Abstract: The increasing demand for ethical governance, employee well-being, and sustainable organizational performance has highlighted significant gaps in conventional Human Resource Management (HRM) models, which are largely efficiency-oriented and grounded in Western managerial paradigms. Addressing this limitation, the present study develops a conceptual model by synthesizing Indian Knowledge Systems (IKS) with contemporary HRM practices to create a holistic and value-driven framework for organizational management. Rooted in classical Indian philosophical principles such as Dharma (ethical duty), Karma (action and consequence), Yoga (self-discipline and mental regulation), and Nishkama Karma (selfless action), the study reinterprets core HR functions including recruitment, training and development, performance management, leadership, and employee engagement.

Adopting a conceptual and integrative research design, the paper draws upon insights from ancient Indian texts alongside modern theoretical perspectives such as the Resource-Based View (RBV), Positive Organizational Behavior (POB), and Ethical Leadership Theory. The proposed framework suggests that Dharma fosters an ethical organizational climate, Karma strengthens accountability and performance orientation, Yoga enhances employee well-being and resilience, and Nishkama Karma promotes intrinsic motivation and commitment. Collectively, these dimensions contribute to aligning individual values with organizational objectives, thereby facilitating sustainable and responsible business practices.

The study offers significant theoretical contributions by bridging indigenous knowledge traditions with contemporary HRM discourse, providing a culturally enriched alternative to dominant management models. From a managerial perspective, the framework highlights the importance of integrating ethical values, mindfulness practices, and holistic development initiatives into HR strategies. Although conceptual in nature, the model lays a strong foundation for future empirical research using advanced analytical techniques such as Structural Equation Modeling (SEM) to validate the proposed relationships.

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