Does accreditation promote organizational learning? A multiple case study of Canadian university business schools
Bibliographic record
Abstract
Purpose The purpose of this paper is to explore the potential learning consequences of AACSB accreditation as perceived by administrators and faculty members at four Canadian university business schools. Design/methodology/approach A qualitative, multiple case study approach was employed. A purposive sample of four Canadian business schools was selected and data were collected from multiple sources. The data were analyzed using NVivo7 and a cross case analysis was performed. Findings The results indicate that AACSB accreditation facilitated organizational learning in three of the four schools. Respondents felt that accreditation promoted strategic alignment, a re‐assessment of the school's mission, and an emphasis on performance management; others identified an increased focus on quality and/or research. Accreditation also served as a catalyst for change, one which motivated program improvement. In terms of contextual factors, leadership was found to be the most pervasive influence on organizational learning effects. Resource dependence was also found to be influential. Research limitations/implications This research highlights the importance of educational leadership in facilitating organizational learning through evaluative inquiry. Because of the qualitative methodology, the sample size is limited to four university business schools. Practical implications This study has practical implications for management education internationally, as AACSB accreditation is increasingly a global phenomenon. The findings will be of interest to educational administrators, policy makers, managers, and accrediting bodies who are interested in facilitating learning through accreditation Originality/value This research offers a novel approach to studying the question of AACSB accreditation and its learning effects. By using a qualitative multiple case study method, this research provided a unique opportunity to focus more keenly on context and its role in influencing the potential learning consequences of accreditation.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.026 | 0.006 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".