Strategic Reality Today: Extraordinary Past Success, but Difficult Challenges Loom
Bibliographic record
Abstract
After quickly reviewing the early history and the subsequent extraordinary success of Strategic Management, we suggest that research in our field today shows signs of settling into a premature institutional equilibrium regarding some vital issues. This equilibrium is inconsistent with strategic reality today on important topical and methodological imperatives the field faces. We suggest that these “strategic realities” must be extensively and thoroughly addressed to ensure our continued success in the future. We also suggest addressing these realities is key to improving our research efforts and their managerial usefulness as we move forward in a rapidly changing world. In other words, they represent important research challenges the business and academic environments present us today. We assert that substantial progress on any subset of these strategic realities over the next 20 years could be an important step toward continued success of our field. We also note that such progress will likely be very difficult.
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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 | 0.027 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.019 |
| Scholarly communication | 0.021 | 0.028 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.006 | 0.013 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".