Leveraging Big Data and Analytics for Auditing: Towards a Taxonomy

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Standard

Leveraging Big Data and Analytics for Auditing: Towards a Taxonomy. / Krieger, Felix; Drews, Paul.
Proceedings of ICIS 2018: Leveraging Big Data and Analytics for Audi. AIS eLibrary, 2018. (International Conference on Information Systems 2018, ICIS 2018).

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Harvard

Krieger, F & Drews, P 2018, Leveraging Big Data and Analytics for Auditing: Towards a Taxonomy. in Proceedings of ICIS 2018: Leveraging Big Data and Analytics for Audi. International Conference on Information Systems 2018, ICIS 2018, AIS eLibrary. <https://aisel.aisnet.org/icis2018/datascience/Presentations/16/>

APA

Krieger, F., & Drews, P. (2018). Leveraging Big Data and Analytics for Auditing: Towards a Taxonomy. In Proceedings of ICIS 2018: Leveraging Big Data and Analytics for Audi (International Conference on Information Systems 2018, ICIS 2018). AIS eLibrary. https://aisel.aisnet.org/icis2018/datascience/Presentations/16/

Vancouver

Krieger F, Drews P. Leveraging Big Data and Analytics for Auditing: Towards a Taxonomy. in Proceedings of ICIS 2018: Leveraging Big Data and Analytics for Audi. AIS eLibrary. 2018. (International Conference on Information Systems 2018, ICIS 2018).

Bibtex

@inbook{e90e065161d9455dbf6ce975f98901bb,
title = "Leveraging Big Data and Analytics for Auditing: Towards a Taxonomy",
abstract = "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.",
keywords = "Business informatics, Audit Analytics, Audit Automation, Audit Transformation",
author = "Felix Krieger and Paul Drews",
year = "2018",
language = "English",
series = "International Conference on Information Systems 2018, ICIS 2018",
publisher = "AIS eLibrary",
booktitle = "Proceedings of ICIS 2018",
address = "United States",

}

RIS

TY - CHAP

T1 - Leveraging Big Data and Analytics for Auditing

T2 - Towards a Taxonomy

AU - Krieger, Felix

AU - Drews, Paul

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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.

KW - Business informatics

KW - Audit Analytics

KW - Audit Automation

KW - Audit Transformation

UR - http://www.scopus.com/inward/record.url?scp=85062563298&partnerID=8YFLogxK

M3 - Article in conference proceedings

T3 - International Conference on Information Systems 2018, ICIS 2018

BT - Proceedings of ICIS 2018

PB - AIS eLibrary

ER -