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Record W3134881769 · doi:10.3390/jtaer16040054

Sustainable Circular Business Model for Transparency and Uncertainty Reduction in Supply Chain Management

2021· article· en· W3134881769 on OpenAlexaff
Xiuli Huang, Yunfeng Wen, Pooja Trivedi, Shanmugan Joghee

Bibliographic record

VenueJournal of theoretical and applied electronic commerce research · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsSeneca Polytechnic
Fundersnot available
KeywordsCircular economySupply chainTransparency (behavior)Sustainable businessSustainabilitySupply chain managementBusinessBusiness modelOpenness to experienceValue propositionIndustrial organizationSustainable developmentValue chainEnvironmental economicsProcess managementComputer scienceEconomicsMarketing

Abstract

fetched live from OpenAlex

Circular Supply Chain Management (CSCM) incorporates the economy concept into supply chain concepts, which gives the supply chain sustainability domain an innovative and convincing viewpoint. The challenging factors in the circular economy are cooperation, trust, and transparency. Therefore, to achieve sustainable results, collaboration, and openness between organizations within networks and value chains are required. This paper explores the sustainability success using the Sustainable Circular Business Model (SCBM) to incorporate the principle at an operational level and suggest a structure for combining Circular Business Model (CBM) and CSCM for sustainable growth. The proposed structure shows how various circular business structures power the global supply chain in multiple loops. The circular business models differ according to the difficulty of the Circular Supply Chain (CSC) and the value proposition. Proposed SCBM shows that circular market and supply chain aid in reaching goals for sustainability has been discussed in this 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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.004
Scholarly communication0.0040.006
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.018
GPT teacher head0.280
Teacher spread0.263 · 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 designTheoretical or conceptual
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

Citations24
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of theoretical and applied electronic commerce researchSame topicSustainable Supply Chain ManagementFrench-language works237,207