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1 – 3 of 3Ahmed Aboelfotoh, Ahmed Mohamed Zamel, Ahmad A. Abu-Musa, Frendy, Sara H. Sabry and Hosam Moubarak
This study aims to examine the ability of big data analytics (BDA) to investigate financial reporting quality (FRQ), identify the knowledge base and conceptual structure of this…
Abstract
Purpose
This study aims to examine the ability of big data analytics (BDA) to investigate financial reporting quality (FRQ), identify the knowledge base and conceptual structure of this research field and explore BDA techniques used over time.
Design/methodology/approach
This study uses a comprehensive bibliometric analysis approach (performance analysis and science mapping) using software packages, including Biblioshiny and VOSviewer. Multiple analyses are conducted, including authors, sources, keywords, co-citations, thematic evolution and trend topic analysis.
Findings
This study reveals that the intellectual structure of using BDA in investigating FRQ encompasses three clusters. These clusters include applying data mining to detect financial reporting fraud (FRF), using machine learning (ML) to examine FRQ and detecting earnings management as a measure of FRQ. Additionally, the results demonstrate that ML and DM algorithms are the most effective techniques for investigating FRQ by providing various prediction and detection models of FRF and EM. Moreover, BDA offers text mining techniques to detect managerial fraud in narrative reports. The findings indicate that artificial intelligence, deep learning and ML are currently trending methods and are expected to continue in the coming years.
Originality/value
To the best of the authors’ knowledge, this study is the first to provide a comprehensive analysis of the current state of the use of BDA in investigating FRQ.
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Keywords
Hosam Moubarak and Ahmed A. Elamer
This study aims to explore the auditors’ responses to the COVID-19 pandemic in Egypt, with a focus on how their demographic characteristics – specifically gender, work experience…
Abstract
Purpose
This study aims to explore the auditors’ responses to the COVID-19 pandemic in Egypt, with a focus on how their demographic characteristics – specifically gender, work experience and audit firm size – affect their ability to identify key audit matters (KAMs).
Design/methodology/approach
The study used exploratory factor analysis to develop an index for evaluating auditors’ proficiency in distinguishing KAMs from non-KAMs, followed by multivariate regression analysis to analyze the impact of auditors’ demographics on this ability.
Findings
The study’s findings are significant as they highlight the influence of auditors’ gender and work experience on their capability to correctly classify KAMs. However, the size of the audit firm showed no significant effect on the auditors’ decision-making efficacy in identifying KAMs.
Research limitations/implications
While the study illuminates critical aspects of audit judgment during unprecedented times, it acknowledges limitations, including its geographical focus on Egypt and reliance on self-reported data. The implications stress the need for audit firms and regulators to consider auditors’ demographic characteristics when formulating policies to enhance audit quality and reliability during crises.
Originality/value
This research breaks new ground in the auditing literature by shedding light on the distinct role of auditor demographics in shaping audit opinion during crises. It is one of the pioneering studies to quantitatively assess the impact of auditors’ gender, experience and firm size on KAM identification in a global health crisis. It provides a unique perspective on audit practices in emerging economies.
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Ahmed Saad Abdelwahed, Ahmad Abd El Salam Abu-Musa, Hebatallah Abd El Salam Badawy and Hosam Moubarak
This study aims to empirically investigate the impact of adopting big data and data analytics (BD&A) on audit quality (AQ).
Abstract
Purpose
This study aims to empirically investigate the impact of adopting big data and data analytics (BD&A) on audit quality (AQ).
Design/methodology/approach
A questionnaire was distributed among audit practitioners working at audit firms in Egypt and 205 responses were collected. Partial least square structural equation modeling (PLS-SEM) was used to analyze and test research hypotheses.
Findings
The results reveal that BD&A has a direct significant positive effect on the audit process (AP) and auditor competence (AC). However, an insignificant impact of BD&A is found on audit fees (AF). In addition, the results indicate that BD&A has significant positive direct and indirect impacts on AQ.
Research limitations/implications
The results of this study will benefit several auditing stakeholders, such as audit firms, audit regulators, novice financial auditors and academic scholars.
Originality/value
This research is one of the earliest to empirically address the role of BD&A in enhancing AQ. It incorporates AP, AC and AF as mediators into a single model to explain the impact of BD&A on AQ. Also, it attempts to provide empirical evidence from a developing country with a less-regulated audit environment.
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