Data-driven performance evaluation and behavior alignment in port operations : a multivariate analysis of strategic indicators

This study investigates how a KPI-based incentive system can enhance behavior alignment and operational performance in complex port environments, addressing the growing need for data-driven governance in public logistics operations. The research analyzes a two-year dataset from 145 navigation teams across 22 Brazilian ports, employing a multivariate approach that integrates cluster analysis, Wilcoxon signed-rank testing, and exploratory factor analysis (EFA). Results reveal distinct performance tiers, with high-performing ports showing consistent improvement in safety, compliance, and technical availability, while low-performing areas exhibit stagnation or decline. The stability of the three-factor structure-Operational Safety, Technical Availability, and Procedural Compliance-over time confirms the model's robustness and suggests increasing internalization of performance expectations by teams. These findings demonstrate that incentive systems, when combined with transparent feedback and recognition, can align team behaviors with organizational goals and drive sustained operational improvement. The study contributes a validated, replicable framework for performance management, offering practical guidance for enhancing governance and strategic alignment in high-risk, complex settings. Future studies should explore motivational factors and the model's applicability across the public sector.