Readiness for organizational change: the effects of individual and organizational factors
Bibliographic record
Abstract
Purpose This study proposes to understand the conditions favorable for readiness for organizational change. The analysis helps in proposing managerial interventions that would be useful for change management in an organization. Design/methodology/approach The study employs an empirical methodology to investigate the effect of individual and organizational factors on readiness for organizational change. The study has used descriptive research design. Bivariate linear regression is used to test the hypotheses, and multiple regression is used to identify the pertinent factor that affect individual's readiness for organizational change. Thereby, a causal relationship model is proposed, using few pertinent factors which are tested using the structured equation modeling (SEM) technique. Findings First, each of the factors independently has a significant effect on readiness for organizational change. Second, the prior experience of change, commitment towards organization and participation in decision-making are the pertinent factors that affect readiness for organizational change. Lastly, commitment towards organization partially mediates the relation between participation in decision-making and readiness for organizational change. Practical implications The analysis helps in proposing managerial interventions that would be useful for change management in an organization. It investigates how individual and organizational characteristics influence employees' readiness for organizational change, causing them to adopt the change process. Originality/value To the best of the authors’ knowledge, this is one of the first studies that investigates the pertinent individual factors and the organizational factors that affect readiness for organizational change in the context of an emerging economy, India.
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 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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 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".