Research Information System
Human Resources Management and Services, vol.8, no.2, 2026 (Scopus)
Addressing persistent gaps in Human Resources Development (HRD) practice, this study presents a systematic framework for competency-based training needs analysis (TNA) that links strategic workforce development to business performance in logistics. Using the Fuzzy Best-Worst Method (F-BWM) with 21 expert judges, we develop an MCDM model that identifies both the strategic importance of technical and behavioral competencies and their current performance gaps. A two-level hierarchy of three dimensions and ten sub-competencies is introduced. Simulation results show that negotiation/conflict resolution skills represent the greatest training need (weighted priority: 6.20), followed by market analysis capacity (2.74) and resilience (2.71)—despite higher strategic weights for technical competencies (e.g., sales, operational knowledge). This divergence between importance and need provides a critical insight: strategic training investments must target performance gaps, not merely important competencies. The framework offers a reproducible, analytically grounded decision-support mechanism for human resources (HR) leaders and logistics businesses to align training with strategy and build organizational capability. The study contributes to HRD theory by demonstrating how MCDM enables rational, defensible resource allocation in complex, multi-stakeholder environments.