Leaving the cocoon: university course design and delivery vis-a-vis competitive strategy
Bibliographic record
Abstract
Purpose – This article aims to ask how Michael Porter’s seminal notions of generic competitive strategy may be applied to an emerging university industry where course design and delivery is conceived of as able to be undertaken using distinctive modes. Design/methodology/approach – The study is principally a polemic piece. However, its method is to view course delivery modes as generic strategies and overlay these on Porter’s strategy grid. Each mode of course delivery is viewed as a strategy because it is associated with a rationale that can be reconciled with the axes of advantage that Porter has defined. These axes are “kind of benefit” and “target market”. Findings – The study finds four generic methods of tertiary course delivery. These can be placed – largely without ambiguity – on Porter’s grid. Research limitations/implications – Further research may recreate findings using methods that draw on more data; possibly, survey evidence or multiple interviews, etc. Practical implications – The work has implications for university administrators and strategic planners within the tertiary sector. It connects sector-specific planning with theory and research about Porter’s generic strategies. Social implications – The article has public policy implications. It offers a portrait of how public-sector education is likely to look in a deregulated context. It offers implicit advice of securing competitive advantage for individual institutions. Originality/value – The article undertakes an exercise that has not been done before. The theory used for interpretation purposes is likely to be unfamiliar to those interested in planning within the tertiary sector (particularly, the public sector), although care is taken to justify new application of the theory.
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 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".