The effect of strategic planning on competitive advantages of small and medium 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
This research starts from a phenomenon that indicates that the competitive advantage of Small and Medium Enterprises (SMEs) in increasingly fierce business competition has not yet achieved in Sukabumi, Indonesia. This is indicated by the inefficiency of production costs felt by SMEs which are not capable of creating competitive prices and the difficulty of making unique products. The purpose of this study is to determine the magnitude of the influence of dimensional strategic planning on the competitive advantage of SMEs. The results of the analysis and discussion are expected to find a concept regarding SME strategic planning. This study uses a quantitative approach, with an explanatory survey design that explains and describes the level of influence of strategic planning on the competitive advantage of SMEs in Sukabumi Regency, Indonesia. By using data analysis of Structural Equation Modeling (SEM), the results of the study indicate that there is a significant influence of strategic planning on the competitive advantage of SMEs in Sukabumi, Indonesia. Strategic planning which consists of three dimensions, namely: the desires of external stakeholder, the company's internal encouragement, and the company's database, significantly influences the competitive advantage of SMEs. Of the three dimensions of strategic planning, the dimensions of external stakeholder have the highest influence, while the company's database have the lowest effect. These results practically imply for SMEs to increase the consideration of company database in preparing the SME strategic planning.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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