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Record W4291177897 · doi:10.1111/poms.13831

Quality investment, inspection policy, and pricing decisions in a decentralized supply chain

2022· article· en· W4291177897 on OpenAlex
Murat Erkoc, Haresh Gurnani, Saibal Ray, Mingzhou Jin

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

VenueProduction and Operations Management · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSupply Chain and Inventory Management
Canadian institutionsMcGill University
Fundersnot available
KeywordsQuality (philosophy)IncentiveSupply chainIndustrial organizationProduct (mathematics)BusinessDecentralizationCompetition (biology)Investment (military)MicroeconomicsEconomicsMarketing

Abstract

fetched live from OpenAlex

This paper studies the interaction between two key quality management decisions—input conformance quality and inspection policy—and related wholesale and retail prices in a two echelon supply chain. Market demand depends on the retail price as well as the end‐product conformance quality, which itself depends on the input quality and the inspection scheme. Consistent with previous empirical findings in the literature, we show that an increase in quality does not always result in higher prices for consumers due to the cost‐lowering effect of better quality. We also show that a lower input quality may still result in higher end‐product quality because of how it might incentivize more and/or better inspection. Any interaction between input quality and inspection policy becomes more pronounced in the decentralized system due to incentive asymmetry between the channel partners. This makes the adoption of a full‐inspection policy more likely there compared to an integrated system. Indeed, while vertical competition due to decentralization results in higher prices for customers, it can also result in better quality of end products. Another interesting finding in the decentralized setting is that, somewhat counterintuitively, a player may indeed opt to bear a higher share of the penalty for defective products sold to consumers resulting in higher profits for the player.

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: Empirical
Teacher disagreement score0.916
Threshold uncertainty score0.789

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
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 head0.032
GPT teacher head0.277
Teacher spread0.245 · 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