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Auditor judgment and decision-making in big data environment: a proposed research framework

Adli Hamdam (Accounting Department, Faculty of Business and Accountancy, University of Malaya, Kuala Lumpur, Malaysia)
Ruzita Jusoh (Accounting Department, Faculty of Business and Accountancy, University of Malaya, Kuala Lumpur, Malaysia)
Yazkhiruni Yahya (Accounting Department, Faculty of Business and Accountancy, University of Malaya, Kuala Lumpur, Malaysia)
Azlina Abdul Jalil (Accounting Department, Faculty of Business and Accountancy, University of Malaya, Kuala Lumpur, Malaysia)
Nor Hafizah Zainal Abidin (Accounting Department, Kulliyyah of Economics and Management Sciences, International Islamic University Malaysia, Kuala Lumpur, Malaysia)

Accounting Research Journal

ISSN: 1030-9616

Article publication date: 26 January 2021

Issue publication date: 8 February 2022

2309

Abstract

Purpose

The role of big data and data analytics in the audit engagement process is evident. Notwithstanding, understanding how big data influences cognitive processes and, consequently, on the auditors’ judgment decision-making process is limited. The purpose of this paper is to present a conceptual framework on the cognitive process that may influence auditors’ judgment decision-making in the big data environment. The proposed framework predicts the relationships among data visualization integration, data processing modes, task complexity and auditors’ judgment decision-making.

Design/methodology/approach

The methodology to accomplish the conceptual framework is based on a thorough literature review that consists of theoretical discussions and comparative studies of other authors’ works and thinking. It also involves summarizing and interpreting previous contributions subjectively and narratively and extending the work in some fashion. Based on this approach, this paper formulates four propositions about data visualization integration, data processing modes, task complexity and auditors’ judgment decision-making. The proposed framework was built from cognitive theory addressing how auditors process data into useful information to make judgment decision-making.

Findings

The proposed framework expects that the cognitive process of data visualization integration and intuitive data processing mode will improve auditors’ judgment decision-making. This paper also contends that task complexity may influence the cognitive process of data visualization integration and processing modes because of the voluminous nature of data and the complexity of business processes. Hence, it is also expected that the relationships between data visualization integration and audit judgment decision-making and between processing mode and audit judgment decision-making will be moderated by task complexity.

Research limitations/implications

There is a dearth of studies examining how big data and big data analytics affect auditors’ cognitive processes in making decisions. This paper will help researchers and auditors understand the behavioral consequences of data visualization integration and data processing mode in making judgment decision-making, given a certain level of task complexity.

Originality/value

With the advent of big data and the evolution of innovative audit procedures, the constructed framework can be used as a theoretical foundation for future empirical studies concerning auditors’ judgment decision-making. It highlights the potential of big data to transform the nature and practice of accounting and auditing.

Keywords

Acknowledgements

This research project was funded by the Ministry of Higher Education of Malaysia through the Fundamental Research Grant Scheme (FRGS – FP089-2018A).

Citation

Hamdam, A., Jusoh, R., Yahya, Y., Abdul Jalil, A. and Zainal Abidin, N.H. (2022), "Auditor judgment and decision-making in big data environment: a proposed research framework", Accounting Research Journal, Vol. 35 No. 1, pp. 55-70. https://doi.org/10.1108/ARJ-04-2020-0078

Publisher

:

Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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