Artículo

Environmental Accounting and Sustainability: Bibliometric Analysis and Documentary Review of Scientific Production, Period 2015-2024

Resumen

The purpose was to describe global scientific and literary outputs, on different aspects around environmental accounting (EA) and sustainability in environmental, business and policy domains, between 2015 and 2024. This was achieved through a quantitative characterization of publications. The methodology used took as referent aspects for the analysis: focus, units, topics, country, authorship, citations and journals, these a descriptive and reflexive documentary study of the scientific literature, based on the collection of papers in Scopus and the use of VOSviewer. The materials were selected according to various criteria, including keywords such as “environmental accounting” and “sustainability”, limited to fields such as: business, management and accounting, during the period from 2015 to 2024. The result included the identification of 54 texts, with the years with the highest number of publications being 2015 with 25.8% and 2018 with 19.7% of the total number of documents. Regarding the approaches, a predominant orientation towards the qualitative paradigm was observed, with 70%, compared to the quantitative one, with 32%. The most common types were exploratory (65%), descriptive (20%) and correlational (3%). As for the units, the majority focused on inquiries in companies with 52%, divided between large companies (57%) and MSMEs (11%). In turn, the sectors most frequently observed were tertiary (48%), followed by secondary (34%) and primary (2%). The origin of most of the studies was the United States, the United Kingdom, Australia and Italy. Finally, the limitations found were mainly related to the methodological approach, the inclusion of only one database, which could have excluded relevant studies not indexed in this one.
Hidayat, Erwin Yudi (57205439013); Hastuti, Khafiizh (56485990500); Muda, Azah Kamilah (23390362900)
Artificial intelligence in digital image processing: A bibliometric analysis
2025
10.1016/j.iswa.2024.200466
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85212984349&doi=10.1016%2fj.iswa.2024.200466&partnerID=40&md5=14c2a82f6cb46e9efa80c050fc79c24f
Faculty of Computer Science, Universitas Dian Nuswantoro, Semarang, 50131, Indonesia; Dinus Research Group for AI in Medical Science (DREAMS), Universitas Dian Nuswantoro, Semarang, 50131, Indonesia; Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Melaka, 76100, Malaysia
All Open Access; Gold Open Access
Scopus
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