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Cited by 288

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Accountability, Completeness, Credibility and the Audit Expectations Gap

Open access
Adams, Carol A., Evans, Richard·2004·Journal of Corporate Citizenship

Abstract

\n\t\t\t\t\tThis article deals with two concerns in achieving greater accountability in social reports: the lack of completeness of reporting, and the lack of credibility of reports. The article focuses, in particular, on the role of social audits in improving the completeness and credibility of reporting, thereby reducing the audit expectations gap. We suggest that this gap arises due to an over-emphasis on the validity of performance data at the expense of addressing completeness and credibility, both of which, we argue, require stakeholder involvement. The article reviews recent guidelines aimed at ensuring that companies produce reports that are complete in all material respects including those produced by the Global Reporting Initiative and the Federation des Experts Comptables Europeens, focusing particularly on AccountAbility's AA1000 Standard and AA1000S Assurance Standard. Finally, the article considers the development of a practical approach to social audit following principles increasingly being incorporated into developing assurance guidelines aimed at reducing the audit expectations gap. \n\t\t\t\t

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Metadata

Authors
Adams, C. A., & Evans, R.
Venue
Journal of Corporate Citizenship
Published
2004-06-01
Volume
2004
Issue
14
Pages
97-115
ISSN
  • 1470-5001 (ISSN-L)
  • 2051-4700
OpenAlex
W2127035639
Cited by
288
References
0
FWCI
9.99
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Accountability, Completeness, Credibility and the Audit Expectations Gap. https://app.cochat.ai/papers/10.9774/gleaf.4700.2004.su.00010
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Adams, C. A., & Evans, R. (2004). Accountability, Completeness, Credibility and the Audit Expectations Gap. Journal of Corporate Citizenship. https://doi.org/10.9774/gleaf.4700.2004.su.00010

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.