Application of Competency Management System in Safety Performance: A Case Study of a Canadian Structural Steel and Erection Industry
Bibliographic record
Abstract
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".