Exploring the Nexus Between Digitalized Human Resource Management and Employee Productivity

The digital transformation of Human Resource Management (HRM) is critical for enhancing organizational performance, yet the specific mechanisms linking digital HR practices to employee productivity remain underexplored. This study aims to identify the critical factors of digitalized HR practices and model their complex interrelationships with employee productivity factors. This study employs a two-phase modeling approach: Interpretive Structural Modeling (ISM) and Total Interpretive Structural Modeling (TISM), integrated with Fuzzy MICMAC analysis. Data were collected from a panel of 10 industry and academic experts in the Pakistani pharmaceutical sector. Through a structured literature review and expert validation, 15 critical factors (10 digital HR practices and five employee productivity factors) were identified and used to develop hierarchical models and analyze their driving and dependence power. The TISM model reveals a seven-level hierarchical structure. Key findings indicate that technological infrastructure factors, such as HR Information Systems (HRIS) and Cloud Computing, act as the most fundamental drivers. These enable HR Analytics and Big Data & AI, which in turn influence transactional practices, such as e-recruitment. The Fuzzy MICMAC analysis classifies these as independent factors with high driving power, directly influencing dependent productivity factors, including employee engagement, output quality, and psychological well-being. This research presents a novel, validated model that elucidates how digital HR investments translate into tangible productivity gains. It contributes to theory by empirically validating and extending the Information Systems theory in an HRM context. For practitioners, it offers a strategic roadmap for pharmaceutical managers, prioritizing investments in foundational digital technologies to maximize employee productivity and achieve sustainable competitive advantage.