Strategic thinking, strategic planning, strategic innovation and the performance of SMEs: The mediating role of human capital
Bibliographic record
Abstract
Strategists have unique skills and abilities to connect the past and the present in order to predict what might happen in the future. The current study is the culmination of a number of research ideas in the field of Strategic Thinking (ST), Strategic Planning (SP) and Strategic Innovation (SI) in relation of Human Capital (HC). The survey method was used to collect data from 235 SMEs in the manufacturing industry of Yemen. Results indicate that ST, SP and SI have a significant effect on HC. The mediating effects of HC on the relationship between ST, SP and SI and SMEs’ performance were also examined. Results indicate that HC mediates the relationship between ST, SP and SI and firm performance. The findings of this study offer important insights for managers of SMEs, researchers and policymakers to further understand the effects of ST, SP SI, HC and SMEs’ performance. SMEs should also be encouraged to develop their ST, SP, SI and HC to improve their performance. Finally, this study serves not only to clarify the mechanism between HC and SMEs’ performance, but also to generalize the ST, SP and SI results in the Yemen and Middle East context.
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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 | 0.005 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".