Organizational Change Skills: An Empirical Cross-National Study
Bibliographic record
Abstract
This research is premised on the proposition that mastering organizational change skills may help improve success rate of change initiatives. The overall purpose of this empirical, cross-national study was to explore whether perceptions of organizational change skills differ across nations. Using a convenience sample, structured interviews were conducted with 90 managers and executives in three regions: the USA, the Baltics and South America to collect quantitative and qualitative data. Statistical significance of between-group differences in means was obtained with the help of one-way ANOVA, and differences in percentages were established using a chi square test. Most of the change skills were perceived similarly across the three regions, but nevertheless, there were some differences. More communication and managing the change process skills were believed to be present in organizations in the USA, while understanding internal and external environment was more characteristic of the Baltics and South America. Respondents in these two regions also considered interpersonal and social skills to be more important. Respondents’ awareness of change skills was quite low without prompting. However, when prompted, all pre-established 11 groups of skills (Somerville & Whelan-Berry, 2009) were rated as important, and the majority of respondents were confident that these skills could be found in their organization. Given the relatively few differences that were found across the three regions, this suggests that cross-border dissemination of organizational change skills is possible, but each geography requires a slight adaptation. The findings also suggest that if those leading/managing change initiatives recognize that there are at least 11 groups of change skills, and cultivate these skills within the organization, this could increase the success rate of change initiatives. Given the paucity of empirical research relating to change skills generally, and cross-national considerations specifically, and the importance of change for organizations globally, this exploratory empirical research makes important contributions.
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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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; 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".