Design and data analytics of electronic human resource management activities through Internet of Things in an organization

Abstract

SummaryA novel design and data analytics for an electronic human resource management (e‐HRM) system has been proposed in this article. E‐HRM software is being widely used in big industries and institutions. This e‐HRM is very cost‐effective, competence, congruence, and commitment for the organization. At present, Internet of Things (IoT) have great impact on e‐HRM, which gives various facilities and supports to e‐HRM functionalities such as securities, standards, privacy, and regulations. The combination of e‐HRM with IoT has wide applications for implementing policies, strategies, and practices within the organization. An e‐HRM has mainly five activities: e‐Selection, e‐Recruitment, e‐Performance, e‐Compensation, and e‐Learning. In this work, the proposed system has two parts. In the first part, the various e‐HRM activities have been discussed and elaborated with examples. In the second part, the description of data analytics based on IoT for each e‐HRM activity has been discussed and demonstrated. Here the data analytics part is divided into four components: (a) data preprocessing; (b) feature selection; (c) data classification; and (d) performance evaluation. Extensive experimentation has been performed for each e‐HRM activity using four HR analytic datasets from Kaggle site, and finally, the performance with proper justifications has been exquisitely done using each dataset respect to each e‐HRM activity.