Effect of Human Resources Policies on Employee Satisfaction; A Case study of Loblaw Companies Limited, Canada
Bibliographic record
Abstract
The study examined the effect of human resources policies on employee satisfaction in a case study of Loblaw Companies Limited in Canada. The study used an explanatory research design. The basis for using the design was to examine the relationship between the variables. The target population were employees from Loblaw Companies Limited. The study used purposive sampling to get the sample size of 289 employees. The study used questionnaires to collect the data. The analysis of the data was done using descriptive and inferential statistics. It was found that HR Policies are positively and significantly related to employee satisfaction (β=0.841, p=0.028). The study concluded that human resource policies are positively and significantly related to employee satisfaction. HR policies are the foundation of optimal utilization, management, workers' job satisfaction, and performance. A properly organized and adequate HR policy boosts employee job satisfaction and hard work in the firm. It also improves efficiency, motivates employees, and boosts employee performance. HR policies ensure that every employee of an organization is looked after, their needs are respected and proper benefits are available for their work. HR policies help address employee complaints, problems and grievances and outline how to solve them appropriately. The study recommended that firms develop methods for equitable and proper employee compensation. Managers should create appealing incentive programs. The management should always look for mechanisms that significantly increase employee happiness and performance. Sound human resource policies help build employee motivation and loyalty. This is especially true when the policies reflect established principles of fair play. The HR policies should guide how employees should behave in the workplace and how management handles issues such as complaints. Keywords: HR policies, employee satisfaction, Loblaw Companies Limited, Canada
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".