The community Walmart uncertainty model: A review of ownership and capital structure aspects
Bibliographic record
Abstract
The purpose of this study was to determine the role of the ideal aspects of ownership structure and capital structure in determining the uncertainty model of operational of Walmart. This type of research is an explanatory survey using qualitative and quantitative approaches. The qualitative method is carried out by descriptive analysis by conducting a field survey using a questionnaire designed in such a way. Respondents of this study were the 78 managers of the community minimart in Medan City, North Sumatera, Indonesia who were selected by purposive sampling method. Meanwhile, the quantitative method was carried out using SEM PLS analysis by analyzing the indicators of aspects of ownership structure, capital structure and dimensions of operational success. The results show that the capital structure variable had a significant effect on Walmart's operational success. Meanwhile, the ownership structure variable had no significant effect on Walmart's operational success. The novelty that is produced from this research is that the success of community self-service is determined by the capital structure. Capital is an obstacle faced by community supermarkets because with limited capital it is difficult for community supermarkets to expand their business.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".