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Record W4400473617 · doi:10.5267/j.uscm.2024.6.003

Green accounting standards and environmental sustainability in Alkharj: Mediating role of social performance

2024· article· en· W4400473617 on OpenAlexvenueno aff
Anass Hamadelneel Adow

Bibliographic record

VenueUncertain Supply Chain Management · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAccountingSustainabilityEnvironmental accountingBusinessSustainability reportingEnvironmental reportingSocial sustainabilityEnvironmental economicsEnvironmental resource managementEconomics

Abstract

fetched live from OpenAlex

The Climate Disclosure Standards Board (CDSB) initiated the standards for sustainability and transparency in corporate reporting, which may be termed Green Accounting Standards (GAS). GAS encourages sustainable decision-making among businesses and practitioners. The present study explores the role of GAS on environmental sustainability in the firms located in the Alkharj governorate. Moreover, the mediating of social performance is also investigated in the relationship between GAS and environmental sustainability. For this purpose, a questionnaire is used to collect the data from accounting practitioners, and 224 valid responses are collected from the survey. The results of PLS-SEM show that GAS improves the environmental sustainability and social performance of the firms. Moreover, social performance also improves environmental sustainability. Thus, GAS promotes resource efficiency by tracking resource use and waste generation, which could be helpful in identifying opportunities for reducing environmental footprints. Thus, it also facilitates monitoring environmental performance in Alkharj to identify the areas needing improvement. Furthermore, GAS also improves social performance by recognizing social costs and engaging stakeholders, which are also facilitating more socially responsible decisions. Based on the results, the study recommends the firms in Alkharj governorate adopt GAS to improve environmental sustainability and social performance.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.598
Threshold uncertainty score0.939

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.004
GPT teacher head0.211
Teacher spread0.206 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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