Supply chain performance and visit interest of restaurants: The role of buzz and viral marketing strategic
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
The purpose of this study was to analyze the relationship between buzz and viral marketing strategy on supply chain performance and visit interest of restaurants in Banten Indonesia. This type of research used explanatory with a quantitative approach using SEM-based variance analysis, this is because the dependent and independent variables in this study amounted to more than one so that they could use variance-based SEM to summarize the formulation of the analysis. The study was conducted on 120 restaurant owner respondents in the province. Banten Indonesia. The distribution of the questionnaire in this study was carried out in two stages, namely the distribution of online questionnaires via google form to restaurant owner consumers. The sampling technique used in this study is accidental sampling, namely the determination of the sample based on accidental samples. The results of this study are buzz marketing has a significant effect on supply chain performance, buzz marketing has a significant effect on visit interest, viral marketing has a significant effect on supply chain performance, viral marketing has a significant effect on visit interest, visit interest has a significant effect on supply chain performance.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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