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Record W4285297132 · doi:10.5267/j.uscm.2022.3.001

The mediating role of environmental sustainability between green human resources management, green supply chain, and green business: A conceptual model

2022· article· en· W4285297132 on OpenAlexvenueno aff
Wahdiana Dian, Widiatmaka F. Pambudi, Djari Adriani janny, Samodro Bintang A.M Leonardus, Sukrisno Sukrisno, Kundori Kundori

Bibliographic record

VenueUncertain Supply Chain Management · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityBusinessSupply chain managementSupply chainSustainable businessMediationEnvironmental economicsIndustrial organizationProcess managementMarketingEconomics

Abstract

fetched live from OpenAlex

This study aims to assess the influence of green HR management and Green Supply Chain on practices for initiating green business and environmental sustainability. The research also incorporated the mediation role of environmental sustainability between green HR practices, Green Supply Chain, and green business. A structural study methodology was used with 220 samples drawn from manufacturing companies in the province of Central Java. A questionnaire was used to collect data. The PLS(SEM) was also utilized to assess the constructs' reliability and validity as well as investigate their hypothesized links. The finding of this study indicates that environmental sustainability significantly mediates the relationship between green HRM, green supply chain, and green business. The research also finds a positive relationship between green HRM, environmental sustainability, and green businesses. Similarly, findings also found a significant relationship between green supply chain, environmental sustainability, and green industries. The results of this study can be applied to strengthen the resource based theory and literature of HRM and supply chain management. There are several practical managerial implications for improving the performance of manufacturing companies in Central Java. They provide recommendations for practitioners and managers to improve the business performance of companies based on green HRM, green supply chain, and environmental sustainability.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Open science
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 score0.376
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0030.001
Scholarly communication0.0000.001
Open science0.0030.009
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.212
Teacher spread0.202 · 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

Citations23
Published2022
Admission routes1
Has abstractyes

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