A Conceptual Approach to Managing Labor Resources in the Maritime Industry
Notice bibliographique
Résumé
Motivation: More than 70% of accidents in the fleet are due to the "human factor" - a wide range of psychological and psychophysiological qualities of the person, which in some way affect the result of its operations. Statistics of major ship accidents in recent decades show that not a single element of the shipping system is aloof from them. That is ship crews, shipowners, charterers, consignees, classification societies and other organizations associated with maritime transportation form a “chain” of risk. The correct combination of human abilities and machine capabilities significantly increases the efficiency of the "person - machine" systems and determines the optimal use by a person of technical means for their intended purpose. Unfortunately, an adequate model that would allow both quantitative and qualitative optimization of the project team, especially in conditions of incomplete determination of the volume of work, today does not exist. In addition, the existing methods do not take into account the specifics of the formation and conditions for the implementation of projects by such teams as the ship's crew, namely the increased level of danger, the inability to make replacements during the voyage, the international composition, the language barrier, etc. In this context, the issue of human resources management as a basic element of achieving the efficiency of project implementation in the field of maritime transport is also urgent, which implies an emphasis on the problem of project-oriented management of crewing and activity of the crew of marine vessels. The issue of clarifying the role, importance and key elements of HRM strategies and policies in the implementation of these projects requires special consideration. The aim of the study is to develop methodological approaches for the forming of quantitative and qualitative composition and effective management of project teams, as a variable component of the project management system of marine vessels.Novelty: Develop methodological approaches for the quantitative and qualitative composition of project teams, as a variable component of the project team on the example of crews of marine vessels. The task of acceptability of the structure, quantitative and qualitative composition of the team was solved. The terminological base of project management was developed by more clearly defining the concepts of “project team” and “project management team”. The approach to the organization of the crewing company recruitment system to work on ships was proposed.Methodology and Methods: In this scientific research to achieve the objective and test the hypotheses suggested in the research paper was used: 1) project teams methodology in project management, in particular, the Project Management Institute Classification (2017) of types of teams in the organizational structure of complex projects and in their management and the taxonomy of SNCB Version 4.1 are designed to provide a comprehensive professional assessment of the level of training of project managers; 2) method for calculating the size of the project team is based on the condition of minimizing its number, which reduces operating costs for the implementation of the project by the Ringelmann effect is known - a formula that provides the ability to quantify and optimize the parameters of the project team; 3) the method of planning of the minimum crew of The International Association of Sea Pilots considering the role of the “human” element in preventing accidents and environmental pollution (the ISM Code and the STCW Convention 78/95 as amended).Data and Empirical Analysis: For the purpose of the study, data were collected and empirical analysis was conducted concerning the analysis of the accident rate of ships and crews for 2009-2019 (causes of accidents: damage to the case and mechanisms; clash; shipwreck and landing; fires and explosions; submergence; contact with the ground; varied; hostilities), that can have a result severe damage or loss of the ship.Policy Considerations: Human factor is the most important aspect that determines the efficiency of shipping development; maintaining of technical and technological processes of the ship puts certain requirements to the quantitative and qualitative composition of the team, deviation from which leads to the occurrence of certain risk events; formation of an effective model of ship's crew manning is the main link in ensuring effective shipping project management.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,004 | 0,004 |
| Études des sciences et des technologies | 0,004 | 0,015 |
| Communication savante | 0,009 | 0,008 |
| Science ouverte | 0,004 | 0,004 |
| Intégrité de la recherche | 0,004 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».