Title: Exploring the impact of human resource analytics on employee engagement using neural networks in the public sector in India

Authors: Kamakshi Mehta; Srinivas Kolachina; Sudha Mavuri; Ajith Kumar Vadakki Veetil; Jayashree Patil; Jithesh Mon Mullool

Addresses: TAPMI School of Business, Manipal University Jaipur, Jaipur, Rajasthan, India ' Koneru Lakshmaiah Education Foundation, Vaddeswaram, AP, India ' Department of Economics, Skyline University Nigeria, Kano, Nigeria ' Department of Business Administration, Skyline University Nigeria, Kano, Nigeria ' Department of Management Studies, Bharati Vidyapeeth Deemed University, Pune (BVDU), India ' Department of Commerce and Management, Amrita Vishwa Vidyapeetham, Mysuru, Karnataka, India

Abstract: In human resource management, the untapped potential of human resource analytics has remained a challenge, resulting in a notable loss of operational efficiency within the public sector. This project uses artificial intelligence to illuminate human resource statistics topics for stakeholders. Human resource analytics, specifically neural networks, can transform public sector human resource departments. Our study covers manufacturing and public-sector employee engagement. Engagement is key to productivity and organisational success, making it a priority for improvement. We show how human resource analytics, especially when combined with neural networks, can transform the game. Human resource analytics is multidimensional and can be used efficiently in the public sector. Our research shows that public enterprises must use human resource analytics to achieve their goals. When used properly, these analytics factors help achieve public sector goals, boosting staff morale and productivity. In conclusion, this study seeks to connect human resource analytics to public sector employee engagement, a crucial topic. We hope to improve human resource operations and create a more engaged and productive public-sector workforce by using neural networks.

Keywords: human resource management; HRM; human resource operations analytics; artificial intelligence; employee engagement; public sector; digital economy; employing neural networks; India.

DOI: 10.1504/IJEF.2026.150291

International Journal of Electronic Finance, 2026 Vol.15 No.1, pp.107 - 130

Received: 22 Sep 2023
Accepted: 15 Dec 2023
Published online: 08 Dec 2025 *

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