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Breaking Down Online and Digital Reporting Practices: A Research Map From Websites to Social Media

Giuseppe Nicolò et al.

Corporate Social Responsibility and Environmental Management2026https://doi.org/10.1002/csr.70517article
AJG 1ABDC C
Weight
0.37

What the paper says

ABSTRACT This paper adopts a mixed research methodology, integrating bibliometric and systematic literature review (SLR) tools, to systematise the academic contributions and the different bodies of knowledge generated over the last decades on online and digital reporting practices, ranging from websites to social media. After defining a structured research protocol in line with the SLR's best practices, a final dataset of 455 articles published in peer‐reviewed journals from 1993 to 2024 was obtained and processed using bibliometric tools provided by the Bibliometrix package of R Studio, along with manual content analysis. The study highlights three main thematic clusters that have shaped the evolution of this research: online CSR/sustainability and IC disclosure in the private sector; Internet financial reporting (IFR), eXtensible Business Reporting Language (XBRL), and social media; and online financial and non‐financial disclosure in the public sector. Additionally, several research gaps have been identified, outlining a robust research agenda for future studies.

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https://doi.org/https://doi.org/10.1002/csr.70517

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@article{giuseppe2026,
  title        = {{Breaking Down Online and Digital Reporting Practices: A Research Map From Websites to Social Media}},
  author       = {Giuseppe Nicolò et al.},
  journal      = {Corporate Social Responsibility and Environmental Management},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1002/csr.70517},
}

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Breaking Down Online and Digital Reporting Practices: A Research Map From Websites to Social Media

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.