書目名稱 | Data-Enabled Analytics |
副標題 | DEA for Big Data |
編輯 | Joe Zhu,Vincent Charles |
視頻video | http://file.papertrans.cn/264/263324/263324.mp4 |
概述 | Explores novel uses of Data Envelopment Analysis and Big Data.Introduces DEA as a data mining tool, under the big data umbrella.Exams DEA models beyond their present scope and mine new insights for be |
叢書名稱 | International Series in Operations Research & Management Science |
圖書封面 |  |
描述 | This book explores the novel uses and potentials of Data Envelopment Analysis (DEA) under big data. These areas are of widespread interest to researchers and practitioners alike. Considering the vast literature on DEA, one could say that DEA has been and continues to be, a widely used technique both in performance and productivity measurement, having covered a plethora of challenges and debates within the modelling framework. |
出版日期 | Book 2021 |
關(guān)鍵詞 | efficiency; big data; best-practice; data envelopment analysis; data-enabled analytics; data science; fore |
版次 | 1 |
doi | https://doi.org/10.1007/978-3-030-75162-3 |
isbn_softcover | 978-3-030-75164-7 |
isbn_ebook | 978-3-030-75162-3Series ISSN 0884-8289 Series E-ISSN 2214-7934 |
issn_series | 0884-8289 |
copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |