MétaCan
Menu
Back to cohort
Record W3115512752 · doi:10.5267/j.uscm.2020.11.007

Going green during COVID-19: Examining the links between green HRM, green supply chain and firm performance in food Industry of Bahrain: The moderating role of lockdown due to COVID-19

2020· article· en· W3115512752 on OpenAlex
Mahmoud Radhwan Hussein AlZgool, Umair Ahmed, Syed Mir Muhammad Shah

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueUncertain Supply Chain Management · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessSupply chainCoronavirus disease 2019 (COVID-19)Supply chain managementData collectionGreen foodFood industryMarketingPopulationIndustrial organizationFood science

Abstract

fetched live from OpenAlex

The objective of this study was to examine the role of green Human Resources Management (HRM) in the green supply chain (SC) and firm performance. The relationships between green HRM, green SC, lockdown, and firm performance were examined. In addition to this, the mediating role of green SC and the moderating role of lockdown was examined. The population of the study was based on the food industry of Bahrain and various companies were selected for data collection. Therefore, data were collected from the food supply companies in Bahrain. A questionnaire was used for data collection in which cluster sampling was applied. The findings of the study highlighted that green HRM has major importance for food supply companies. It has a positive role in promoting the performance of food supply companies in Bahrain. Furthermore, green SC also plays a vital contribution to the performance of food supply companies. However, COVID-19 has a negative role in firm performance. The situation of lockdown due to COVID-19 has a negative effect on the performance of these companies.

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.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.218
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.056
GPT teacher head0.257
Teacher spread0.201 · 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