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Record W4404837611 · doi:10.5267/j.uscm.2024.9.006

The eco-friendly commodity supply chain strategy and competitive advantage on Indonesia plastic industry

2024· article· en· W4404837611 on OpenAlexvenueno aff
Setiyo Purwanto, Didin Hikmah Perkasa, Nur Endah Retno Wuryandari, Ryani Dhyan Parashakti

Bibliographic record

VenueUncertain Supply Chain Management · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Trade and Competitiveness
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessSupply chainIndustrial organizationEnvironmentally friendlyCommodityCommerceCompetitive advantageChain (unit)MarketingFinance

Abstract

fetched live from OpenAlex

The research aims to examine the role of supply chain strategy on eco-friendly commodity products and competitive advantage to improve financial performance of plastic recycling industries, export commitments and circular economic regulations as an intervening variable to see whether it will be better. This research involved a saturated sample of 176 employees in plastic recycle industries. Quantitative analysis was carried out through a survey approach using questionnaires and the Smart-PLS model structural analysis method. The interesting finding of this study is the eco-friendly commodity supply chain strategic and competitive advantage of plastic recycling products has a positive effect to improve financial performance. The circular economy regulation has a positive support also in this effect as well without any export commitment to the Indonesia plastic recycling industry. The importance of optimizing local resources in the eco-friendly commodities as recycling products to become a competitive advantage will be potentially in the export market.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.949
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.237
Teacher spread0.223 · 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 teacher head, not a consensus.

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

Citations1
Published2024
Admission routes1
Has abstractyes

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