The Interactive Effects of HPWP and Adaptive Leadership on Readiness and Commitment to Change
Bibliographic record
Abstract
Utilizing the Social cognitive theory, this study suggests that organizations that promote high performance work practices are instrumental in fostering an individual's affective commitment to change. We also hypothesize that an individual's readiness to change is an explanatory mechanism through which high performance work practices lead to an affective commitment to change. Additionally, the high performance work practices and readiness to change relationship would be strengthened in the presence of high adaptive leadership. We tested our hypotheses using a temporally segregated research design across three-time waves (n=337). We found support for our direct, mediating, moderating, and mod-med hypotheses. Our results corroborate that a high adaptive leadership and an organization implementing high performance work practices set the stage for creating an individual's affective commitment to change via their readiness to change. The current study integrates the change management, leadership, and HRM literature by suggesting unique mechanisms and boundary conditions that advance research and practice in an individual's willingness and acceptance to change. We suggest theoretical and practical implications for research and practice based on our study's findings.
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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 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".