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Measuring and monitoring diversity in organizations through functional instruments with an application to ethnic workforce diversity of the U.S. Federal Agencies

Author

Listed:
  • Fabrizio Maturo

    (“G. d’Annunzio” University of Chieti-Pescara)

  • Stefania Migliori

    (“G. d’Annunzio” University of Chieti-Pescara)

  • Francesco Paolone

    (University of Naples)

Abstract

The role of diversity in organizations has been widely discussed in recent decades; nevertheless, both theoretical perspectives and empirical results appear conflicting and inconsistent. Scholars identify many possible reasons such as the definition of diversity, theoretical perspectives, variables, and methodological approaches; this study focuses on the methodological issue of assessing variety. To evaluate the role of diversity, most studies adopt static approaches and refer to the classical univariate indices; this research shows their limitations and stresses the importance of treating diversity with a multivariate dynamic approach. Taking advantage of functional data analysis and some recent ecological studies, this dual gap of the organizational literature is addressed by proposing a new methodological approach for measuring and monitoring diversity in organizations. We illustrate an application of this method by using a real dataset concerning the workforce diversity of the “Corporation For National And Community Service Overview” within the project “Federal Equal Opportunity Recruitment Program (FEORP)” of the Government of the United States of America. The goal of this research is to provide human resources specialists, policy makers, and scholars with additional techniques to improve the understanding of the dynamics of workforce diversity and minority employment within organizations.

Suggested Citation

  • Fabrizio Maturo & Stefania Migliori & Francesco Paolone, 2019. "Measuring and monitoring diversity in organizations through functional instruments with an application to ethnic workforce diversity of the U.S. Federal Agencies," Computational and Mathematical Organization Theory, Springer, vol. 25(4), pages 357-388, December.
  • Handle: RePEc:spr:comaot:v:25:y:2019:i:4:d:10.1007_s10588-018-9267-7
    DOI: 10.1007/s10588-018-9267-7
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    References listed on IDEAS

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