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Record W2154459378 · doi:10.1287/mnsc.1090.1100

Inventory Dynamics and Supply Chain Coordination

2009· article· en· W2154459378 on OpenAlex
Harish Krishnan, Ralph A. Winter

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

VenueManagement Science · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSupply Chain and Inventory Management
Canadian institutionsUniversity of British Columbia
FundersLuonnontieteiden ja Tekniikan Tutkimuksen ToimikuntaSouthern Methodist UniversityUniversity of WashingtonWashington University in St. LouisUniversity of Southern California
KeywordsNewsvendor modelIncentiveSupply chainMicroeconomicsDistortion (music)Product (mathematics)Inventory theoryCompetition (biology)Industrial organizationPerpetual inventoryBusinessSubsidyInventory controlEconomicsMarketingComputer science

Abstract

fetched live from OpenAlex

This paper extends the theory of supply chain incentive contracts from the static newsvendor framework of the existing literature to the simplest dynamic setting. A manufacturer distributes a product through retailers who compete on both price and fill rates. We show that inventory durability is the key factor in determining the underlying nature of incentive distortions and their contractual resolutions. When the product is highly perishable, retailers are biased toward excessive price competition and inadequate inventories. Vertical price floors or inventory buybacks (subsidies for unsold inventory) can coordinate incentives in both pricing and inventory decisions. When the product is less perishable, the distortion is reversed and vertical price ceilings or inventory penalties can coordinate incentives.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.848
Threshold uncertainty score0.786

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.000
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 head0.011
GPT teacher head0.217
Teacher spread0.207 · 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