Do high-performance work practices promote an individual's readiness and commitment to change? The moderating role of adaptive leadership
Bibliographic record
Abstract
Purpose Utilizing the social cognitive theory, this study aims to suggest that organizations that promote high-performance work practices (HPWPs) are instrumental in fostering an individual's affective commitment to change through the explanatory process of an individual's readiness to change. In addition, high adaptive leadership would also strengthen HPWPs and readiness to change relationships. Design/methodology/approach This study tested the hypotheses using a temporally segregated research design across three time waves (n = 337). Findings This study found support for the direct, mediating, moderating and mod-med hypotheses. The results of this study corroborate that a high adaptive leadership and an organization implementing HPWPs set the stage for creating an individual's affective commitment to change via their readiness to change. Originality/value The current study integrates the change management, leadership and HRM literature by suggesting a unique mechanism and boundary conditions that advance research and practice in an individual's willingness and acceptance to change. Based on the study's findings, the authors suggest theoretical and practical implications for research and practice.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".