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Record W4285203708 · doi:10.5267/j.uscm.2022.5.010

Financial supply chain management: A bibliometric analysis for 2006-2022

2022· article· en· W4285203708 on OpenAlexvenueno aff
Ayman Abdalmajeed Alsmadi, Anwar Al-Gasaymeh, Najed Alrawashdeh, Loai Naser Alhwamdeh

Bibliographic record

VenueUncertain Supply Chain Management · 2022
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsStatus quoSupply chain managementSupply chainBusinessFinancial managementFinanceConceptual frameworkPhenomenonEconomicsMarketing

Abstract

fetched live from OpenAlex

Supply Chain Finance (SCF) is playing an increasingly important role in operational and financial practices and attracted growing attention from academia and industry alike. However, researchers have not yet been totally able to reach a consensus on the definition of this phenomenon. The study presented in the paper provides an overview of the advancements present in research on Financial Supply Chain Management. Using a bibliometric analysis approach, the paper summarizes the trends of development and the status quo of the Financial Supply Chain Management. The aim is to provide the reader with guidance and a solid conceptual framework for future research.

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)0.004
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.890
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.1100.193
Science and technology studies0.0010.000
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.013
GPT teacher head0.234
Teacher spread0.221 · 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.

Study designNot applicable
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

Citations40
Published2022
Admission routes1
Has abstractyes

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