Supply chain management evaluation in the oil and industry natural gas using SCOR model
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
This study aims to evaluate supply chain management on fuel oil to optimize improvement strategies that can be applied to ConocoPhillips companies in Indonesia. Effective and efficient supply chain management is one of the goals to achieve the company's business stability in the fuel oil supply chain. Fuel oil is a very complex basic need for companies in carrying out industrial and transportation activities. The research method is measuring and evaluating company performance through a combination of the Supply Chain Operation Reference (SCOR) model and the Analytic Hierarchy Process. Research respondents through interviews with four informants from the company ConocoPhilips. Based on the SCOR Version 11.0 model, in this study the SCOR measurement is divided into four perspectives, namely Plan, Source, Deliver and Return. Furthermore, through the measurement of Key Performance Indicators, it is classified using five supply chain dimensions, namely reliability, responsiveness, agility, costs, and assets. The research resulted in the final value of supply chain performance of 74,992 which can be categorized as a moderate or intermediate level, this implies that the existence of an assessment system or measurement of supply chain performance on an ongoing basis can be used as a consideration in determining the optimal strategy. Research findings, improvements, and strategies are needed, especially in the perspective of delivering which has the lowest score.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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