طراحی مدل جامع ارزیابی عملکرد همراه با بهبود قدرت تفکیک پذیری واحدهای تصمیم در تحلیل پوششی داده ها به اتکاء سیستم استنتاج فازی
محورهای موضوعی : مدیریت(تحقیق در عملیات)
نوید شریفی
1
(دانشجوی دکتری گروه مدیریت صنعتی ، دانشکده مدیریت و حسابداری ،دانشگاه علامه طباطبایی،تهران،ایران)
مقصود امیری
2
(استاد گروه مدیریت صنعتی،دانشکده مدیریت و حسابداری ، دانشگاه علامه طباطبائی،تهران،ایران)
لعیا الفت
3
(استاد گروه مدیریت صنعتی،دانشکده مدیریت و حسابداری ، دانشگاه علامه طباطبائی،تهران،ایران)
امیر یوسفلی
4
(استادیار گروه مهندسی صنایع،دانشکده فنی ، دانشگاه زنجان، زنجان، ایران)
کلید واژه: تحلیل پوششی داده‌ها, کارت امتیازی متوازن, مؤسسات آموزش عالی, سیستم استنتاج فازی ممدانی,
چکیده مقاله :
استفاده از مدل تحلیل پوششی داده‌ها-برای ارزیابی عملکرد و رتبه بندی سازمان‌ها- در حال گسترش است. یکی از چالش‌های مهم این مدل، کاهش قدرت تفکیک پذیری واحدهای تصمیم‌گیر در مواجهه با تعداد زیاد ورودی و خروجی است؛ بنابراین هدف پژوهش، توسعۀ مدل جامع ارزیابی عملکرد همراه با بهبود قدرت تفکیک پذیری واحدهای تصمیم‌گیر است. در این راستا از کارت امتیازی متوازن برای شناسایی شاخص‌های جامع استفاده شد. برای اولین بار-به‌طور همزمان-از دو رویکرد عینی و ذهنی مبتنی بر تحلیل عاملی و سیستم استنتاج فازی برای کاهش شاخص‌ها و بهبود قدرت تفکیک پذیری واحدهای تصمیم‌گیر استفاده شد. پژوهش از حیث روش، توصیفی-تبیینی و از لحاظ جهت گیری تحقیق، کاربردی-توسعه ای است. جامعۀ آماری-برای شناسایی شاخص‌های ارزیابی عملکرد و تدوین قوانین استنتاج فازی-خبرگان مؤسسات آموزش عالی شهرستان سمنان بوده است. همچنین بیست و چهار مؤسسه آموزش عالی شهرستان سمنان برای تست مدل انتخاب شدند. ابزارگردآوری داده‌ها دو پرسشنامه محقق ساخته است. روایی پرسشنامه‌ها به ترتیب توسط روایی محتوا و سازه مورد تأیید قرارگرفت. همچنین پایایی پرسشنامه‌ها به ترتیب به استناد مقدارآلفای کرونباخ و پایایی ترکیبی بیشتر از 0.7مورد تایید است. دستاورد پژوهش را می‌توان طراحی مدل تلفیقی با رویکردهای عینی و ذهنی برای بهبود قدرت تفکیک پذیری واحدهای تصمیم‌گیر دانست. در این خصوص 26 شاخص شناسایی شد و توسط تحلیل عاملی به 8 سازه تقلیل یافت. همچنین با اتکا به سیستم استنتاج فازی طراحی شده،سازه‌ها نمره دهی شدند. نتایج نشان داد:قدرت تفکیک پذیری واحدهای تصمیم‌گیر توسط مدل پیشنهادی در مقایسه با دیگر مدل‌های مرسوم مبتنی بر رویکردهای عینی و ذهنی بیشتر بوده به طوری‌که تعداد واحدهای کارا در مدل پیشنهادی به 10 مورد کاهش یافته است. همچنین منتج از نتایج آزمون کروسکال- والیس و محاسبه انحراف معیارنمرۀ کارایی؛ مدل پیشنهادی به ترتیب با کسب میانگین رتبه 48.29 و کسب پراکندگی 0.221دارای رتبه کارایی کمتر و پراکندگی نمره کارایی بیشتر نسبت به سایر مدلها است که تأییدی بر بهبود قدرت تفکیک پذیری مدل پیشنهادی می باشد.
The utilization of data envelopment analysis models for assessing and ranking organizational performance is on the rise. One of the important challenges of this model is the diminishing of the decision-making unit’s precision when dealing with a multitude of inputs and outputs. Hence, the aim of the present research was to develop a comprehensive performance evaluation model while enhancing the resolution of decision-making units. To this end, a balanced scorecard was used to identify comprehensive indicators. At the same time, for the first time, two objective and subjective approaches based on factor analysis and fuzzy inference system were used simultaneously to reduce indicators and improve the resolution of decision-making units. This study used an explanatory-descriptive method and was conducted as an applied-developmental research. The statistical population for identifying performance evaluation indicators and developing fuzzy inference rules included the experts of higher education institutions of Semnan city. Moreover, twenty-four higher education institutions of Semnan city were selected for model testing. The researcher made two questionnaires for the data collection. The validity of the questionnaires was confirmed by content and construct validity, respectively. Also, the reliability of the questionnaires was confirmed by Cronbach's alpha value and composite reliability of more than 0.7 respectively. The main accomplishment of the research can be designing a unified model with objective and subjective approaches to improve the resolution of decision units. In this regard, 26 indicators were identified and reduced to 8 structures by factor analysis. Also, the structures were scored by relying on the designed fuzzy inference system. The results demonstrated a significant improvement in the resolution of decision-making units when utilizing the proposed model, in contrast to conventional models which are mostly based on objective and subjective methods. As a result, the number of effective units in the proposed model effectively reduced to 10. Additionally, the results of the Kruskal-Wallis test and the calculation of the standard deviation of the efficiency scores revealed that the proposed model with an average rating of 48.29 and a dispersion of 0.221 has a lower efficiency rating and a greater dispersion as compered to other models. This finding serves as a confirmation of the enhanced resolution achieved by the proposed model
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Abirami, G., & Venkataraman, R. (2021). Performance analysis of the dynamic trust model algorithm using the fuzzy inference system for access control. Computers & Electrical Engineering, 92(1), 107132. doi:10.1016/ j.compeleceng.2021.107132
Adler, N., & Golany, B. (2002). Including principal component weights to improve discrimination in data envelopment analysis. Journal of the Operational Research Society, 53(9), 985-991.
Alipour, Nasri, & Faramarz. (2017). Investigation and analysis of educational performance indicators of the University of Marine Sciences by BSC-TOPSIS method. Journal of Marine Science Education, 4 (2), 45-60 [In Persian].
Amiri, M. Ramezanzadeh, M. Khatami Firoozabadi, M & Sedghiani. (2016). Evaluating the performance of scientific departments of Amin University of Law Enforcement Sciences by the common weights approach in data envelopment analysis and fuzzy principal component analysis. Quarterly Journal of Resource Management, (14), 11-36 [In Persian]
Andersen, P., & Petersen, N. C. (1993). A procedure for ranking efficient units in data envelopment analysis. Management science, 39(10), 1261-1264. doi:10.1287/mnsc.39.10.1261
Azar,A. Zarei Mahmoudabadi,M. (2013). Improve performance measurement and resolution in DEA models by introducing a new model. Journal of Improving Management, (20),99-114 [In Persian].
Bagherikahvarin, M., & De Smet, Y. (2016). A ranking method based on DEA and PROMETHEE II (a rank based on DEA & PR. II). Measurement, 89, 333-342.doi:10.1016/j.measurement.2016.04.026
Bal, H., Örkcü, H. H., & Çelebioğlu, S. (2010). Improving the discrimination power and weights dispersion in the data envelopment analysis. Journal of Computers & Operations Research, 37(1), 99-107. doi:10.1016/j.cor.2009. 03.028
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Charnes, A., Cooper, W. W., Huang, Z. M., & Sun, D. B. (1990). Polyhedral cone-ratio DEA models with an illustrative application to large commercial banks. Journal of econometrics, 46(1-2), 73-91.doi:10.1016/0304-4076(90) 90048-X
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Chen, Y. (2005). Measuring super-efficiency in DEA in the presence of infeasibility. European Journal of Operational Research, 161(2), 545-551. doi:10.1016/j.ejor.2003.08.060
Chen, Y. W., Larbani, M., & Chang, Y. P. (2009). Multiobjective data envelopment analysis. Journal of the Operational Research Society, 60(11), 1556-1566. doi:10.1057/jors.2009.92
Cook, W. D., & Zhu, J. (2014). DEA Cobb–Douglas frontier and cross-efficiency. Journal of the Operational Research Society, 65(2), 265-268. doi:10.1057/jors.2013.13
Cook, W. D., Roll, Y., & Kazakov, A. (1990). A dea model for measuring the relative eeficiency of highway maintenance patrols. Journal of information systems and operational research, 28(2), 113-124. doi:10.1080/03155986. 1990.11732125
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