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Sequential benchmarking to achieve the closest cross-sectional targets in DEA
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چکیده: (724 مشاهده) |
| The models that set the closest targets have made an important contribution to data envelopment analysis (DEA) as tool for best-practice benchmarking of decision making units (DMUs). These models may help define plans for improving the require less effort from the DMUs. One of the important issues in the process of benchmarking and target setting, is to set realistic and achievable targets for inefficient units. Because in practice and in the real world, we often face units that perform poorly and the targets for them are not available in one step, to solve this problem, in this study, an algorithm is presented that takes advantage of the onion layering method has three main advantages over other step-by-step benchmarking methods: firstly, in each step, it offers a better and closer target and benchmark to the manager sequentially. Secondly, by adjusting the number of jumps in the layers according to the conditions, it provides the possibility of more adjustments and flexibility in targets for the manager. Thirdly, by classifying the decision-making units based on the level of efficiency and performance, it specifies a benchmark and a realistic achievable target for the inefficient units at each stage. The proposed method has been implemented on the data of 24 Portuguese bank branches and And targets are specified sequentially for each ineffective unit. |
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متن کامل [PDF 628 kb]
(498 دریافت)
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نوع مطالعه: پژوهشي |
موضوع مقاله:
عمومى
دریافت: 1401/10/20 | پذیرش: 1402/4/5
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