Keywords
Vocational Education
Administrative in Practice
Data-Based Decision Making
Institutional Competitiveness
How to Cite
Abstract
Purpose: This study conceptualizes Competitive Intelligence (CI) as a strategic capability to support intelligence-based decision-making in higher vocational education administration. It examines the extent to which CI practices enhance decision quality, operational efficiency, and institutional competitiveness, addressing the gap between data use and strategic intelligence in educational management.
Methodology/approach: A mixed-methods design was employed, combining quantitative survey data (n = 75) with qualitative semi-structured interviews (n = 15) involving institutional administrators. Quantitative analysis included descriptive statistics, correlation, and regression models, while qualitative data were analyzed through thematic coding to capture decision-making dynamics and contextual insights.
Originality/Relevance: The study advances CI research by extending its application to vocational education administration and by reframing CI as a decision-support capability rather than a purely informational process. It contributes to bridging the gap between data analytics and strategic intelligence use in institutional governance.
Key findings: CI practices—particularly environmental scanning and data-driven decision-making—demonstrate strong positive effects on decision quality (r = 0.85) and competitiveness (r = 0.78). Regression results confirm CI as a significant predictor of decision effectiveness (β = 0.62), operational efficiency (β = 0.48), and competitiveness (β = 0.55). However, strategic intelligence functions such as competitor analysis and forecasting remain underutilized.
Theoretical/methodological contributions: The study positions CI as a dynamic capability embedded in decision processes and proposes a framework linking intelligence practices to data-driven governance and sustainable competitive performance.
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