Sustainability reporting in carbon-intensive industries: Insights from a cross-sector machine learning approach

IF 12.5 1区 管理学 Q1 BUSINESS
Edoardo Crocco, Laura Broccardo, Hind Alofaysan, Reeti Agarwal
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引用次数: 0

Abstract

Due to climate change concerns, academics and practitioners focus more on environmental management and sustainability. Accounting researchers have focused on corporate environmental disclosure and sustainability reporting in response to stakeholder demand for openness and accountability. Thus, scholarly studies on sustainability reporting have gained momentum with the frequent use of qualitative text analysis to assess company disclosures' completeness and quality. However, sustainability reporting research has major limitations wherein past studies have focused on certain sectors or qualitative content analysis. Coherently with the abovementioned gap, our study intends to examine sustainability reports of companies in agriculture, conventional energy, heavy industry and manufacturing, transport and automotive, and construction, the highly carbon-intensive industries most vulnerable to physical climate damage and net-zero transition risk. In doing so, the goal of the present research is to investigate sustainability reporting practice on a larger, cross-sectoral scale by using automated, machine learning-powered text analysis methods to complement and strengthen qualitative research results that scholars have previously obtained. The latent Dirichlet allocation topic modelling technique has been used to examine companies' sustainability efforts and identify industry-specific subtopics based on quantitative distribution. The originality of our analysis lies in determining how companies prioritise issues in sustainability reports. By comparing reports from different industries, we also identify sector-specific patterns and how organisations in highly carbon-intensive industries that are most exposed to physical climate damage and net-zero transition risk prioritise certain themes over others, as well as identifying what type of content is overall more prominently featured in reports, regardless of the industry. Our study adds to sustainability reporting literature by investigating a previously unstudied sample of sectors. Moreover, our study informs practitioners of existing sustainability reporting procedures. The subject model and a cross-industry view can advise policymakers and industry of which themes are under-disclosed and what industry-specific rules may be desirable to suit sector-specific needs.

碳密集型行业的可持续性报告:跨行业机器学习方法的启示
由于对气候变化的担忧,学术界和从业人员更加关注环境管理和可持续性。会计研究人员关注企业环境信息披露和可持续发展报告,以回应利益相关者对公开性和问责制的要求。因此,关于可持续发展报告的学术研究势头强劲,经常使用定性文本分析来评估公司披露信息的完整性和质量。然而,可持续发展报告研究存在很大的局限性,过去的研究主要集中在某些领域或定性内容分析上。针对上述不足,我们的研究拟考察农业、传统能源、重工业和制造业、运输和汽车业以及建筑业等高碳密集型行业的公司的可持续发展报告,这些行业最容易受到实际气候损害和净零过渡风险的影响。因此,本研究的目标是通过使用自动化、机器学习驱动的文本分析方法,在更大的跨行业范围内调查可持续发展报告实践,以补充和加强学者们之前获得的定性研究成果。我们采用了潜在 Dirichlet 分配主题建模技术来研究公司的可持续发展努力,并根据定量分布确定特定行业的子主题。我们分析的独创性在于确定公司如何在可持续发展报告中优先考虑问题。通过比较不同行业的报告,我们还确定了特定行业的模式,以及高碳密集型行业(这些行业最容易受到实际气候破坏和净零过渡风险的影响)的组织如何优先考虑某些主题而不是其他主题,同时还确定了无论哪个行业,哪类内容在报告中更突出。我们的研究通过调查以前未研究过的行业样本,为可持续发展报告文献增添了新的内容。此外,我们的研究还为现有可持续发展报告程序的实践者提供了参考。主题模型和跨行业视角可以为政策制定者和行业提供建议,帮助他们了解哪些主题披露不足,以及哪些特定行业的规则可以满足特定行业的需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
22.50
自引率
19.40%
发文量
336
期刊介绍: Business Strategy and the Environment (BSE) is a leading academic journal focused on business strategies for improving the natural environment. It publishes peer-reviewed research on various topics such as systems and standards, environmental performance, disclosure, eco-innovation, corporate environmental management tools, organizations and management, supply chains, circular economy, governance, green finance, industry sectors, and responses to climate change and other contemporary environmental issues. The journal aims to provide original contributions that enhance the understanding of sustainability in business. Its target audience includes academics, practitioners, business managers, and consultants. However, BSE does not accept papers on corporate social responsibility (CSR), as this topic is covered by its sibling journal Corporate Social Responsibility and Environmental Management. The journal is indexed in several databases and collections such as ABI/INFORM Collection, Agricultural & Environmental Science Database, BIOBASE, Emerald Management Reviews, GeoArchive, Environment Index, GEOBASE, INSPEC, Technology Collection, and Web of Science.
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