Abstract
PurposeThe purpose of this study is to explore the negative consequences of human resource analytics applications using the privacy calculus approach.Design/methodology/approachBy using the existing literature and privacy calculus theory, a theoretical model has been developed. This model helps to examine the benefits and risks associated with HR analytics applications. The theoretical model was validated using the partial least square structural equation modeling (PLS-SEM) technique with 315 respondents from different organizations.FindingsHR analytics provides multiple benefits to employees and organizations. But employee privacy may be compromised due to unauthorized access to employee data. There are also security concerns about the uncontrolled use of these applications. Tracking employees without their consent increases the risk. The study suggests that appropriate regulation is necessary for using HR analytics.Research limitations/implicationsThis study is based on cross-sectional data from a specific region. A longitudinal study would have provided more comprehensive results. This study considers five predictors, including other boundary conditions that could enhance the model’s explanative power. Also, data from other countries could improve the proposed model.Practical implicationsThe proposed model is useful for HR practitioners and other policymakers in organizations. Appropriate regulations are important for HR analytics applications. The study also highlights various employee privacy and security-related issues emerging from HR analytics applications. The study also discusses the role of leadership support for the appropriate usage of HR analytics.Originality/valueOnly a few research studies have explored the issues of HR analytics and its consequences. The proposed theoretical model is the first to consider the negative consequence of HR analytics through privacy calculus theory. In this perspective, the research is considered to be novel.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.