SELECTING INPUTS AND OUTPUTS IN DATA ENVELOPMENT ANALYSIS BY DESIGNING STATISTICAL EXPERIMENTS(<Special Issue>Operations Research for Performance Evaluation)
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概要
- 論文の詳細を見る
Data envelopment analysis (DEA) is a data oriented, non-parametric method to evaluate relative efficiency based on pre-selected inputs and outputs. In some cases, the performance model is not well defined, so it is critical to select the appropriate inputs and outputs by other means. When we have many potential variables for evaluation, it is difficult to select inputs and outputs from a large number of possible combinations. We propose an input output selection method that uses diagonal layout experiments, which is a statistical approach to find an optimal combination. We demonstrate the proposed method using financial statement data from NIKKEI 500 index.
著者
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Morita Hiroshi
Osaka University
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Avkiran Necmi
The University of Queensland
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Morita Hiroshi
Osaka Mishima Critical Care Medical Center
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- Preface
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