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Record W2589774483 · doi:10.1108/meq-10-2015-0191

Does GRI reporting impact environmental sustainability? A cross-industry analysis of CO<sub>2</sub> emissions performance between GRI-reporting and non-reporting companies

2017· article· en· W2589774483 on OpenAlexaff
Lotfi Belkhir, Sneha Bernard, Samih Abdelgadir

Bibliographic record

VenueManagement of Environmental Quality An International Journal · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainable Supply Chain Management
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSustainability reportingSustainabilityBusinessAccountingGreenhouse gasNull hypothesisEconometricsEconomics

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to assess whether Global Reporting Initiative (GRI) reporting has any direct and positive impact on environmental sustainability performance, and more specifically on CO 2 emissions of the reporting companies. Design/methodology/approach The authors analyze the CO 2 emissions data from 40 A-level GRI-reporting companies, over a period of six years and across five industry sectors, comparing them with a control group of 24 non-reporting companies, to assess any direct impact of reporting on emissions. Using one-way analysis of variance statistical analysis, the authors perform a cross-industry analysis of the five-year cumulative change in absolute emissions and emissions intensity for both groups of companies from 2008 to 2012. Findings The authors find that for both metrics, the p -value between the two groups of companies far exceeds the threshold of 0.05, hence strongly favouring the “null hypothesis” that there is no correlation between GRI-reporting and sustainability improvement. More specifically, the authors find that the mean of the five-year cumulative change for the GRI group is an actual increase of about 6 percent in absolute emissions and a decrease of 15 percent emissions intensity, while the mean for non-GRI entities shows a decrease of about 3 percent and a decrease of 17 percent in absolute emissions and emission intensity, respectively. Research limitations/implications The authors are limited by the small sample of companies that have five or more years of reliable reporting of CO 2 emissions at Scopes 1 and 2. Nonetheless, a normality test shows that the sample size is sufficiently representative of the entire population. Practical implications The lack of any correlation between GRI reporting, which often consists of the lion share of corporate social responsibility (CSR) investment, and any material improvement in CO 2 performance, suggests that the current CSR strategies are futile as far as environmental sustainability is concerned, and hence need to be drastically modified. Originality/value This work is the first of its kind to investigate quantitatively, and using rigorous statistical methods, the correlation between GRI reporting and carbon emissions 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)0.008
metaresearch head score (Gemma)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.004
Open science0.0010.002
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 head0.034
GPT teacher head0.351
Teacher spread0.318 · 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 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

Citations64
Published2017
Admission routes1
Has abstractyes

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