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

Authors: Nasar, N., Ray, S., Umer, S. and Mohan Pandey, H.

Journal: Software - Practice and Experience

Volume: 51

Issue: 12

Pages: 2411-2427

eISSN: 1097-024X

ISSN: 0038-0644

DOI: 10.1002/spe.2817

Abstract:

A 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.

Source: Scopus