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Record W3011885609 · doi:10.1080/13675567.2020.1741524

On joint effects of return policy coordination and retail competition

2020· article· en· W3011885609 on OpenAlexaff
Joong Y. Son, Rickard Enstroem

Bibliographic record

VenueInternational Journal of Logistics Research and Applications · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSupply Chain and Inventory Management
Canadian institutionsMacEwan University
Fundersnot available
KeywordsProfitability indexCompetition (biology)Industrial organizationPoolingIncentiveBusinessSupply chainVendorMicroeconomicsEconomicsMarketingFinanceComputer science

Abstract

fetched live from OpenAlex

This paper studies the effectiveness of a return policy as an incentive-aligned coordination mechanism in a decentralised supply chain for short life-cycle products. System performance with regards to profitability and product availability is assessed with a coordinated return policy between the vendor and two competing retailers. Building on the optimal return policy coordination model for short life-cycle products, this paper evaluates individual and joint effects of competition and coordination under the four different settings of competition with and without coordination, and no competition with and without coordination. Results indicate that joint effects are largely contingent on demand structures in the supply chain, whereas individually, return policy coordination displays greater effectiveness in improving fill rates at local retailers by maintaining high stocking levels and competition commands significant impact in improving the system profitability and service level by creating inventory pooling effects between competing retailers.

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 imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.094
GPT teacher head0.338
Teacher spread0.244 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2020
Admission routes1
Has abstractyes

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