The effects of entrepreneurial orientation and organizational learning on marketing capability in supply chain management
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
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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