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Cited by 330

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Big Data as Complementary Audit Evidence

Yoon, Kyunghee, Hoogduin, Lucas, Zhang, Li·2015·Accounting Horizons

Abstract

SYNOPSIS: In this paper we argue for the use of Big Data as complementary audit evidence. We evaluate the applicability of Big Data using the audit evidence criteria framework and provide cost-benefit analysis for sufficiency, reliability, and relevance considerations. Critical challenges, including integration with traditional audit evidence, information transfer issues, and information privacy protection, are discussed and possible solutions are provided.

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Metadata

Authors
Yoon, K., Hoogduin, L., & Zhang, L.
Venue
Accounting Horizons
Published
2015-06-01
Volume
29
Issue
2
Pages
431-438
ISSN
  • 0888-7993 (ISSN-L)
  • 1558-7975
OpenAlex
W2066147459
Cited by
330
References
3
FWCI
75.15
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Big Data as Complementary Audit Evidence. https://app.cochat.ai/papers/10.2308/acch-51076
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Yoon, K., Hoogduin, L., & Zhang, L. (2015). Big Data as Complementary Audit Evidence. Accounting Horizons. https://doi.org/10.2308/acch-51076

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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.