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Record W2593851478 · doi:10.1111/itor.12396

Outsource planning with asymmetric supply cost information through a menu of option contracts

2017· article· en· W2593851478 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 Transactions in Operational Research · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSupply Chain and Inventory Management
Canadian institutionsConcordia University
Fundersnot available
KeywordsOutsourcingProfit (economics)MicroeconomicsOrder (exchange)Supply chainBusinessComputer scienceInformation asymmetryPrivate information retrievalOperations researchEconomicsIndustrial organizationMathematicsMarketingFinance

Abstract

fetched live from OpenAlex

Abstract This paper investigates a supply contract design by a dominant manufacturer who faces a stochastic demand during a selling season. The manufacturer has several estimations of the supplier's cost with corresponding probabilities, that is, asymmetric cost information. The manufacturer designs a menu of call option contracts that include three variables: a supply order, an option, and an exercise price. We determine the optimal negative correlation between option and exercise prices as well as closed‐form formulas for the optimal supply orders. The results show that in the optimal menu of contracts either the option or the exercise price may be omitted from the menu, whereas the supply orders should always be customized for each supplier type. We show that in this problem, optimal profit assignment between contract partners under put and bidirectional option contracts is the same as call option contract studied. Numerical analysis including managerial insights is presented.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.873
Threshold uncertainty score0.821

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.006
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.106
GPT teacher head0.378
Teacher spread0.272 · 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