شاخص بهره‌وری مالمکوئیست در شبکه و کاربرد آن برای محاسبه پیشرفت و پسرفت پژوهش دانشکده‌ها در یک دانشگاه
الموضوعات :
مرتضی آذرباد
1
(دانش آموخته گروه مهندسی صنایع، واحد بندرعباس، دانشگاه آزاد اسلامی، بندرعباس، ایران)
فرهاد حسین زاده لطفی
2
(استاد،گروه ریاضی، واحدعلوم تحقیقات تهران، دانشگاه آزاداسلامی، تهران،ایران()
الکلمات المفتاحية: محاسبه پیشرفت و پسرفت, ساختار شبکه دومرحله‌ای, داده‌های نادقیق و کارایی نسبی,
ملخص المقالة :
ارتقای بهره وری سبب پیشرفت و توسعه یافتگی می شود و اکثر کشورهای توسعه یافته و در حال توسعه به منظور اشاعه نگرش به مقوله بهره وری و تعمیم بکارگیری فنون و روش های ارتقای آن، سرمایه گذاری های زیادی انجام داده اند.یکی از اجزاء مهم ارزیابی عملکرد، سنجش کارایی سازمان است. سنجش کارایی سازمان های مختلف و مقایسه کارایی بین واحدهای آنها، از جمله مسائل مهمی است که امروزه مورد توجه قرارگرفته است. یکی از مسائل اساسی که مؤسسه آموزشی و پژوهشی و به طور خاص دانشگاه ها با آن مواجه هستند فقدان سیستم های منسجم ارزیابی عملکرد است. تحلیل پوششی داده ها (DEA) تکنیکی ریاضی و مدیریتی برای ارزیابی واحدهای تصمیم گیرنده (DMU) با ورودی و خروجی های متعدد و متنوع است و با در نظر گرفتن وابستگی ها و ساختار سیستم ها و همچنین بازخورد اثرات متقابل معیارها به ارزیابی سیستماتیک عملکرد DMUها پرداخته می شود. در پژوهش حاضر اندازه گیری و مقایسه کارایی هجده دانشکده ی دانشگاه آزاد اسلامی واحد علوم و تحقیقات در حوزه پژوهشی برای دو مقطع زمانی صورت گرفت که در مجموع پژوهش دانشکده ها در مقطع زمانی اول یعنی نیمسال دوم سال تحصیلی 93-92 از وضعیت بهتری نسبت به مقطع زمانی دوم یعنی نیمسال اول سال تحصیلی 94-93 برخوردار بودند.
Abbot, M., & Doucouliagos, C.(2003),The Efficiency of Australian University: A Data Envelopment Analysis. Economics of Education Review, 22(1), 89-97.
Aliannezhad, Z. (2014),The Performance Review to Help of DMUs Ideal and Anti-Ideal in DEA. Master's Thesis, Islamic Azad University: Science and Research Branch, (In Persian).
Antonio, A., & Santos, M. (2008), Students and Teachers: A DEA Approach to the Relative Efficiency of Portuguese Public Universities. IDEAS, 13(1), 67-87.
Chen, Y., Cook, W., & Li., D. (2009), Additive Efficiency Decomposition in Two-Dtage DEA. European Journal of Operation Research, 196, 1170-1176.
Chen, Y., & Zhu, J. (2004), Measuring Information Technology Sin Direct Impact on Firm Performance. Information Technology and Management Journal, 5(1-2), 9-22.
Cooper, W. W., Deng, H., & Huang, Zh. Li., S. X. (2004), Chance Constrained Programming Approaches to Congestion in Stochastic Data Envelopment Analysis. Journal of European Journal of Operational Research, 155, 487-501.
DaneshvarRoyendegh, B., & Frol, S. (2010), A DEA-ANP Hybrid Algorithm Approach to Evaluate a University's Performance. International Journal of Basic and Applied Sciences, 9(10), 76-86.
Ebrahimzade Edlimi, M. (2012), The Relative Efficiency Calculate and Modeling in Two-Stage Decision Making Units. Master's Thesis, Islamic Azad University: Zahedan Branch, (In Persian).
Farrell, M. J. (1957), The Measurement of Productive Efficiency. Journal of the Royal Statistical Society, 120, 90-115.
Hamze, P. (2005), The Performance Evaluation of Departments in Islamic Azad University,s Science and Research Branch. Master's Thesis, Islamic Azad University: Qazvin Branch, (In Persian).
Jahanshahloo, G. R., & Afzalinejad, M. (2006), A Ranking Method Based on a Full-Inefficient Frontier. Applied Mathematical Modeling, 30, 248-260.
Jahanshahloo, GH., Alirezaei, M., Mehrabian, S. (1995), The Performance Evaluation of Efficiency in Tarbiat Moallem University of Tehran. Development Management, 4, 35-46, (In Persian).
Journady, O., & Ris, C. (2005), Performance in European Higher Education: A Non-Parametric Production Frontier Approach. Education Economics, 13(2),189-205.
Kao, C., & hung, H. T. (2008), Efficiency Decomposition in Two-Stage Data Envelopment Analysis: An Application to Non-Life Insurance Companies in Taiwan. European Journal of Operational Research, 185(1), 418-429.
Mousakhani, M., Vadoudi Mofid, B., & Hamidi, N. (2006), The Develop of Model for Assessing the Efficiency and Productivity Growth in Higher Education Institutions (Case study: Islamic Azad university). Journal of Industrial Strategic Management, 6, 34-53, (In Persian).
Parade, J. C., Asmild, M., & Simak, P. C. (2004), Using DEA and Worst Practice Dea in Credit Risk Evaluation. Journal of Productivity Analysis, 21, 153-165.4.
Seiford, L., & Zhu, J. (1999), Profit Ability and Market Ability of the Top 55US Commercial Banks. Management Science, 45(9), 1270-1288.
Wang, Y. M., Liu, J., & Elhag, T. M. S. (2007),An Integrated AHP-DEA Methodology for Bridge Risk Assessment. Journal of Computer and Industrial Engineering, 54(3), 513-525.
Yousefpour, M. (2013), The Presentation VC-DEA Model Developed for Multistage. Master's Thesis, Islamic Azad University: Qazvin Branch, (In Persian).
_||_Abbot, M., & Doucouliagos, C.(2003),The Efficiency of Australian University: A Data Envelopment Analysis. Economics of Education Review, 22(1), 89-97.
Aliannezhad, Z. (2014),The Performance Review to Help of DMUs Ideal and Anti-Ideal in DEA. Master's Thesis, Islamic Azad University: Science and Research Branch, (In Persian).
Antonio, A., & Santos, M. (2008), Students and Teachers: A DEA Approach to the Relative Efficiency of Portuguese Public Universities. IDEAS, 13(1), 67-87.
Chen, Y., Cook, W., & Li., D. (2009), Additive Efficiency Decomposition in Two-Dtage DEA. European Journal of Operation Research, 196, 1170-1176.
Chen, Y., & Zhu, J. (2004), Measuring Information Technology Sin Direct Impact on Firm Performance. Information Technology and Management Journal, 5(1-2), 9-22.
Cooper, W. W., Deng, H., & Huang, Zh. Li., S. X. (2004), Chance Constrained Programming Approaches to Congestion in Stochastic Data Envelopment Analysis. Journal of European Journal of Operational Research, 155, 487-501.
DaneshvarRoyendegh, B., & Frol, S. (2010), A DEA-ANP Hybrid Algorithm Approach to Evaluate a University's Performance. International Journal of Basic and Applied Sciences, 9(10), 76-86.
Ebrahimzade Edlimi, M. (2012), The Relative Efficiency Calculate and Modeling in Two-Stage Decision Making Units. Master's Thesis, Islamic Azad University: Zahedan Branch, (In Persian).
Farrell, M. J. (1957), The Measurement of Productive Efficiency. Journal of the Royal Statistical Society, 120, 90-115.
Hamze, P. (2005), The Performance Evaluation of Departments in Islamic Azad University,s Science and Research Branch. Master's Thesis, Islamic Azad University: Qazvin Branch, (In Persian).
Jahanshahloo, G. R., & Afzalinejad, M. (2006), A Ranking Method Based on a Full-Inefficient Frontier. Applied Mathematical Modeling, 30, 248-260.
Jahanshahloo, GH., Alirezaei, M., Mehrabian, S. (1995), The Performance Evaluation of Efficiency in Tarbiat Moallem University of Tehran. Development Management, 4, 35-46, (In Persian).
Journady, O., & Ris, C. (2005), Performance in European Higher Education: A Non-Parametric Production Frontier Approach. Education Economics, 13(2),189-205.
Kao, C., & hung, H. T. (2008), Efficiency Decomposition in Two-Stage Data Envelopment Analysis: An Application to Non-Life Insurance Companies in Taiwan. European Journal of Operational Research, 185(1), 418-429.
Mousakhani, M., Vadoudi Mofid, B., & Hamidi, N. (2006), The Develop of Model for Assessing the Efficiency and Productivity Growth in Higher Education Institutions (Case study: Islamic Azad university). Journal of Industrial Strategic Management, 6, 34-53, (In Persian).
Parade, J. C., Asmild, M., & Simak, P. C. (2004), Using DEA and Worst Practice Dea in Credit Risk Evaluation. Journal of Productivity Analysis, 21, 153-165.4.
Seiford, L., & Zhu, J. (1999), Profit Ability and Market Ability of the Top 55US Commercial Banks. Management Science, 45(9), 1270-1288.
Wang, Y. M., Liu, J., & Elhag, T. M. S. (2007),An Integrated AHP-DEA Methodology for Bridge Risk Assessment. Journal of Computer and Industrial Engineering, 54(3), 513-525.
Yousefpour, M. (2013), The Presentation VC-DEA Model Developed for Multistage. Master's Thesis, Islamic Azad University: Qazvin Branch, (In Persian).
