSRR-432). Carnegie-Mellon Univ Pittsburgh Pa Management Sciences Research Group.
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444.
Cho, J., & Baek, W. (2019). Identifying factors affecting the quality of teaching in basic science education: Physics, biological sciences, mathematics, and chemistry. Sustainability, 11(14), 3958.
Cooper, W. W., Seiford, L. M., & Zhu, J. (2004). Data envelopment analysis. In Handbook on data envelopment analysis (pp. 1-39). Springer, Boston, MA.
Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society: Series A (General), 120(3), 253-281.
Hadi, R., Rezapour, Y., & Salmanpour, S. (2016). Indicators for measuring the quality of higher education based on the Kano model in Urmia University, Scientific-Research Journal of Education and Evaluation, 9(34), 35-50. [in Persian]
Helal, S., Li, J., Liu, L., Ebrahimie, E., Dawson, S., & Murray, D. J. (2019). Identifying key factors of student academic performance by subgroup discovery. International Journal of Data Science and Analytics, 7(3), 227-245.
Johnes, J., & Johnes, G. (1995). Research funding and performance in UK university departments of economics: A frontier analysis. Economics of Education Review, 14(3), 301-314.
Khadivi, A., Seyed Kalan, S. M., Hassanpour, T., Ahmadi, H., & Tarahbari, H. (2015). A study of factors affecting the quality of education and teaching in farhangian university (Case Study: Campuses of Ardabil Province). Education and Evaluation Quarterly, 11, 185-161. [in Persian]
Koronakos, G., Sotiros, D., Despotis, D. K., & Apostolou, D. (2017, June). Performance evaluation of academic research activity in a greek university: A DEA approach. In International Conference on Intelligent Decision Technologies (pp. 373-383). Springer, Cham.
Kuah, C. T., & Wong, K. Y. (2011). Efficiency assessment of universities through data envelopment analysis. Procedia Computer Science, 3, 499-506.
Latif, K. F., Latif, I., Farooq Sahibzada, U., & Ullah, M. (2019). In search of quality: Measuring higher education service quality (HiEduQual). Total Quality Management & Business Excellence, 30(7-8), 768-791.
Li, J., Li, J., & Zheng, F. (2014). Unified efficiency measurement of electric power supply companies in China. Sustainability, 6(2), 779-793.
Mehregan, M. R. (2008). Quantitative models in evaluating the performance of organizations. Faculty of University Management, Tehran, second edition. [in Persian]
Movahedi, R., Shirkhani, M., & Hassanpour Talebi, B. (2017). A study of factors affecting improving the quality of education from students perspectives (Case Study of the Faculty of Agriculture, Bu Ali Sina University). Journal of Higher Education, 38, 110-79. [in Persian]
Nazarko, J., & Šaparauskas, J. (2014). Application of DEA method in efficiency evaluation of public higher education institutions. Technological and Economic development of Economy, 20(1), 25-44.
Nusche, D., Earl, L., Maxwell, W., & Shewbridge, C. (2011). OECD reviews of evaluation and assessment in education. Oslo: OECD.
Reichmann, G., & Sommersguter-Reichmann, M. (2006). University library benchmarking: An international comparison using DEA. International journal of production economics, 100(1), 131-147.
Sagarra, M., Mar-Molinero, C., & Agasisti, T. (2017). Exploring the efficiency of Mexican universities: Integrating data envelopment analysis and multidimensional scaling. Omega, 67, 123-133.
Samati & Rezvani, M. A. (2001). A study of the efficiency of large public universities in Iran using the DEA method. Economic Research, 59, 147-117. [in Persian]
Sufian, F. (2011). Benchmarking the efficiency of the Korean banking sector: a DEA approach. Benchmarking: An International Journal.
Talluri, S. (2000). Data envelopment analysis: models and extensions. Decision Line, 31(3), 8-11.
Taqwa Nia, M., & Sohrabi, Z. (2015). The concept of quality in the education system: Qualitative study, Strides in Development of Medical Education, 12(3), 561-563. [in Persian]
)