MétaCan
Menu
Back to cohort
Record W2757296799 · doi:10.5267/j.uscm.2017.8.002

Supply chain collaboration: A state-of-the-art literature review

2017· article· en· W2757296799 on OpenAlexvenueno aff
Harjit Singh, Rajiv Kumar Garg, Anish Sachdeva

Bibliographic record

VenueUncertain Supply Chain Management · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicQuality and Supply Management
Canadian institutionsnot available
Fundersnot available
KeywordsState (computer science)Supply chainChain (unit)BusinessComputer scienceProcess managementMarketingAlgorithm

Abstract

fetched live from OpenAlex

Global competition in the marketing has led organizations to be more responsive and efficient to the customers' needs through quick-new product development and minimized delivery time. Customer satisfaction becomes the major issue for organizations; therefore organizations focus more and more on the collaborative supply chain. Thus, supply chain collaboration has become a major success factor for the organizations to achieve their corporate goals. The current research study is an attempt to address the supply chain collaboration through a systematic literature review. In findings, various specific areas have been examined to understand the necessity, evolution, issues and challenges, types, drivers, benefits, and barriers in the context of supply chain collaboration. Further, the research gap and future agenda have been derived which is very helpful for academics and practitioners to understand supply chain collaboration, gaps in the literature, and future agenda about the supply chain collaboration.

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)0.006
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.021
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0190.026
Science and technology studies0.0010.002
Scholarly communication0.0050.006
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.016
GPT teacher head0.261
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

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

Citations84
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueUncertain Supply Chain ManagementSame topicQuality and Supply ManagementFrench-language works237,207