Hee Seok Song, Shaneth A. Estrada, Young Ae Kim, Su Hyeon Namn, Shin Cheol Kang
언어
영어(ENG)
URL
https://www.earticle.net/Article/A98010
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4,000원
원문정보
초록
영어
In DEA, it is difficult for inefficient DMUs to be efficient by benchmarking a target DMU which has different input use. Identifying appropriate benchmarks based on the similarity of input endowment makes it easier for an inefficient DMU to imitate its target DMUs. But it is rare to find out a target DMU, which is both the most efficient and similar in input endowments, in real situation. Therefore, it is necessary to provide an optimal path to the most efficient DMU on the frontier through several times of a proximity-based target selection process. We propose a dynamic method of stepwise benchmarking for inefficient DMUs to improve their efficiency gradually. The empirical study is conducted to compare the performance between the proposed method and the prior methods with a dataset collected from Canadian Bank branches. The comparison result shows that the proposed method is very practical to obtain a gradual improvement for inefficient DMUs while it assures to reach frontier eventually.
목차
Abstract Introduction Literature review Problem definition Methodology Evaluating efficiency score of DMUs Obtaining neighborhood information amongDMUs Learning an optimal path to the frontier Empirical study Evaluation metric Dataset Determination of a SOM model Determination of parameters Comparison with basic DEA and layer model Relationship between efficiency score improvementand distance of input use Conclusion References
키워드
Data Envelopment Analysis; Self-Organizing Map; Reinforcement Learning; Benchmarking
저자
Hee Seok Song [ Department of Management Information Systems., Hannam University ]
Shaneth A. Estrada [ Department of Management Information Systems., Hannam University ]
Young Ae Kim [ Business School, Korea Advanced Institute of Science and Technology (KAIST) ]
Su Hyeon Namn [ Department of Management Information Systems., Hannam University ]
Shin Cheol Kang [ Department of Management Information Systems., Hannam University ]