<b>The Impact of strategic Agility on the</b> <b>SMEs competitive capabilities in the Kingdom of Bahrain </b>
Bibliographic record
Abstract
With a highly uncertain and changing business environment, the typical way of planning a business is not particularly useful in different organizations world-wide. The current literature explores the concept of strategic Agility based on the idea of flexible planning and implementation and can pivot direction at the time of crises. Three main theories underpinning these concepts are contingency-based theory, resource-based theory, and Dynamic capability theory. These theories have one common point of view: enterprises' ability to cope with unexpected changes, survive unprecedented threats from the business environment, and take advantage of changes as opportunities. The literature has identified various varia-bles that impact the adoption of strategic Agility in the organization, including strategic sensitivity, Resource fluidity, and Leadership unity. Some studies in the literature have found these variables as dimensions of strategic Agility. Further, the literature discussed how competitiveness could be achieved through strategic Agility at times of crisis, particularly in SMEs, which are highly prone to external problems due to limited resources and budgets.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".