Strategic pivoting: how organizations can shift attention whatever their size
Bibliographic record
Abstract
Purpose Strategic pivoting, the decision to invest in shifting the attention of an organization, is no longer limited to early-stage organizations and entrepreneurs but has, without a discussion of complications, been applied to large corporations and public agencies. Design/methodology/approach This conceptual paper defines strategic pivoting, highlights the centrality of pivoting in new and entrepreneurial organizations and critically examines its application as a strategy fostering organizational agility in corporations. Findings Pivoting in the corporate context complicates the ease of executing an attention shift by introducing a path-dependent momentum that requires modification of the time horizon, stakeholder strategy and the frequency of pivoting. Practical implications This comparative examination of pivoting highlights the importance of organizational size, complexity, degree of specialization and path-dependent history when deciding to pivot. Originality/value The present ease with which the strategic pivot is treated as an adaptive strategy to corporate leaders seeking greater flexibility overstates the ease of execution.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".