Participation in decision making: a case study of job satisfaction and commitment (part two)
Bibliographic record
Abstract
Purpose – When employees believe in and trust their management, it motivates and encourages employees' participation in decision making which improves employees' efforts, and benefits their job satisfaction and commitment to work. All of these factors, in turn, contribute to a trustworthy manager-employee relationship. While the literature supports this premise, there is little empirical evidence that patterns of causal inference in the relationship are clearly understood. This three-part empirical case aims to focus on studying the relations between employee trust in management in a Quebec manufacturing company and their job satisfaction, intention to quit, level of employee participation in decision making and their commitment. Design/methodology/approach – This empirical case will test five hypotheses regarding seven variables influencing the level of employee engagement and commitment, employee turnover, employee participation in decision-making processes and job satisfaction. Findings – The article finds that employee trust in management is an important determinant of their willingness to participate in decision making. Insufficient employee participation in decision making in turn leads to low level of employee job satisfaction and employee commitment. Lack of employee commitment and engagement affects the employee's intention to quit. Research limitations/implications – The sample size of the office workers was not sufficient in order to have statistically significant results of the correlations between the variables for the production department employees, and for the office/administrative staff. This could have helped to determine the level of internal communication specifically, but also the level of all of the other variables for the two different groups of employees. Practical implications – This article offers useful insights for management in relation to strengthening interpersonal trust within an organization, introducing employee empowerment practices and increasing employee job satisfaction and commitment. Social implications – Due to lack of trust in management, there will be high employee turnover. This in its turn will have a negative effect on both the performance of management and employees' welfare. Originality/value – The findings provide empirical evidence to support theoretical models that link employee trust in management, participation in decision making, job satisfaction, commitment, and turnover intentions and highlight the impact of these factors on organizational performance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".