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Title: Internal auditor selection using a TOPSIS/non-linear programming model
Authors: Petridis, Konstantinos
Drogalas, George
Zografidou, Eleni
Type: Article
Subjects: FRASCATI::Social sciences::Economics and Business::Accounting
FRASCATI::Social sciences::Economics and Business::Economics
Keywords: Internal auditor selection
Quantitative methods
Non-linear programming
Issue Date: 1-Aug-2021
Source: Annals of Operations Research
Volume: 296
Issue: 1-2
First Page: 513
Last Page: 539
Abstract: One of the most challenging problems in personnel selection is the multi-attribute nature of the candidates. This problem is magnified during the procedure of selection of sophisticated personnel, such as internal auditors. By definition, an internal auditor must combine a selection of analytical and non-analytical skills, corresponding to specific cognitive and behavioral attributes. In this paper, a framework for internal auditors’ selection using TOPSIS technique is proposed, integrating behavioral and cognitive skills. AHP technique has been used to determine the weights of each criterion. By prioritizing the latter skills, the proposed framework can identify employable and potentially employable candidates. Besides considering the desirable skills in the process of personnel selection, the expected performance is also taken into account. To examine what would be the ideal importance of cognitive and behavioral skills that maximizes candidates’ performance, a non-linear programming method is applied. A real-life application is demonstrated to a sample of internal auditors from the Greek branch of a multi-national company.
ISSN: 0254-5330
Other Identifiers: 10.1007/s10479-019-03307-x
Appears in Collections:Department of Applied Informatics
Department of Business Administration

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