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Record W1024128566 · doi:10.1080/23302674.2015.1050079

A game theoretic model for coordination of single manufacturer and multiple suppliers with quality variations under uncertain demands

2015· article· en· W1024128566 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Systems Science Operations & Logistics · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSupply Chain and Inventory Management
Canadian institutionsUniversity of Windsor
FundersJapan Society for the Promotion of Science
KeywordsStackelberg competitionSupply chainQuality (philosophy)Game theorySensitivity (control systems)Operations researchComputer scienceMicroeconomicsBusinessIndustrial organizationMathematical optimizationEconomicsMathematicsMarketingEngineering

Abstract

fetched live from OpenAlex

In this paper, a game theoretic model for supply chain coordination problem is studied. The supply chain coordination problem involves one manufacturer and multi-suppliers with quality variations under demand uncertainty. The number of defective parts purchased from suppliers is unknown to the manufacturer while each supplier can determine the standard deviation of defective items. The relationship between the manufacturer and the suppliers is modelled by a non-cooperative game. The non-cooperative game model is analysed by the Stackelberg equilibrium where the manufacturer is regarded as a leader and the suppliers as followers. By deriving suppliers’ best response functions, the Stackelberg equilibrium under uncertainties is established. Sensitivity analysis is conducted to investigate the features of the proposed models with cost parameters. The results validate the derived managerial insights derived for the proposed model.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.927
Threshold uncertainty score0.443

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.093
GPT teacher head0.311
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it