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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Cheng-Chin Lu Ling-ling Kao Chih-Chou Chiu |
| Copyright Year | 2010 |
| Description | Author affiliation: Department of Business Management, National Taipei University of Technology, Taiwan (Ling-ling Kao; Chih-Chou Chiu) || Graduate Institute of Industrial and Business Management, National Taipei University of Technology, Taiwan (Cheng-Chin Lu) |
| Abstract | In this paper, a two-stage approach of integrating spatiotemporal independent component analysis (stICA) and data envelopment analysis (DEA) is developed for efficiency measurement. stICA is used to search for latent source signals where no relevant signal mixture mechanisms are available; and DEA is used to measure the relative efficiencies of decision making units (DMUs). We suggest using stICA first to extract the input variables for generating independent components (IC), then selecting the ICs representing the independent sources of input variables, and finally inputting the selected ICs as new variables in the DEA model. The training institution dataset provided by the Semiconductor Institute in Taiwan is used for analysis. The result shows that the proposed method can not only separate performance differences between the training institutions but also improve the discriminatory capability of the DEA's efficiency measurement. The study results can serve as a reference for training institutions wishing to enhance their training efficiency. |
| Starting Page | 2431 |
| Ending Page | 2434 |
| File Size | 211122 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424485017 |
| ISSN | 2157362X |
| e-ISBN | 9781424485031 |
| e-ISBN | 9781424485024 |
| DOI | 10.1109/IEEM.2010.5674379 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-12-07 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Training Biological system modeling Computational modeling Efficiency measurement Spatiotemporal independent component analysis Data envelopment analysis |
| Content Type | Text |
| Resource Type | Article |
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