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Record W3008370838 · doi:10.6000/1929-7092.2020.09.12

A Conceptual Approach to Managing Labor Resources in the Maritime Industry

2020· article· en· W3008370838 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Reviews on Global Economics · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Business Development Strategies
Canadian institutionsnot available
Fundersnot available
KeywordsCrewContext (archaeology)Element (criminal law)Maritime industryOperations researchHuman resourcesWork (physics)Risk analysis (engineering)Computer scienceOperations managementBusinessHuman resource managementProcess managementManagement scienceKnowledge managementEngineeringManagementEconomicsAeronauticsPolitical science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.931
Threshold uncertainty score0.689

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.086
GPT teacher head0.248
Teacher spread0.163 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it