Performance Evaluation of Banking Organizations Using the New Proposed Integrated DEA-BSC Model

  • سال انتشار: 1398
  • محل انتشار: فصلنامه فرایندهای نوین در ساخت و تولید، دوره: 8، شماره: 1
  • کد COI اختصاصی: JR_MPMPJ-8-1_006
  • زبان مقاله: انگلیسی
  • تعداد مشاهده: 531
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نویسندگان

Kianoosh Kianfar

Department of Industrial Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

Mahnaz Ahadzadeh Namin

Department of Mathematics, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran

Akbar Alam Tabriz

Department of Management, Shahid Beheshti University, Tehran, Iran

Esmaeil Najafi

Department of Industrial Engineering, Science and Research branch, Islamic Azad University, Tehran, Iran

Farhad Hosseinzadeh Lotfi

Department of Mathematics, Science and Research branch, Islamic Azad University, Tehran, Iran

چکیده

Data envelopment analysis (DEA) is a nonparametric approach to estimate relative efficiency of Decision Making Units (DMUs). DEA is one of the best quantitative approaches and balanced scorecard (BSC) is one of the best qualitative methods to measure efficiency of an organization. Since simultaneous evaluation of network performance of the quad areas of BSC model is considered as a necessity and separate use of DEA and BSC is not effective and leads to miscalculation of performance, integrated DEA-BSC model is applied. Regarding to multi-objective nature of the proposed model, two techniques including goal programming and weighted average method are used to solve such problems. At the end of the study, based on data relating to indexes of quad areas of BSC model, the results of the mentioned methods are compared. Besides assessing validation of the proposed model, the overall efficiency and each of the different stages of BSC are obtained. So that, finding a model for decision making units in various stages of BSC is the innovation of this research study.

کلیدواژه ها

Data envelopment analysis, Balanced Scorecard, Decision Making Units, goal programming, Weighting Objective Function, Multi Objective Programming

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