Bibliographic record
Abstract
Purpose – This paper views the phenomenon of offering/user interface complexity as having competitive strategy-related consequences. Porter’s conception of generic management strategy was created in the 1980s. It is not well adapted to industries which have proliferated in the Internet age. Accordingly, the conception presented in this article offers a modified version of Porter’s generic strategy framework. The new view incorporates the dimension of complexity alongside the original dimensions of “target market” and “type of advantage”. The article uses an analysis of the contemporary Canadian Telco sector to prosecute its case. Design/methodology/approach – The project uses an analysis of the stated competitive positioning orientations of firms operating in the contemporary Canadian Telecommunications sector to build a case about the changed nature of generic strategy in the digital age. It uses inductive reasoning to generalise findings about the Telco sector to other recently emerged (digital-age) industries. Findings – A revised view of Porter’s generic strategy grid is presented and defended. Research limitations/implications – The study analyses only one sector, but draws many broad conclusions. It uses inductive reasoning which is limited by the extent to which the exemplar case (telecommunications) may be compared to other cases within the same category (other digital age industries). The study does not use an extensive analysis of strategic planning documents of individual firms; however, this is not a limitation unless and until a critique challenges the claims made about generic strategies being pursued. Practical implications – The new conceptualisation may be used as a planning tool for digital-age firms. Originality/value – The project is a genuinely new attempt to update Porter’s view of generic strategy. It overcomes the problems which have been associated with previous attempts at such revision.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.009 | 0.022 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".