Marketing performance of bread and cake small and medium business with competitive advantage as moderating variable
Bibliographic record
Abstract
Small and Medium Business (UKM) of bread and cake can develop and encounter business competition if they are concerned greatly with their marketing performance. The purpose of this study was to determine: 1. The effect of market orientation and product innovation on marketing performance of Bread and Cake UKMs. 2.The moderating effect of competitive ad-vantage, strengthens or weakens, of market orientation and product innovation on the marketing performance of Bread and Cake UKMs partially. Data were obtained through offline questionnaire distribution to 80 respondents. The respondents were the business owners and employees of Bread and Cake UKMs in Bengkulu, Indonesia. The data analysis used in this research was Structural Equation Model (SEM) which was operated through the Partial Least Square (PLS) program, SmartPLS 3.2.9. The result indicated that market orientation and product innovation partially influenced marketing performance. Competitive advantage partially moderated (strengthens) the effect of market orientation and product innovation on marketing performance. This research contributes to the theoretical development of competitive advantage which moderates the effect of market orientation and product innovation partially on marketing performance. The study also helps to find the strategy to increase the marketing performance of Bread and Cake UKMs in Bengkulu, Indonesia.
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".