Enhancing Digital Transformation and Green HRM through Human-AI Collaboration: A Supply Chain-Inspired Framework for Institutional Quality Support in Community Colleges of Bagmati Province, Nepal
DOI:
https://doi.org/10.3126/nprcjmr.v2i7.80610Keywords:
Digital transformation, Green HRM, Human–AI collaboration, Supply chain management, Higher education; Quality assurance; NepalAbstract
This study explores how human–AI collaboration moderates the relationship between digital transformation and Green Human Resource Management (Green HRM) within Nepal’s community colleges. Bridging digital and green HRM frameworks, it introduces a supply chain–inspired lens to examine service delivery and sustainability in public higher education. Guided by Resource-Based View (RBV) and Socio-Technical Systems Theory, the research applies a mixed-methods design combining Structural Equation Modeling (SEM) with fuzzy-set Qualitative Comparative Analysis (fsQCA) on data from 285 staff members across five Tribhuvan University–affiliated community colleges in Bagmati Province.SEM results confirm that digital transformation significantly enhances Green HRM (β = 0.48, p < 0.001), and this relationship is strengthened by effective human–AI collaboration (interaction β = 0.25, p < 0.001). fsQCA identifies two equifinal pathways to high Green HRM: (1) Tech + AI Synergy (high digitalization and high human–AI collaboration), and (2) Tech-Driven Path (high digitalization alone). These findings reveal that while AI augmentation enhances green outcomes, foundational digital infrastructure alone can also yield substantial sustainability gains. Theoretically, this is one of the first empirical studies to integrate digital transformation, Green HRM, and human–AI collaboration within a developing country education system, extending supply chain models from corporate to academic contexts. Practically, it provides actionable insights for Internal Quality Assurance Cells (IQACs) to align digital and green agendas and suggests that policy bodies like UGC and MoEST should embed AI-readiness and sustainability metrics into accreditation frameworks. The study underscores the importance of socio-technical alignment in enabling sustainable, tech-enabled institutional quality in Nepal’s higher education landscape.
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