Titlebook: Data-Enabled Analytics; DEA for Big Data Joe Zhu,Vincent Charles Book 2021 The Editor(s) (if applicable) and The Author(s), under exclusive

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書目名稱Data-Enabled Analytics影響因子(影響力)




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書目名稱Data-Enabled Analytics網(wǎng)絡(luò)公開度學(xué)科排名




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Book 2021ers 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.

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0884-8289 A 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.978-3-030-75164-7978-3-030-75162-3Series ISSN 0884-8289 Series E-ISSN 2214-7934

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Magda Pischetola,Lone Dirckinck-Holmfeldractice. The network paradigm provides a versatile and efficient modelling framework that allows computing a wide array of quantitative characterization measures as well as powerful visualization capabilities. The methodology is illustrated with data on how the COVID-19 pandemic has affected the different countries.

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Network DEA and Big Data with an Application to the Coronavirus Pandemic,rable and undesirable outputs, and the reallocation of inputs, across time, to optimize production. An example of the use of NDEA is offered for the Covid Pandemic in the US. We find that an optimal reallocation of tests for Covid could have averted 10,800 deaths.

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Hierarchical Data Envelopment Analysis for Classification of High-Dimensional Data,d security attributes. Furthermore, the findings can be used to assist countries in projecting learning path from other high-performing nations. Such path information doesn’t exist when country grouping is carried out using personal judgement thus reduces subjectivity in measuring multiple food security performance attributes.