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Enregistrement W7128735032 · doi:10.26180/4621366

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

2017· dissertation· W7128735032 sur OpenAlexaboutno aff
Aries Widiarto Sutantoputra

Notice bibliographique

RevueMonash University · 2017
Typedissertation
Langue
DomaineBusiness, Management and Accounting
ThématiqueCorporate Social Responsibility Reporting
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésVoluntary disclosureSustainabilityAffect (linguistics)DiscretionFlexibility (engineering)Environmental reportingSustainability reportingEnvironmental impact assessment

Résumé

récupéré en direct d'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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,015
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,080
Score d'incertitude au seuil0,159

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,015
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,003
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0010,002
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,064
Tête enseignante GPT0,255
Écart entre enseignants0,191 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2017
Routes d'admission1
Résumé présentoui

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