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Record W4309720034 · doi:10.53819/81018102t5136

Effect of Human Resources Policies on Employee Satisfaction; A Case study of Loblaw Companies Limited, Canada

2022· article· en· W4309720034 on OpenAlexaffabout
Reyna Dest Jawaad, Russell Weston Saputra, Sargent Weah Elorza

Bibliographic record

VenueJournal of Human Resource &Leadership · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicRisk Management in Financial Firms
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsJob satisfactionBusinessIncentiveLoyaltyHuman resourcesMarketingHuman resource policiesEmployee researchHuman resource managementPopulationEmployee motivationWork (physics)Descriptive statisticsEmployee engagementEconomicsManagementEngineering

Abstract

fetched live from OpenAlex

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

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.

How this classification was reachedexpand

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.423
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.067
GPT teacher head0.274
Teacher spread0.207 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2022
Admission routes2
Has abstractyes

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