Mixed-methods evaluation demonstrates enhanced operational efficiency across universities, suggesting scalable frameworks for institutional digital transformation.
Addressing challenges in higher education management during digital transformation, including insufficient process coordination, underutilized data value, imprecise service delivery, and inadequate integration of technology and operations, this study investigates pathway optimization strategies for improving management efficiency. In the context of increasingly complex digital information environments and intelligent data transmission systems, efficient management architectures provide methodological insights for large-scale information processing and integrated sensing frameworks associated with advanced electromagnetic and communication applications. Drawing upon collaborative governance theory, data governance theory, and an extended Technology Acceptance Model, the study first analyzes the essential characteristics and evaluation dimensions of digital transformation in higher education management. Subsequently, questionnaires, in-depth interviews, and case studies are employed to identify key bottlenecks in organizational structure, data application, service models, and technological support. Based on these findings, a four-dimensional collaborative optimization framework is established, integrating organizational collaboration, data-driven empowerment, service innovation, and technological ecosystem construction. Practical validation across representative universities demonstrates that the proposed framework significantly improves crossdepartmental collaboration, data utilization, service quality, and management efficiency. The proposed methodology provides a systematic reference for intelligent information management and multimodal data coordination, with potential implications for complex electromagnetic information processing and digital infrastructure optimization.
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Xu et al. (2026) studied this question.
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