Data Analytics and Machine Learning paradigm to gauge performances combining classification, ranking and sorting for system analysis

Andrea Pontiggia () and Giovanni Fasano ()
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Andrea Pontiggia: Dept. of Management, Università Ca' Foscari Venice
Giovanni Fasano: Dept. of Management, Università Ca' Foscari Venice

No 5, Working Papers from Venice School of Management - Department of Management, Università Ca' Foscari Venezia

Abstract: We consider the problem of measuring the performances associated with members of a given group of homogeneous individuals. We provide both an analysis, relying on Machine Learning paradigms, along with a numerical experience based on three conceptually different real applications. A keynote aspect in the proposed approach is represented by our data–driven framework, where guidelines for evaluating individuals’ performance are derived from the data associated to the entire group. This makes our analysis and the relative outcomes quite versatile, so that a number of real problems can be studied in view of the proposed general perspective.

Keywords: Performance Analysis; Data Analytics; Support Vector Machines; Human Resources (search for similar items in EconPapers)
JEL-codes: C38 M51 (search for similar items in EconPapers)
Pages: 46 pages
Date: 2021-07
New Economics Papers: this item is included in nep-big, nep-cmp and nep-ore
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Persistent link: https://EconPapers.repec.org/RePEc:vnm:wpdman:182

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