This study aims to examine and visualize the adopted internal control structure and effectiveness in firms and present a typology of firms. Control structure and effectiveness are measured based on the assessment of management, rather than using reported material weaknesses as most studies do. This type of evaluation is more purposeful for firms that do not apply the Sarbanes-Oxley Act. Internal control frameworks provide only broad guidance concerning internal control concepts, leaving the details to the adopting firms.
The survey data (from 741 CEOs) are clustered using the self-organizing map, a visual artificial neural network approach. A three-dimensional effectiveness proxy is used.
The analysis reveals four alternative types of internal control effectiveness in firms and visually presents how the components of the internal control structure are associated with each one. A typology of internal control structure and effectiveness is then created.
The findings suggest that there are interrelated, but not straightforward, relationships between internal control variables and that there is a link between some of them and higher internal control effectiveness in practice. These findings have important implications for those responsible for improving or assessing internal control, such as management, personnel and internal and external auditors.
This paper uses a clustering approach to create a typology for alternative types of internal control structure and effectiveness, based on data from actual firms. Instead of using material weaknesses as a measure, this study uses managers’ own assessments of internal control effectiveness.
The contribution of the respondent firms to the survey is gratefully acknowledged. The financial support of the Academy of Finland (grants no. 122175 and 127656) is also gratefully acknowledged.
Länsiluoto, A., Jokipii, A. and Eklund, T. (2016), "Internal control effectiveness – a clustering approach", Managerial Auditing Journal, Vol. 31 No. 1, pp. 5-34. https://doi.org/10.1108/MAJ-08-2013-0910
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