Impact of Human Resource Management Practices on Nursing Home Performance
Bibliographic record
Abstract
Management scholars and practitioners alike have become increasingly interested in learning more about the ability of certain ‘progressive’ or ‘high-performance’ human resource management (HRM) practices to enhance organizational effectiveness. There is growing evidence to suggest that the contribution of various HRM practices to impact firm performance may be synergistic in effect yet contingent on a number of contextual factors, including workplace climate. A contingency theory perspective suggests that in order to be effective, HMR policies and practices must be consistent with other aspects of the organization, including its environment. This paper reports on empirical findings from research that examines the relationship between HRM practices, workplace climate and perceptions of organizational performance, in a large sample of Canadian nursing homes. Data from 283 nursing homes were collected by means of a mail survey that included questions on HRM practices, programmes, and policies, on human resource aspects of workplace climate, as well as a variety of indicators that include employee, customer/resident and facility measures of organizational performance. Results derived from ordered probit analysis suggest that nursing homes in our sample which had implemented more ‘progressive’ HRM practices and which reported a workplace climate that strongly values employee participation, empowerment and accountability tended to be perceived to generally perform better on a number of valued organizational outcomes. Nursing homes in our sample that performed best overall were found to be more likely to not only have implemented more of these HRM practices, but also to report having a workplace climate that reflects the seminal value that it places on its human resources. This finding is consistent with the conclusion that simply introducing HRM practices or programmes, in the absence of an appropriately supportive workplace climate, will be insufficient to attain optimal organizational 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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".