A New Robust Bootstrap Algorithm for the Assessment of Common Set of Weights in Performance Analysis

Document Type: Research Paper


Department of Statistics, Faculty of Sciences, Gazi University, Ankara, Turkey


The performance of the units is defined as the ratio of the weighted sum of outputs to the weighted sum of inputs. These weights can be determined by data envelopment analysis (DEA) models. The inputs and outputs of the related (Decision Making Unit) DMU are assessed by a set of the weights obtained via DEA for each DMU. In addition, the weights are not generally common, but rather, they are very close to zero or they are even equal to zero. This means that some major criteria will not be considered. Another problem is the similarity of the efficiency scores of efficient DMUs. However, this is not the case in reality, and the performance of the DMUs should be completely ranked. Using common weights can solve these problems completely during measuring the performance of DMUs. There are some articles in the literature to determine common weight sets (CSWs), but none of them takes into account the bootstrap approach. This paper introduces a novel, empirical and robust algorithm based on bootstrapping technique to find CSWs.


Main Subjects

Article Title [Persian]

یک الگوریتم نوین بندپوتین قوی برای ارزیابی مجموعه وزنهای مشترک در تحلیل عملکرد

Authors [Persian]

  • احسان آلپ
  • ولکان سونر اوزسوی
گروه آمار، دانشکده علوم، دانشگاه غازی، آنکارا، ترکیه
Abstract [Persian]

عملکرد واحدهای تصمیم گیری (DMUs) به عنوان نسبت مجموع موزون خروجیها به مجموع موزون ورودیها تعریف می شود. این وزن ها می توانند با استفاده از مدلهای تحلیل پوششی داده ها (DEA) تعیین شوند. ورودیها و خروجیهای واحد تصمیم گیری مرتبط، توسط مجموعه ای از وزنهای به دست آمده از روش تحلیل پوششی داده ها برای هر واحد تصمیم گیری، ارزیابی می شوند. علاوه بر این، وزن ها به طور کلی مشترک نبوده، آنها خیلی نزدیک به صفر یا حتی گاهی برابر با صفر هستند. این بدین معنی است که برخی از معیارهای مهم (در ارزیابی عملکرد) در نظر گرفته نخواهند شد. مشکل دیگر امتیاز کارایی برابر برای واحدهای تصمیم گیری کارآ است. اگرچه این مطلب اغلب مورد قبول نیست و واحدهای تصمیم گیری باید به طور کامل رتبه بندی شوند. استفاده از وزن های مشترک می تواند این مشکلات را در حین اندازه گیری عملکرد واحدهای تصمیم گیری به طور کامل مرتفع نماید. اگرچه چندین مطالعه در ادبیات موضوع برای تعیین مجموعه وزنهای مشترک (CSWs) وجود دارند، اما هیچ کدام از آنها به رویکرد بندپوتین توجه نکرده اند. این مقاله یک الگوریتم جدید، بدیع ، تجربی و قوی مبتنی بر تکنیک بندپوتین برای پیدا کردن مجموعه وزنهای مشترک معرفی می کند.

Keywords [Persian]

  • تحلیل پوششی داده ها
  • مجموعه وزنهای مشترک
  • ارزیابی عملکرد
  • روش بندپوتین
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