A bibliometric review of corporate environmental disclosure literature with machine learning algorithms

Research output: Contribution to conferencePaperpeer-review

Abstract

The study identifies and discusses influential aspects of corporate environmental disclosure (CED) literature, including key streams, themes, authors, keywords, journals, affiliations, and countries. This review also constructs agendas for future CED research. Using a bibliometric review approach, we reviewed 560 articles on CED from 215 journals published between 1982 and 2020. Our insights are three-fold. First, we identified three core streams of CED research: 'legitimization of environmental hazards via environmental disclosures', 'the role of environmental accounting in achieving corporate environmental sustainability', and 'integrating environmental social and governance (ESG) reporting into the GRI guidelines'. Second, we also deployed a thematic map that classifies CED research into four themes: niche themes (e.g., institutional theory and environmental management system), motor themes (e.g., stakeholder engagement), emerging/declining themes (e.g., legitimacy theory), and basic/transversal themes (e.g., voluntary CED, environmental reporting, and corporate social responsibility). Third, we highlighted important CED authors, keywords, journals, articles, affiliations, and countries. This study assists researchers, journal editors, and consultants in the corporate sector to comprehensively understand various dimensions of CED research and practices and suggests potential emerging research areas. The study uses a more comprehensive data mining technique that uses keywords in abstracts, titles and the whole body of papers and then identifies inclusive trends in CED literature. We contribute to the extant accounting literature by investigating the organizational-level CED, both mandatory and voluntary, using a systematic and bibliometric literature review model to summarize the key research streams, themes, authors, journals, affiliations and countries. By doing so, we construct a future research agenda for CED literature.
Original languageEnglish
Publication statusPublished - 12 Jun 2023
EventAI and Big Data in Accounting and Finance Research Conference and the BAR special issue: 2023 XJTLU AI and Big Data - Suzhou, China
Duration: 11 Jun 202313 Jun 2023

Conference

ConferenceAI and Big Data in Accounting and Finance Research Conference and the BAR special issue
Country/TerritoryChina
CitySuzhou
Period11/06/2313/06/23

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