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Record W2059902720 · doi:10.5539/jms.v5n1p149

The Impact of Green Supply Chain Management Practices on Organizational Performance: A Study of Jordanian Food Industries

2015· article· en· W2059902720 on OpenAlexvenueno aff
Salah M. Diab, Faisal A. Al-Bourini, Asad Aburumman

Bibliographic record

VenueJournal of Management and Sustainability · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsnot available
Fundersnot available
KeywordsSupply chain managementBusinessSupply chainOrganizational performanceMarketingConsistency (knowledge bases)Test (biology)Industrial organizationOperations managementEconomicsComputer science

Abstract

fetched live from OpenAlex

The purpose of this study is to test The Impact of Green Supply Chain Management Practices on Organizational Performance: A study On Jordanian Nutrition Industries. The Data was collected through a questionnaire; the consistency percentage was 85%; Cranach's alpha for all the domains and the whole tool is (0.89). Means, standard deviation, and simple and multiple linear regressions analysis were used to test the study hypothesis and the relationships between the dependent and independent variabeles. The researcher built the model and hypothesis based on the dimensions of green supply chain management practices. The researchers chose (6) firms specialized in industrial food sector and which the firms that applied the concept of green manufacturing. The results of the study showed that there was an impact of green supply chain management practices and its elements on organizational performance. The implications of this study are; academic implications, and managerial implications. The researchers include all the green supply chain management elements, on organizational performance which are; environmental performance, financial performance, and Operational Performanc. As a recomendation for this study, it may play an important role for managers and firms through understanding the green supply chain management and increasing the sales and benefits.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.275
Threshold uncertainty score0.906

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
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 head0.020
GPT teacher head0.266
Teacher spread0.246 · 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.

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

Citations84
Published2015
Admission routes1
Has abstractyes

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