شاخص بهره‌وری مالمکوئیست در شبکه و کاربرد آن برای محاسبه پیشرفت و پسرفت پژوهش دانشکده‌ها در یک دانشگاه
محورهای موضوعی : مدیریت بازرگانیمرتضی آذرباد 1 , فرهاد حسین زاده لطفی 2
1 - دانش آموخته گروه مهندسی صنایع، واحد بندرعباس، دانشگاه آزاد اسلامی، بندرعباس، ایران
2 - استاد،گروه ریاضی، واحدعلوم تحقیقات تهران، دانشگاه آزاداسلامی، تهران،ایران(
کلید واژه: محاسبه پیشرفت و پسرفت, ساختار شبکه دومرحله‌ای, داده‌های نادقیق و کارایی نسبی,
چکیده مقاله :
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.
Improve productivity leads to progress and development and developed and developing countries in order to promote the attitude towards the use of techniques and methods to improve the efficiency and extend the done a lot of investments. Oneofthe important parts ofthe performance evaluation, performan cemeasurement organization. Performance measureand comparethe performan ceoftheirvarious organizations, includingthe main pointsof interestarelocated.One of the fundamental issues of education and research institutions and universities in particular are faced with the lack of a coherent system of performance appraisal. Development Environment Data (DEA) mathematical technique and management to evaluate theDecision Making Units (DMUs) with the input and output of multiple and diverse that combining this technique with Multiple Criteria Decision Making (MCDM) a technical engineering and taking into account dependencies and system structure as well as measures to assess systematic feedback interactions are paid DMU performance. This approach (combining two techniques, DEA and MCDM) to eliminate restrictions on the complete ranking in the classic DEA method.In this study, measure and compare the performance of the eighteen schools of Islamic Azad University, Science and Research branch in the field of research has been done for two time periods.
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).