Published Online:October 2024
Product Name:The IUP Journal of Accounting Research & Audit Practices
Product Type:Article
Product Code:IJARAP201024
Author Name:Rakesh Naik Vadithe and Bikrant Kesari
Availability:YES
Subject/Domain:Finance
Download Format:PDF
Pages:431-454
This paper explores the impact of advanced technologies on the adoption of human resource (HR) analytics in organizations, with a particular focus on the Indian context. Despite the growing importance of HR analytics for data-driven decision making, many organizations struggle to integrate these tools effectively. This paper addresses the problem of understanding how exponential technologies, such as chatbots, big data, machine learning (ML), artificial intelligence (AI), neural fuzzy networks and social media networks, can facilitate HR analytics adoption. Data collected from 669 HR managers were analyzed using partial least squares-structural equation modeling (PLS-SEM) with SmartPLS 4.0 to validate the research model. The findings reveal that these technologies significantly enhance the adoption of HR analytics, offering practical insights for HR practitioners and organizations seeking to leverage digital tools for competitive advantage. The uniqueness of the study lies in its comprehensive examination of the role of exponential technologies in overcoming the barriers to HR analytics adoption, making it a valuable addition to the existing literature.
The application of data-driven methodologies for the evaluation of human resource (HR) management has long been established in the scholarly literature (Marler and Boudreau, 2017). Within the context, HR practices powered by technology use descriptive, visual and statistical analysis of data about HR assets and organizational performance, thereby substantiating their impact on business operations and prompting a culture of data-informed decision making (Marler and Boudreau, 2017; and Margherita, 2022).