How Good Is the Professional's Aptitude in the Conceptual Understanding of Change Management?
Bibliographic record
Abstract
As information technology (IT) functions and their professionals become partners in managing the information resource of the organization, contributors to the strategic planning process and major players in the business, rather than appendages which can be outsourced, new skills and competencies are needed for IT personnel. In particular, the proposition that IT specialists will have to function more like change agents has been echoed by a number of writers. However, there has been no prior empirical research that explicitly measures the degree of knowledge that IT specialists possess about fundamental concepts in the management of change in organizations. The present study offers to fill that gap. Data were collected using a survey instrument, the Managing Change Questionnaire, which was mailed to over 2,200 Canadian IT specialists. Of the sample, 18% returned completed questionnaires. ANOVA and t-test were used to identity differences among categories of respondents. Overall, IT practitioners' scores were acceptable but not particularly impressive. Results indicate that most IT specialists could pass the test regarding their knowledge of the concepts underlying organizational change management, and in the techniques needed to implement such a process, but they were not outstanding in that knowledge. Further, senior IT managers and systems/business analysts demonstrated a better grasp of many of the issues inherent in organizational change efforts than did technical personnel. Implications of these results for research as well as practice and educational programs in IT are discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".