Digital Human Resource Management Adoption in Higher Education: An Integrated TAM, TPB and Diffusion of Innovation Framework

Abstract

Digital transformation has moved Human Resource Management (HRM) from largely administrative record keeping toward technology-enabled recruitment, performance management, learning, analytics and strategic workforce decision-making. Higher education institutions are an important setting for this transformation because they manage knowledge-intensive workforces while operating through complex professional and administrative structures. Yet explanations of Digital Human Resource Management (DHRM) adoption remain theoretically fragmented. This paper develops an integrated theoretical account by bringing together the Technology Acceptance Model (TAM), Theory of Reasoned Action (TRA), Theory of Planned Behavior (TPB), and Diffusion of Innovation (DOI) theory. A structured integrative literature review was used to synthesize theoretical and contextual evidence, with particular attention to higher education and the Indian context. The synthesis indicates that TAM explains how perceived usefulness and perceived ease of use shape individual acceptance; TRA explains the influence of social expectations; TPB adds perceived behavioral control and therefore accounts for capability and contextual constraints; and DOI explains how an innovation moves from individual acceptance toward institutional diffusion. The paper argues that these theories should not be treated as competing explanations. Instead, they can be positioned as complementary layers within a micro–meso–macro framework. The resulting framework identifies technological characteristics, organizational readiness, leadership, digital literacy, infrastructure and resistance to change as important boundary conditions. The paper concludes that successful DHRM transformation in higher education depends on the alignment of technology perceptions, employee capability, social support and institutional innovation readiness. The framework offers a basis for future empirical research without claiming new primary-data evidence..