分析
计算机科学
数据科学
独创性
结构方程建模
数据分析
商业分析
知识管理
业务
商业模式
心理学
数据挖掘
营销
业务分析
创造力
社会心理学
机器学习
作者
Sheshadri Chatterjee,Ranjan Chaudhuri,Demetris Vrontis,Evangelia Siachou
标识
DOI:10.1108/ijm-02-2021-0087
摘要
Purpose The purpose of this study is to explore the negative consequences of human resource analytics applications using the privacy calculus approach. Design/methodology/approach By 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. Findings HR 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/implications This 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 implications The 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/value Only 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.
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