Development of algorithms for assessing the competencies of employees of transport security departments

Abstract

This paper presents the results of a study on the development and validation of algorithms for assessing the professional competencies of employees of transport security departments. The relevance of the research is due to the increasing requirements for ensuring the safety of transport infrastructure in the context of modern challenges and threats, as well as the need to improve the effectiveness of human resource management in this area. The research methodology is based on an integrated approach, including the analysis of professional standards, expert assessments, multi-criteria analysis, machine learning and statistical modeling. The empirical basis was made up of data on the assessment of the competencies of 1,247 employees from 78 transport security departments of various modes of transport (aviation, railway, marine and automobile) in the period 2020-2023. The developed algorithms are based on a matrix model of competencies weighted by levels of criticality to ensure safety, and include a dynamic assessment system using machine learning methods. The results of the study demonstrate an increase in the accuracy of competence assessment by 27.3% compared with traditional methods, a decrease in assessment time by 42.6% and an increase in predictive validity by 31.5%. The proposed algorithms make it possible to identify critical areas of staff development and optimize training programs. The practical significance of the research lies in the development of an adaptive assessment system that takes into account the specifics of the transport sectors and the changing regulatory framework. Further research prospects are related to the integration of the developed algorithms into digital personnel management platforms and the expansion of the model, taking into account the intersectoral aspects of transport security.