<![CDATA[Technical and Vocational Education and Training (TVET) institutions face increasing pressure to enhance performance through strategic resource management, technological innovation, and adaptive capabilities, yet the relative influence of Resource-Based View (RBV), AI-driven institutional agility, and dynamic capabilities on institutional performance remains underexplored. This literature review synthesizes empirical evidence from peer-reviewed studies published between 2015 and 2025 to examine the influence of X1 (RBV), X2 (AI-driven institutional agility), and X3 (dynamic capability) on Y (TVET performance). A systematic search was conducted across academic databases including Google Scholar, ERIC, and institutional repositories, yielding studies that employed quantitative, quasi-experimental, and case study methodologies in TVET contexts. Results indicate that RBV (X1) demonstrates an indirect and mixed influence on TVET performance, functioning primarily as a theoretical foundation where resources must be converted into capabilities to affect outcomes. AI-driven institutional agility (X2) exhibits a positive and significant influence on TVET performance (p < 0.001), with empirical evidence showing improvements in student engagement, learning outcomes, and operational efficiency through personalization, task automation, and AI-enabled monitoring. Dynamic capability (X3) demonstrates a positive and significant relationship with TVET performance through sensing, seizing, and reconfiguring mechanisms that enable institutional innovation and competitive advantage. The findings suggest that TVET institutions should prioritize developing dynamic capabilities and integrating AI-driven agile practices over merely accumulating resources, as performance gains emerge through capability transformation and technological innovation rather than resource ownership alone.]]>
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