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Titlebook: Quantitative Models for Performance Evaluation and Benchmarking; Data Envelopment Ana Joe Zhu Book 20031st edition Springer-Verlag US 2003

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发表于 2025-3-21 17:20:51 | 显示全部楼层 |阅读模式
书目名称Quantitative Models for Performance Evaluation and Benchmarking
副标题Data Envelopment Ana
编辑Joe Zhu
视频video
丛书名称International Series in Operations Research & Management Science
图书封面Titlebook: Quantitative Models for Performance Evaluation and Benchmarking; Data Envelopment Ana Joe Zhu Book 20031st edition Springer-Verlag US 2003
描述Managers are often under great pressure to improve the performance of their organizations. To improve performance, one needs to constantly evaluate operations or processes related to producing products, providing services, and marketing and selling products. Performance evaluation and benchmarking are a widely used method to identify and adopt best practices as a means to improve performance and increase productivity, and are particularly valuable when no objective or engineered standard is available to define efficient and effective performance. For this reason, benchmarking is often used in managing service operations, because service standards (benchmarks) are more difficult to define than manufacturing standards. Benchmarks can be established but they are somewhat limited as they work with single measurements one at a time. It is difficult to evaluate an organization‘s performance when there are multiple inputs and outputs to the system. The difficulties are further enhanced when the relationships between the inputs and the outputs are complex and involve unknown tradeoffs. It is critical to show benchmarks where multiple measurements exist. The current book introduces the meth
出版日期Book 20031st edition
关键词DEA (data envelopment analysis); Data Envelopment Analysis; Data-Envelopment-Analysis; benchmarking; cal
版次1
doihttps://doi.org/10.1007/978-1-4757-4246-6
isbn_ebook978-1-4757-4246-6Series ISSN 0884-8289 Series E-ISSN 2214-7934
issn_series 0884-8289
copyrightSpringer-Verlag US 2003
The information of publication is updating

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发表于 2025-3-21 22:00:14 | 显示全部楼层
https://doi.org/10.1007/978-1-4757-4246-6DEA (data envelopment analysis); Data Envelopment Analysis; Data-Envelopment-Analysis; benchmarking; cal
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Measure-specific DEA Models,al improvements of inputs or outputs. This assumption becomes invalid when a preference structure over the improvement of different inputs (outputs) is present in evaluating (inefficient) DMUs (see Chapter 4). We need models where a particular set of performance measures is given pre-emptive priority to improve.
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Modeling Undesirable Measures, One wants to reduce the number of defects to improve the performance. If inefficiency exists in production processes where final products are manufactured with a production of wastes and pollutants, the outputs of wastes and pollutants are undesirable and should be reduced to improve the performance.
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Congestion,n be found in underground mining and agriculture. For example, too much fertilizer applied to a given plot could reduce the overall output. We here adopt the following definition of congestion from Cooper, Thompson and Thrall (1996).
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Quantitative Models for Performance Evaluation and Benchmarking978-1-4757-4246-6Series ISSN 0884-8289 Series E-ISSN 2214-7934
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