The Co-Evolution of IT, Knowledge, and Agility in Micro and Small Enterprises
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Small firms facing today’s turbulent business environment often fail early in their life if they do not develop the necessary capabilities to survive. The main goal of this study is to investigate how IT and knowledge co-evolve, influencing a firm’s agility, within the context of micro and small enterprises (MSEs). Applying the resource-based view of the firm and dynamic capabilities, a multiple case study of eight firms was used to explore links among business, IT and knowledge strategies, resources, and capabilities. Links among IT and knowledge capabilities and firm agility were also explored. The results demonstrate that an MSE’s business strategy shapes, and is also shaped by, the firm’s IT and knowledge strategies; and that both IT and knowledge capabilities shape, and are shaped by, the firm’s agility, coevolving with it. By highlighting the important antecedents of small firm agility and presenting crucial links among agility, IT capabilities, and knowledge capabilities in MSEs, we encourage practitioners to think carefully about their IT and knowledge strategies and to rethink their use of firm resources and capabilities to develop agility in the face of environmental uncertainty and change.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 it