On the transposability of change management research results: a systematic scoping review of studies published in JOCM and JCM
Bibliographic record
Abstract
Purpose The purpose of this study was to assess the transposability of study results published in the Journal of Organizational Change Management (JOCM) and the Journal of Change Management (JCM) between 2000 and 2019 for change-management practitioners and researchers. Design/methodology/approach A systematic scoping review of a large sample of articles published in both journals was undertaken: 122 studies were considered for analysis and coded by two independent coders using an inductive grid. Findings Findings show that few studies (1) describe the nature of changes undertaken by organizations; (2) explain the contextual elements that characterize the environment at the moment when these same transformations are deployed; or (3) nuance their observations according to the change operation. Research limitations/implications Information on the type of change undertaken by the organization and about how change has been implemented is useful when communicating new scientific knowledge to practitioners. Nevertheless, the way in which studies are sometimes described masks some important nuances to be considered when interpreting or replicating certain results. Practical implications The relevance of these issues is enhanced by the fact that researchers or practitioners (as knowledge users) are likely to reproduce some of the actions carried out in previous studies in order to deepen research avenues or to facilitate the implementation of change initiatives in workplaces. Originality/value This research is among the first to assess the transferability of change-management study results published in both journals over such a long period. Its relevance also speaks to the importance of contextualizing results to ease their transposability by researchers and practitioners.
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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 | 0.449 | 0.783 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.078 | 0.054 |
| Science and technology studies | 0.005 | 0.012 |
| Scholarly communication | 0.019 | 0.021 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".