The role of HR analytics in driving organizational agility and operational performance: evidence from the construction sector
Purpose This study examines the impact of human resource information systems (HRIS) and human resource big data (HRBD) on HR analytics, organizational agility (OA), and operational performance (OP) in India’s construction sector. Furthermore, the study explores the mediating role of HR analytics in these relationships, highlighting its significance in leveraging HR technology for enhanced organizational outcomes. Design/methodology/approach Data were collected from 330 HR managers in the Indian construction industry, and the proposed model was analyzed using partial least squares structural equation modeling (PLS-SEM) using SmartPLS 4.0. Findings The findings reveal that HRIS and HRBD positive influence on HR analytics, which, in turn, positively influences OA and OP. Moreover, HR analytics acts as a partial mediator, underscoring its crucial role in optimizing HR technology for improved agility and performance. Practical implications From a practical perspective, the study recommends that organizations invest in advanced HRIS and HRBD tools to strengthen HR analytics capabilities, thereby improving workforce management, operational efficiency, and market responsiveness. Originality/value The novelty of this research lies in its focus on the Indian construction sector, providing empirical evidence of the mediating role of HR analytics. By establishing a framework linking HR technology to organizational outcomes, this study contributes to the existing body of knowledge on HR analytics and its strategic implications.
Authors
- Nenavath Sreenu (ORCID: https://orcid.org/0000-0002-8535-1293)
- Bikrant Kesari (ORCID: https://orcid.org/0000-0003-3363-3421)
- Rakesh Naik Vadithe
- Rubvita Chadha Rajput
- Velagapalli Chiranjeevi
- Chinna Brahmaiah Naik Mudavath
Publication Details
- Journal
- Engineering Construction & Architectural Management
- Published
- 2025-05-06
- DOI
- https://doi.org/10.1108/ecam-01-2025-0076
- Citations
- 4
- Primary Topic
- AI and HR Technologies
- Type
- article
- Field-Weighted Citation Impact
- 11.05