The Role of Multi Dimensional EO in the Competitive Strategy - Performance Link
Bibliographic record
Abstract
Despite the increase market in catering industry by 37% per year, the number of SME-catering service firms is only 30.000, or only 5% from the total number of SME in 2016. From 30,000 registered catering service company, only 10% is an active business with annual growth rate (3%). In order to achieve competitive advantage and growth, firms will develop appropriate competitive strategy, strategy which directly relate to firm performance. The purpose of this paper is to develop a better understanding of the relationship between competitive strategy and firm performance in a different entrepreneurial orientation (EO) dimension. The statistical results revealed a) innovativeness, risk taking and proactivenss were found to have a significant and positive moderating effect on the relationship between differentiation strategy and firm performance b) innovativeness, risk taking and proactivenss were found to have a significant and positive moderating effect on the relationship between CL strategy and firm performance.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".