Audit‐firm group appointment: an artificial intelligence approach |
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Authors: | Efstathios Kirkos Charalambos Spathis Yannis Manolopoulos |
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Institution: | 1. Department of Accounting, Technological Educational Institution of Thessaloniki, PO Box 141, 57400, Thessaloniki, Greece;2. Division of Business Administration, Department of Economics, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece;3. Department of Informatics, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece |
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Abstract: | Auditor appointment can be regarded as a matter of pursued audit quality and is driven by several factors. The adoption of an effective auditor procurement process increases the likelihood that a company will engage the right auditor at a fair price. In this study, three techniques derived from artificial intelligence (AI) are used to propose models capable of discriminating between cases where companies appoint a Big 4 or a Non‐Big 4 auditor. These three AI methods are then compared with the broadly used method of logistic regression. The results indicate that two of the AI techniques outperform logistic regression. In addition, one method further improves its performance by applying bagging. Finally, significant factors associated with auditor appointment are revealed. Copyright © 2009 John Wiley & Sons, Ltd. |
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Keywords: | auditor appointment artificial intelligence audit quality data mining |
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