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Record W2172012961 · doi:10.1108/13683040910984275

Analyzing price transmission in agri‐food supply chains: an overview

2009· article· en· W2172012961 on OpenAlexaboutno aff
L.H. Aramyan, Marijke Kuiper

Bibliographic record

VenueMeasuring Business Excellence · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomics of Agriculture and Food Markets
Canadian institutionsnot available
Fundersnot available
KeywordsSupply chainIndustrial organizationFood supplyBusinessTransmission (telecommunications)Power transmissionEconomicsPower (physics)MarketingComputer scienceAgricultural economicsTelecommunications

Abstract

fetched live from OpenAlex

Purpose The purpose of this study is to present a conceptual overview of the price transmissions within agri‐food supply chains. Analyzing price transmission in agri‐food supply chains is essential since imperfect price transition may result in market power. This is an important issue that needs attention, given that the structure of agri‐food retail in Europe, USA and Canada is experiencing rapid change towards retail power. Design/methodology/approach The conceptual overview draws on a review of different approaches in analyzing transmission of prices through an agri‐food supply chain based on supply chain analysis and price transmission studies. Findings Three key challenges are identified in analyzing price transmission in agri‐food supply chains: structure of the supply chain; factors affecting price transmission; and supply response. Originality/value This paper presents a novel concept in analyzing price transmission in agri‐food supply chains using price transmission literature and bi‐directional flows of information and products in agri‐food supply chains

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0010.001
Scholarly communication0.0030.006
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.063
GPT teacher head0.222
Teacher spread0.159 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations25
Published2009
Admission routes1
Has abstractyes

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