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Leveraging Big Data and Analytics for Auditing: Towards a Taxonomy

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Authors

The application of big data and analytics to auditing is sparking a lot of interest in both research and practice. Along with other technological developments, big data and analytics are expected to drive the digitization of auditing and to improving its effectivity and efficiency. While several use cases and first literature reviews on this topic have already been published, the categories for classifying the use cases are still fragmented. By employing a systematic taxonomy development process, we developed a taxonomy that draws upon conceptual work and use cases from the academic literature. This
taxonomy provides dimensions and characteristics that help to classify use cases for big data in analytics in auditing in a structured manner.
Original languageEnglish
Title of host publicationProceedings of ICIS 2018 : Leveraging Big Data and Analytics for Audi
Number of pages9
PublisherAIS eLibrary
Publication date2018
ISBN (electronic)978-0-9966831-7-3
Publication statusPublished - 2018

Other publications by the same author(s)

AI-Enhanced Literature Reviews: Connecting Emerging Phenomena and Bodies of Knowledge

Naqvi, S. A. A., Zimmer, M. P., Kauschinger, M., Drews, P. & Basole, R. C., 2026, (Accepted/In press) Proceedings of HICSS 2026.

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Aligning Experimentation with Product Operations: A Taxonomy for Structuring Experimentation Teams

Stotz, N., Labay, B., Vermeer, L. & Drews, P., 2026, Software Engineering and Advanced Applications - 51st Euromicro Conference, SEAA 2025, Proceedings: 51st Euromicro Conference, SEAA 2025 Salerno, Italy, September 10–12, 2025 Proceedings, Part III. Taibi, D. & Smite, D. (eds.). Cham: Springer Nature Switzerland AG, Vol. 3. p. 23-38 16 p. (Lecture Notes in Computer Science; vol. 16083).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Conveying the Ethics of Artificial Intelligence in K–12 and Academia: A Systematic Review of Teaching Methods

Tschoppe, N. J., Katsarov, J., Drews, P. & Trittin-Ulbrich, H., 07.01.2025, Proceedings of the 58th Hawaii International Conference on System Sciences: Hilton Waikoloa Village, January 7-10, 2025. Bui, T. X. (ed.). Honolulu: University of Hawaii at Manoa, p. 4744-4753 10 p. (Hawaii International Conference on System Sciences (HICSS); vol. 2025).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Digital leadership routines: Understanding the role of artifacts in digital leadership development

Eberl, J. K., Zimmer, M. P. & Drews, P., 12.2025, In: Information and Organization. 35, 4, 21 p., 100599.

Research output: Journal contributions › Journal articles › Research › peer-review

Govern Like You Mean It: Embedding Data Ethics Practices within Data Governance

Richter, K., Zimmer, M. P. & Drews, P., 2025, AMCIS 2025 Proceedings. Atlanta: AIS eLibrary, 10 p. 1265. (The AMCIS proceedings series; vol. 2025).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

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