Quantitative models for performance evaluation and benchmarking : data envelopment analysis with spreadsheets
著者
書誌事項
Quantitative models for performance evaluation and benchmarking : data envelopment analysis with spreadsheets
(International series in operations research & management science, 126)
Springer, c2009
2nd ed
- : hbk
大学図書館所蔵 全7件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes bibliographical references and indexes
内容説明・目次
内容説明
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 methodology of data envelopment analysis (DEA) and its uses in performance evaluation and benchmarking under the context of multiple performance measures.
目次
Envelopment DEA Models.- Multiplier and Slack-based Models.- Measure-specific DEA Models.- Non-radial DEA Models and DEA with Preference.- Modeling Undesirable Measures.- Context-dependent Data Envelopment Analysis.- Benchmarking Models.- Models for Evaluating Supply Chains.- Congestion.- Super Efficiency.- Sensitivity Analysis.- Identifying Critical Measures in DEA.- Returns-to-Scale.- DEA Models for Two-Stage Processes.
「Nielsen BookData」 より