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Big Data and Employee Wellbeing: Walking the Tightrope between Utopia and Dystopia

Author

Listed:
  • Carolyn Axtell

    (Institute of Work Psychology, Sheffield University Management School, Sheffield S10 1FL, UK)

  • Mark Taylor

    (Melbourne Law School, University of Melbourne, Parkville, VIC 3010, Australia)

  • Bridgette Wessels

    (School of Social & Political Sciences, University of Glasgow, Glasgow G12 8RS, UK)

Abstract

This special issue was inspired by an Economic & Social Research Council funded seminar series that explored the possibilities for using Big Data and data analytics for assessing health and wellbeing risks within organisations. The aim of this special issue was to build on some of the themes developed in the seminar series and draw together and update some key insights from different disciplinary perspectives on the opportunities, challenges and lessons that could be applied in this area. This editorial, therefore, draws together the findings and themes from the submitted papers and interprets these in light of the findings from the seminar series.

Suggested Citation

  • Carolyn Axtell & Mark Taylor & Bridgette Wessels, 2019. "Big Data and Employee Wellbeing: Walking the Tightrope between Utopia and Dystopia," Social Sciences, MDPI, vol. 8(12), pages 1-5, November.
    • Handle: RePEc:gam:jscscx:v:8:y:2019:i:12:p:321-:d:289721
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    References listed on IDEAS

    as
    1. Adam M. Kleinbaum & Toby E. Stuart & Michael L. Tushman, 2013. "Discretion Within Constraint: Homophily and Structure in a Formal Organization," Organization Science, INFORMS, vol. 24(5), pages 1316-1336, October.
    2. Manuela Nocker & Vania Sena, 2019. "Big Data and Human Resources Management: The Rise of Talent Analytics," Social Sciences, MDPI, vol. 8(10), pages 1-19, September.
    3. Thomas Calvard, 2019. "Integrating Social Scientific Perspectives on the Quantified Employee Self," Social Sciences, MDPI, vol. 8(9), pages 1-19, September.
    4. Mark J. Taylor & Megan Prictor, 2019. "Insight or Intrusion? Correlating Routinely Collected Employee Data with Health Risk," Social Sciences, MDPI, vol. 8(10), pages 1-19, October.
    Full references (including those not matched with items on IDEAS)

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