Bibliographic record
Abstract
Over past few years, supply chain coordination has been widely studied and numerous practitioners and researchers proposed many models on this field. \nAlthough many previous studies addressed channel competition considering a scenario with an exclusive retailer with only one producer’s brand, in real world the retailers sell various products with different brands. This study was to analyze the relation between two suppliers and a common retailer by taking various degree of product sustainability into account. The market is considered to be duopoly. This thesis describes modifying and implementation of a supply chain coordinator tool in order to enhance the profit earned by any of the parties involved in this supply chain. \nIn this thesis we present a cooperation and collaboration model in a supply chain consisting of two suppliers with a common retailer. We establish the conditions for cooperation in such scenario with popular supply chain contracts. Even though other methods have been reviewed under various scenarios, we confine our interest to apply a coordinating contract and analyse the results. \nThe type of the contract that can coordinate the supply chain is debatable and it needs to be analyzed depending on the limitations. The methodological approach taken in this study is modifying a contract in order to coordinate the supply chain and leads to better off for all parties. \n \nFirst we consider the classical model then the whole sale price contract is applied. Later in order to enable the supply chain coordination, facility sharing contract and franchise contract have been modified and implemented. Finally by illustrating the results of implementing each contract, a framework is presented. In this study the linear demand function is used because of tractability in providing analytical results while in real case the nonlinear demand function is widely used.
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.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".