TUNING REGRESSION RESULTS FOR USE IN MULTI-STAGE DATA ADJUSTMENT APPROACH OF DEA(<Special Issue>Operations Research for Performance Evaluation)
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- Tone Kaoru
- National Graduate Institute for Policy Studies
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- Tsutsui Miki
- Central Research Institute of Electric Power Industry
書誌事項
- タイトル別名
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- Tuning regression results for use in multi-stage data adjustment approach of DEA
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説明
Data envelopment analysis (DEA) has been a wildly used powerful method to measure efficiencies of decision making units (DMUs). However, DEA efficiency scores are influenced by uncontrollable factors for respective DMUs. Previous studies attempted separating such factors from DEA scores. Fried et al. [4] proposed a multi-stage data adjustment approach using DEA and a regression model, and several studies have followed it, such as Fried et al. [5], Avkiran and Rowlands [1], and so forth. Firstly, we point out shortcomings of the traditional adjustment scheme for combining regression results for use in DEA in the multi-stage approach, and then we propose a new scheme for data adjustment. We demonstrate the effect of this adjustment formula using an electric utility dataset.
収録刊行物
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- 日本オペレーションズ・リサーチ学会論文誌
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日本オペレーションズ・リサーチ学会論文誌 52 (2), 76-85, 2009
公益社団法人 日本オペレーションズ・リサーチ学会
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詳細情報 詳細情報について
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- CRID
- 1390282679085851904
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- NII論文ID
- 110007330944
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- NII書誌ID
- AA00703935
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- ISSN
- 21888299
- 04534514
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- NDL書誌ID
- 10250189
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- 本文言語コード
- en
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- データソース種別
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- JaLC
- IRDB
- NDL
- Crossref
- CiNii Articles
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- 使用不可