The effects of entrepreneurial orientation and organizational learning on marketing capability in supply chain management
Bibliographic record
Abstract
Research continues on supply chain management for environmentally friendly business products in supporting business continuity with strategic management in RBV theory. This study is accomplished through the health protocols and support government discourse during the COVID-19 period with a business strategy of learning, knowledge, entrepreneurship in implementing business change methods effectively and efficiently. The purpose of the study is to increase consumer satisfaction through entrepreneurial orientation, organizational learning, online marketing capabilities to get market needs and products that consumers accept and to build business strategies in resource-based business activities. The results show that entrepreneurial orientation and organizational learning significantly increased marketing capabilities and significantly increased customer satisfaction during the weak economy. Apart from that, organizational learning also significantly increases customer satisfaction. The Body Shop is a product made from environmentally friendly raw materials in a professional manner in the best processing, packaging and delivery to maintain relationships with consumers. The quantitative research method uses SPSS 23.0 and SEM AMOS 23.0 from distributing questionnaires to 100 consumers in Central Kalimantan and 100 consumers in South Kalimantan. The implication of this research is aimed at body shop companies that have outlets in Central and South Kalimantan in order to utilize technology to build business relationships and maintain consumer confidence in body shop products.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".