<![CDATA[Purpose – Indonesian retail investing has grown sharply (KSEI, 2025), yet research centers on financial literacy, leaving intuitive judgment unmeasured. This paper proposes Intuitive Cognitive Competence (ICC), a latent construct capturing experience integration, pattern recognition, and adaptive execution, and demonstrates its scale-development protocol via simulation. Design/methodology/approach – Fifteen items across three dimensions were tested on two independent synthetic samples (exploratory N = 50; confirmatory N = 200) from a fully specified population model, avoiding same-sample circularity. Retention used minimum-residual EFA with Promax rotation, cross-checked against parallel analysis, Velicer's MAP, and a Monte Carlo recovery check. Finding/Results – EFA recovered the three-factor structure (KMO = 0.895; common variance = 59.4%); parallel analysis was more conservative than MAP and the eigenvalue rule at N = 50 (4.3% vs. 83.0-92.0% correct recovery). One item was removed for low communality. The refined 14-item model outperformed a one-factor alternative (CFI = 0.759 vs. ≈1.00; RMSEA = 0.155 vs. 0.000), with strong convergent (AVE = 0.58-0.65) and discriminant validity (Fornell-Larcker; HTMT < 0.71). A second-order model showed equivalent fit. Originality/Value – This demonstration offers a fully specified item pool, documented data-generating process, and rigorous EFA-CFA protocol, ready for field-data redeployment toward a validated ICC model.]]>
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