ارزیابی واحدهای تصمیم گیری با داده‌های چند مرحله‌ای با استفاده از مدل‌های DEA-R
محورهای موضوعی : تحقیق در عملیاتمهسا ترکاوان نژاد 1 , بهروز دانشیان 2 , قاسم توحیدی 3 , مهناز مقبولی 4 , فرزین مدرس خیابانی 5
1 - گروه ریاضی، واحد تبریز، دانشگاه آزاد اسلامی، تبریز، ایران
2 - گروه ریاضی، واحد تهران مرکزی، دانشگاه آزاد اسلامی، تهران، ایران
3 - گروه ریاضی، واحد تهران مرکزی، دانشگاه آزاد اسلامی، تهران، ایران
4 - گروه ریاضی، واحد ارس، دانشگاه آزاد اسلامی، جلفا، ایران
5 - گروه ریاضی، واحد تبریز، دانشگاه آزاد اسلامی، تبریز، ایران
کلید واژه: non-zero weights, Overall efficiency, Multi-Periodic Production Process, lower bound, Ratio Data Envelopment Analysis(DEA-R),
چکیده مقاله :
در اندازه‌گیری کارآیی مجموعه‌ای از واحدها در یک بازه زمانی که چند دوره را پوشش می‌دهد، مدل‌های مبتنی بر تکنیک DEA استاندارد، وضعیت هر واحد در هر دوره را نادیده می‌گیرند که این باعث نتایج گمراه‌کننده می‌شود. این مقاله مدل‌های DEA-R را در حضور داده‌های چند دوره‌ای به گونه‌ای توسعه می‌دهد که روش پیشنهادی می‌تواند کارآیی کلی را با توجه به کارآیی کلی و دوره‌ای همه واحدها ارزیابی کند. روش پیشنهادی با ارائه یک کران پایین در وزن‌های بدست آمده از دوره‌ها، به اولویت‌بندی واحدها پرداخته و با ایجاد بینش‌های ارزشمند به تصمیم‌گیرندگان کمک می‌کند تا یافته‌های یک فرآیند ارزیابی عملکرد را بهتر درک کنند. این مقاله دارای چهار ویژگی است: (1) کارآیی کلی محاسبه شده از روش پیشنهادی به عملکرد تمام واحدها در تمام دوره‌ها بستگی دارد، (2) روش پیشنهادی، کارآیی کلی را با تحمیل یک کران پایین به دست آمده از تمام دوره‌ها بر روی وزن‌ها ارزیابی می‌کند، (3) این رویکرد دارای قدرت تشخیص بالا در تمییز واحدهایی است که در مدل‌های چند دوره‌ای موجود به عنوان کارآ ارزیابی می‌شوند، (4) برای روشن شدن جزئیات روش پیشنهادی، مقایسه‌ای بین مدل‌های موجود و مدل DEA-R چند دوره‌ای پیشنهادی، برای اندازه گیری کارآیی 22 بانک تجاری تایوانی در دوره زمانی 2009-2011 انجام شده است.
In measuring the efficiency of a set of units over a period of time covering multiple periods, models based on the standard DEA technique ignore the status of each unit in each period that causes misleading results. This paper develops DEA-R models in the presence of multi-periodic data in such a way that the proposed method can evaluate the overall efficiency with respect to the overall and periodic efficiencies of all units. By providing a lower bound on the weights derived from periods, the proposed method prioritizes the units for yielding valuable insights that aid decision makers to better understand the findings from a performance evaluation process. The contribution of this paper is fourfold: (1) the overall efficiency calculated from the proposed method depends on the unit performance of all units in all periods, (2) the proposed method determines the overall efficiency by imposing a lower bound obtained from all periods on the weights, (3) this method endowed with a high discriminatory power in differentiating the units which are evaluated as efficient in the existing multi-period models, (4) To elucidate the details of the proposed method, a comparison is made between the existing models in the literature and the proposed multi-period DEA-R method to measure the efficiency of 22 Taiwanese commercial banks for the period of 2009–2011.
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