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The quality of work in public universities with no-parametric statistical models

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  • Benedetto Torrisi

Abstract

The existing studies investigating well-being in public universities indicate that there are unresolved issues: how does one measure the quality of work and the quality of the organisation in the university sector? What is the quality of life for Italian researchers in the workplace? What information can provide results in terms of suggesting new governance structures? The aim of this study is to answer these questions using a sample survey and the results obtained from the PIR 2012 project, “Productivity of Italian Researchers”. The information is obtained from micro data at a highly specific level and represents a first step toward an in-depth examination of an issue that is related more to theory than to empirical analysis. This objective was achieved through multivariate statistical models that determine the relationship between the quality of work, the quality of the organisation and governance policies. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Benedetto Torrisi, 2015. "The quality of work in public universities with no-parametric statistical models," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(1), pages 349-363, January.
  • Handle: RePEc:spr:qualqt:v:49:y:2015:i:1:p:349-363
    DOI: 10.1007/s11135-014-9990-1
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    Citations

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    Cited by:

    1. Sharifah Rahama Amirul & Khairul Hanim Pazim & Sharifah Milda Amirul & Rasid Mail & Jakaria Dasan, 2022. "Developing and validating the qualitative labour productivity measurement in service industry," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(4), pages 2853-2874, August.
    2. Benedetto Torrisi & Giuseppe Pernagallo, 2022. "The Relationship Between Academic Well-Being and Territoriality in Italy," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 161(2), pages 413-431, June.
    3. Prem Kumar Singh, 2023. "Research impact analysis of an institute using Scopus data and its hierarchical order visualization," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2859-2892, June.

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