This study uses the Principal Component Analysis (PCA) approach and factor analysis to analyse the factors driving competitiveness revealed in the ASEAN region. The data included 150 observations from 10 ASEAN countries with 9 indicators grouped into 4 main factors. The results of the PCA show that three indicators of competitiveness (GDP per Capita, labour productivity, and export value) can be reduced to one primary dimension that explains 93.20% of the total variance. Factor analysis identified four driving factors: Human Capital Development (HCD) with an eigenvalue of 2,577 (28.63%), Human Capital in Higher Education (HCH) with an eigenvalue of 1,893 (21.03%), Research and Technology Development (RTD) with an eigenvalue of 1,234 (13.71%), and Social Capital Unemployment (SCU) with an eigenvalue of 1,013 (11.26%). The results of multiple linear regression showed that all factors with a significant effect on competitiveness were revealed (R² = 0.9897) with HCD having the most critical influence (β = 0.8156), followed by RTD (β = 0.6823), HCH (β = 0.4789), and SCU (β = 0.2456). The cluster analysis reveals that the development is polarised in the ASEAN region, with Singapore and Brunei Darussalam showing superior performance, while Cambodia and Myanmar face significant structural challenges.
Surti Surti (Tue,) studied this question.