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Record W3213321555 · doi:10.5267/j.uscm.2021.9.008

The mediation role of supply chain agility on supply chain orientation-supply chain performance link

2021· article· en· W3213321555 on OpenAlexvenueno aff
Moh. Mukhsin, H.E.R. Taufik, Asep Ridwan, Tulus Suryanto

Bibliographic record

VenueUncertain Supply Chain Management · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Optimization Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsSupply chainBusinessMediationFlexibility (engineering)Upstream (networking)Supply chain managementIndustrial organizationProduction (economics)Supply chain risk managementDownstream (manufacturing)Process managementOperations managementService managementMarketingComputer scienceMicroeconomicsEngineeringEconomicsTelecommunicationsManagement

Abstract

fetched live from OpenAlex

This study aims to analyze the supply chain performance mediation on the relationship between supplier flexibility, supply agility, and company performance. The population in this study were 100 broilers in the districts / cities in Banten Province. The data to be used in this study are primary data, through sending questionnaires. Development of theoretical models with five hypotheses processed in the analysis using SmartPLS Software version 3.0.m3. The results showed that supplier flexibility and supply agility have a positive and significant effect on company performance, supplier flexibility and supply agility have a positive and significant effect on supply chain performance and supply chain performance has a positive and significant effect as an intervening variable to the company performance. Supply chain mediation has an important role in integrating production processes from upstream to downstream, including establishing good relations between businesses involved in supply chain management to improve the company's performance.

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)0.002
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.001

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 head0.008
GPT teacher head0.222
Teacher spread0.213 · 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 designObservational
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

Citations22
Published2021
Admission routes1
Has abstractyes

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