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Record W7128732279 · doi:10.26180/4621366.v1

The relationship between environmental performance and environmental disclosure: evidence from Australia

2017· dissertation· W7128732279 on OpenAlexaboutno aff
Aries Widiarto Sutantoputra

Bibliographic record

VenueMonash University · 2017
Typedissertation
Language
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsnot available
Fundersnot available
KeywordsVoluntary disclosureSustainabilityAffect (linguistics)DiscretionFlexibility (engineering)Environmental reportingSustainability reportingEnvironmental impact assessment

Abstract

fetched live from OpenAlex

The link between environmental performance and environmental disclosure is not clear, and previous studies in the U.S. and Canada have found mixed relationships. This study researched the disclosure behaviour of 53 Australian listed companies. Quantitative and qualitative research approaches were employed to provide explanations of the relationship between environmental performance and disclosure as the disclosure of environmental information still remains largely voluntary in Australia. Firms have the discretion to disclose additional information, which also gives them flexibility to determine the breadth and depth of their environmental reporting in the non-regulated sections of their annual report, and in other mediums such as environmental reports, sustainability reports and their websites. The quantitative relationship between environmental performance and disclosure was examined first, followed by interviews with company representatives and a review of each company's publicly available documents relating to environmental performance and disclosure. The findings from the quantitative component of the study revealed that environmental performance, measured by emissions divided by sales and Corporate Monitor environmental ratings, has no statistically significant association with environmental disclosure. In addition, the study also found that levels of environmental disclosure were generally low, and there was greater reliance on the use of soft or un-verifiable types of environmental disclosure than on hard or verifiable information. However, industry classifications, company size and capital intensity were found to affect the level of environmental disclosure. Firms may disclose environmental information if they belong to high polluting industries, are large and have outlayed considerable capital expenditure,as has been suggested by voluntary disclosure theory. However, disclosing firms were not found to receive perceived financial benefits such as lower cost of capital (equity), increased share price, better future financial performance, or lower cost of debts. This may suggest either that the financial market in Australia does not value environmental information in the same way that it values financial information, or that firms do not receive significant pressure from the financial market to disclose. Environmental disclosure may thus be limited as firms see the perceived costs as higher than the perceived financial benefits. Further, the findings from the qualitative study highlighted the different drivers of environmental disclosure across four groups, based on perceptual mapping of environmental performance and environmental disclosure. The study found that the high level of environmental disclosure for Greenwashing (poor performance and high disclosure) and Green Companies (good performance and high disclosure) was influenced by the demand of financial markets. In addition, for Green Companies, customers appear to have also demanded more transparency over firms' environmental practices. The low level of environmental disclosure for the Silent Con-panies (poor performance and low disclosure) and Silent Achiever (good performance and low disclosure) groups may have been caused by low demand from their stakeholder base. Stakeholder theory is able to explain the environmental disclosure phenomena in Australia where firms tend to react to stakeholder groups' demands for environmental information. Disclosure can then be seen as a function of stakeholders' demands or pressures, and in the absence of such demand firms may disclose little or stay silent. This may suggest that they use disclosure practices as a public relations tool to satisfy stakeholder needs for information. The low level of environmental disclosure across the sample companies shows that Australian businesses do not appear to believe there is a strong business case to disclose environmental information. The study also revealed that the previous, largely voluntary, requirements for environmental disclosure enabled Australian businesses to disclose environmental information selectively, and this may not necessarily reflect their actual environmental performance. As a consequence, the users of these firms' environmental information may need to interpret the information carefully. The findings of this study also suggest regulators should avoid using a "one size fits all" approach. By understanding the drivers of disclosure, regulators can design regulations which cover all possible behaviours within the environmental performance and environmental disclosure relationship. Regulators may also need to endorse the development of an environmental reporting standard and mandatory audited environmental disclosure for Australian listed firms.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.080
Threshold uncertainty score0.159

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
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 head0.064
GPT teacher head0.255
Teacher spread0.191 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2017
Admission routes1
Has abstractyes

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