Identifying criteria for a new MBA program model: a qualitative study of MBA stakeholder perceptions of 21st century management and leadership
Bibliographic record
Abstract
Much attention has been paid to the current state of graduate business education, specifically the MBA degree, and the seeming disconnect between industry needs and what business schools are preparing MBA graduates for. A comprehensive study on the state of MBA education was completed in 2010 by Datar, Garvin, and Cullen (2010), the goal of which was to document the forces reshaping business education and the institutional responses to them, as well as provide suggestions on a path forward for MBA education. This research picked up where Datar et al. (2010) left off: the purpose of this study was to identify criteria for a new model MBA. The Datar et al. (2010) study defined the unmet needs, but what remained undefined were the (a) skills; (b) capabilities; and (c) techniques that are central to the practice of 21st century management, and the (d) values; (e) attitudes; and (f) beliefs that should be part of a 21st century leader's world-view and professional identity. This study used a qualitative approach to add meaning to the variables defined above; specifically interviews with 14 participants were used to gather perceptions of 21st century leadership and management from MBA stakeholders as part of an in-depth and detailed inquiry. This study also reviewed five Southern California business schools in order to identify best-practices curricula. Based on the data gathered in this study a new model MBA was posited. A discussion of the findings and the implications for MBA education was included in Chapter 5.
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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".