The relationship between sustainable HRM practices and employees’ attraction: the influence of SME managers’ values and intentions
Bibliographic record
Abstract
Purpose In many parts of the world, labor shortages are likely to affect the activities of SMEs. Consequently, SMEs needs to adopt attractive HRM practices. This study analyzes the impact of one type of sustainable HRM (SD-HRM) on employees’ attraction and retention factors such as employees’ motivation, the quality of image and customer satisfaction in SMEs context. It also looks at the impact of SME managers’ value-intentions, calculative (egoist-strategic) and non-calculative (altruist-institutional) on this relationship. Design/methodology/approach Drawing on part of a survey of 409 Quebec SME managers’ commitment to sustainability, a mediation model is used to consider the impact of the manager’s values-intentions on potential workforce attraction and retention factors. Findings The results show that the implementation of SD-HRM practices has a positive impact on the outcomes considered, as it was expected, but show the counterintuitive results that it is altruistic values (non-calculative), rather than egoistic values, that helps to maximize the desired effects. Practical implications SME managers could adopt SRHRM practices to attract and retain employees. To maximize positive impacts, they might strategically integrate this approach while remaining authentic to their altruistic values. Purely institutional intentions are insufficient. By being both personally committed and strategic, managers can improve both employee well-being and organizational performance. Originality/value The original aspect of this research is the integration of expectations of spin-offs (positive or neutral) in relation to SD-HRM, based on the values and intentions of SME managers. This allows to recognize the multiple profiles, justifications and objectives of SMEs, which do not form a monolithic whole and need to be understood and supported by considering their differences.
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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 | 0.003 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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".