Linking entrepreneurial orientation dimensions with multidimensional differentiation strategy
Bibliographic record
Abstract
The aim of this study is to investigate the impact of entrepreneurial orientation (EO) on differentiation strategy. In this study, the components of EO are innovativeness, proactiveness and risk-taking. On the other hand, differentiation strategy indicates the product, process, market and brand differentiation. The study uses survey questionnaire for data collection. The data are collected from Muslim entrepreneurs of the apparel industry from Bangladesh. The study uses 339 data to conduct the research. After data collection, SmartPLS is applied for quantitative analysis to examine the effect of EO on differentiation strategy. The study indicates a positive and significant effect of innovativeness, proactiveness and risk-taking (EO) on differentiation strategy. Among the three components of EO, proactiveness is found the most significant component on differentiation strategy followed by innovativeness and risk-taking.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".