DIGITAL MODEL OF NAVIGATOR'S COMPETENCIES BASED ON THE ANALYSIS OF STCW QUALIFICATION REQUIREMENTS
https://doi.org/10.33815/2313-4763.2025.2.31.006-018
Abstract
This study presents the development and validation of a digital competency-based model designed to optimize seafarer recruitment while ensuring full compliance with the International Convention on Standards of Training, Certification and Watchkeeping for Seafarers (STCW). Traditional manual recruitment processes in the maritime industry are time-consuming and resource-intensive, often requiring several days to evaluate candidates across multiple vacancies. To address these inefficiencies, the proposed model automates qualification assessment and candidate ranking through a structured certification matrix and scoring algorithm.
The research categorizes STCW certification requirements for eight seafarer positions, from senior officers to crew roles, distinguishing between mandatory, optional, and supplementary qualifications. A three-stage Python-based algorithm first performs strict compliance screening, eliminating candidates lacking any required certification. Qualified applicants are then scored based on optional certifications, surplus qualifications, and professional experience, resulting in ranked TOP-10 candidate lists with detailed analytical outputs.
Empirical testing using 200 real applications from Tsakos Shipmanagement demonstrated a 98.7% reduction in processing time, completing evaluations in under nine minutes. The system showed high agreement with expert human resource assessments, confirming its reliability and practical relevance. Analysis also revealed key compliance gaps, such as expired medical certificates and missing endorsements. Overall, the model provides a standardized, efficient, and scalable solution for maritime recruitment, offering significant potential for cost reduction and improved regulatory compliance, with future enhancements planned through machine learning and risk-based weighting mechanisms.
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