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

Author

Listed:
  • Andrea Pontiggia

    (Dept. of Management, Università Ca' Foscari Venice)

  • Giovanni Fasano

    (Dept. of Management, Università Ca' Foscari Venice)

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.

Suggested Citation

  • Andrea Pontiggia & Giovanni Fasano, 2021. "Data Analytics and Machine Learning paradigm to gauge performances combining classification, ranking and sorting for system analysis," Working Papers 05, Department of Management, Università Ca' Foscari Venezia.
  • Handle: RePEc:vnm:wpdman:182
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    References listed on IDEAS

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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Performance Analysis; Data Analytics; Support Vector Machines; Human Resources;
    All these keywords.

    JEL classification:

    • M51 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Firm Employment Decisions; Promotions
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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