Designing a Characteristics Effectiveness Model for Internal Audit

Steven Grima, Peter J. Baldacchino, Simon Grima (), Murat Kizilkaya, Norbert Tabone and Lauren Ellul
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Steven Grima: Department of Accountancy, Faculty of Economics, Management and Accountancy, University of Malta, MSD 2080 Msida, Malta
Peter J. Baldacchino: Department of Accountancy, Faculty of Economics, Management and Accountancy, University of Malta, MSD 2080 Msida, Malta
Simon Grima: Department of Insurance and Risk Management, Faculty of Economics, Management and Accountancy, University of Malta, MSD 2080 Msida, Malta
Murat Kizilkaya: Department of Economics, Faculty of Economics and Administrative Sciences, Ardahan University, 75000 Ardahan, Turkey
Norbert Tabone: Department of Accountancy, Faculty of Economics, Management and Accountancy, University of Malta, MSD 2080 Msida, Malta
Lauren Ellul: Department of Accountancy, Faculty of Economics, Management and Accountancy, University of Malta, MSD 2080 Msida, Malta

JRFM, 2023, vol. 16, issue 2, 1-44

Abstract: Identifying factors/latent constructs deemed to influence internal audit effectiveness (IAE), through identifying variables used as measures of effectiveness and hypothesising which variables have a statistically significant relationship with IAE was the primary objective. Secondary objectives involved exploring the perceptions and viewpoints of internal auditing and providing general recommendations. To achieve the above objectives, questionnaires were remitted to internal auditors (IA) in various countries, receiving 402 final valid responses. Exploratory factor analysis (EFA) was carried out to identify new latent variables/constructs, with confirmatory factor analysis (CFA) in structural equation modelling (SEM) utilised to confirm these factors. The EFA process identified 7 latent factors, with 5 being confirmed through SEM. These factors, confirmed the positive influence of 8/16 hypotheses with 3/16 having partial confirmation, 4/16 not achieving any statistically significant evidence and 1/16 having negative influence. Risk Management, IA size, competency, management support, External Audit (EA) and Audit Committee (AC) cooperation, follow-up process, and control environment were all deemed to positively influence IA effectiveness. Independence, objectivity, and standard adherence achieved partial confirmation of their positive influence. Audit quality, Big Data, scope limitations and public/private organisations achieved no statistically significant results on their influence, while outsourcing was deemed to negatively influence effectiveness.

Keywords: internal audit; audit effectiveness; risk; audit characteristics; audit committee; exploratory factor analysis; confirmatory factor analysis; structural equation modelling (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2023
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