Application of Competency Management System in Safety Performance: A Case Study of a Canadian Structural Steel and Erection Industry
Notice bibliographique
Résumé
The construction industry is the most hazardous industry because of the nature of its tasks and insufficient proactive approaches confronting the incidents. A safe work environment is needed for workers as they are the key components of the construction industry and should not be exposed to the unpredictable situations on the jobsite without significant attention to their safety. Therefore, safety practices should be an integral part of the construction processes right from the onset. Despite advancements in occupational health and safety practices, accident rates in the construction industry remain high. Previous research studies examining human resource management introduced the concept of competency as the skills in which individuals know or learn to perform tasks. While the competency management approach has been examined from an industrial psychology perspective, studies have yet to examine the ability of competency management to improve safety performance in construction practice. This thesis focuses on developing a novel framework for examining the relationship between competency management and safety performance on construction sites. Two novel methodologies are presented in this thesis. The first methodology contributes to the existing knowledge by (i) newly identifying a relationship between competency management and safety performance in construction, (ii) describing the features of competency program implementation at a construction company, (iii) detailing a procedure for determining the correlation between the penetration rate of a competency program and safety indicators, (iv) comparing the differences in safety performance prior and subsequent to the implementation of a competency program, and (v) analysing the cost benefit of applying a competency program as a consequence of improvements in safety iii performance. To demonstrate the application of the proposed methodology, a statistical correlation analysis has been conducted. Data from safety performance and competency management system are provided by a steel fabrication company in Alberta, Canada. The results show a strong correlation between safety performance indicators and competency management and suggest that competency knowledge may improve safety performance. The second methodology proposes a system dynamic approach for examining how the competency management process contributes to the incident occurrence over time. Firstly, the competency hierarchy for performing construction tasks is introduced. Then, a causal loop diagram (CLD) for visualizing the relationships between the competency management and the incident rate is developed to understand the cause and effect of competency management and safety performance. Given the data available for modeling the relationships in the CLD, a stock and flow diagram (SFD) model can be developed to simulate the safety performance over time. To show the practical application of the developed approach, a case study was conducted in the same steel fabrication company to verify the significance of competency management approach in safety improvement. The simulation results prove that the incident rate decreases with job trainings. A sensitivity analysis also reveals that on-the-job training is one of the most important types of training for improving construction safety performance.
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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 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,009 | 0,002 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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 ».