Finding a Common Weight Vector of Data Envelopment Analysis Based upon Bargaining Game
Finding a Common Weight Vector of Data Envelopment Analysis Based upon Bargaining Game
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DOI：
10.11114/set.v1i1.277
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发表时间：
2013-11
期刊：
影响因子：
--
通讯作者：
Manabu Sugiyama;T. Sueyoshi
中科院分区：
文献类型：
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作者：
Manabu Sugiyama;T. Sueyoshi
数据包络分析（DEA）是一种通过评价决策单元（dmu）的产出和投入来衡量其相对效率的数学规划方法。在DEA的历史上，第j个DMU的交叉效率作为对给定DMU的效率度量被研究者广泛使用。该方法总是在评估中使用与输入和输出相关的权重。不幸的是，在交叉效率度量中，权重并不总是唯一确定的，因为DEA总是存在多个解，因此表明存在多个权重。为了克服这一困难，本文提出了一种基于议价博弈的DEA公共权向量确定方法。
Data Envelopment Analysis (DEA) is a mathematical programming method for measuring the relative efficiency of Decision Making Units (DMUs) by evaluating their outputs and inputs. In the history of DEA, the cross-efficiency of j th DMU is widely used as an efficiency measure of a given DMU o among researchers. The approach always utilizes weights related to inputs and outputs in the assessment. Unfortunately, the weights are not always uniquely determined in the cross-efficiency measurement because DEA always suffers from an occurrence of multiple solutions, so indicating an occurrence of multiple weights. To overcome such a difficulty, this paper proposes a new approach for determining a common weight vector of DEA based on bargaining game.