Nor Aprina Hadiani
Lambung Mangkurat University

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Boosting Risk Management Performance through Human Capital Capacity, Managerial Commitment, and Effective Implementation Processes Nor Aprina Hadiani; Abdurrahman Sadikin; Mahdi Hidayatullah
Ilomata International Journal of Management Vol. 7 No. 3 (2026): July 2026
Publisher : Yayasan Sinergi Kawula Muda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61194/ijjm.v7i3.2301

Abstract

Risk management in utility infrastructure depends on two behavioral foundations: technical competence of operational staff and strategic commitment of leaders. This study examines how human capital capacity and managerial commitment are associated with risk management implementation process, risk management effectiveness, and risk management performance at PT PLN (Persero) UIP3B Kalimantan. Prior studies emphasize technical risk frameworks, yet limited attention has been given to how organizational behavior and leadership commitment relate to implementation quality and perceived performance outcomes in state-owned utility settings. Data were collected through a census survey of 170 technical personnel directly involved in risk management activities, complemented by assessments from 12 supervisory performance raters. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to examine the hypothesized structural relationships. Results indicate that managerial commitment shows the strongest association with implementation quality, while human capital capacity shows a smaller but significant association. Implementation process and risk management effectiveness indicate a possible pathway linking behavioral inputs to perceived risk management performance. However, this pathway should be interpreted cautiously because the mediation effects are weak, the explained variance for effectiveness is low, and effectiveness and performance may share overlapping perceptual domains. The study is bounded by a single-organization, cross-sectional design with self-reported and supervisory perception-based measures; therefore, the findings should be generalized cautiously and validated through longitudinal designs and objective operational indicators.