Special Issue "Big Data and Employee Wellbeing"
A special issue of Social Sciences (ISSN 2076-0760).
Deadline for manuscript submissions: 30 June 2019
Organisations are starting to use Big Data and data analytics to examine employee health and wellbeing (e.g., through the use of fitness tracking technology) with the aim of improving the health and wellbeing of their workforce. There are also vast amounts of digitally captured data gathered within organisations (e.g., network traffic, log-in/off data) that are currently under-utilized but could be used to indicate areas of highly intensive workload where wellbeing risks might occur. While there could be very positive effects of using data to proactively assess and intervene where health and wellbeing risks are highlighted, there are also several challenges—not only in terms of the technical difficulties of handling this data, but also concerns about the reliability/validity of the data, what decisions or actions will be taken as a result of the analysis, and issues relating to data protection, trust, and consent. The complexity of these issues means that a critical multi-disciplinary perspective is required to understand this area better. This Special Issue therefore seeks to draw together theoretical, methodological, and empirical papers from different disciplinary perspectives that examine some of the opportunities, challenges, and lessons learned from other contexts that inform our understanding of using Big Data/data analytics to examine wellbeing within organisations.
This Special Issue was stimulated by an inter-disciplinary ESRC-funded seminar series on the topic of Data and Employee Wellbeing (www.dew.group.shef.ac.uk).
Dr. Carolyn Axtell
Prof. Bridgette Wessels
Dr. Christine Sprigg
Dr. Mark J Taylor
Manuscript Submission Information
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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a double-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Social Sciences is an international peer-reviewed open access monthly journal published by MDPI.
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- Big Data
- Data Analytics
- Employee Wellbeing
- Assessment of Wellbeing
- Wellbeing Intervention
- Digital Sociology
- Data Protection