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Wang, X., Ferreira, F. & Yan, P. (N/A). A multi-objective competency-based decision support system for the assignment of internal auditors to multiple projects. Annals of Operations Research.

X. Wang et al.,  "A multi-objective competency-based decision support system for the assignment of internal auditors to multiple projects", in Ann. of Operations Research, N/A

@article{wangN/A_1716143753737,
	author = "Wang, X. and Ferreira, F. and Yan, P.",
	title = "A multi-objective competency-based decision support system for the assignment of internal auditors to multiple projects",
	journal = "Annals of Operations Research",
	year = "N/A",
	volume = "",
	number = "",
	doi = "10.1007/s10479-024-05855-3",
	url = "https://link.springer.com/article/10.1007/s10479-024-05855-3"
}

TY  - JOUR
TI  - A multi-objective competency-based decision support system for the assignment of internal auditors to multiple projects
T2  - Annals of Operations Research
AU  - Wang, X.
AU  - Ferreira, F.
AU  - Yan, P.
PY  - N/A
SN  - 0254-5330
DO  - 10.1007/s10479-024-05855-3
UR  - https://link.springer.com/article/10.1007/s10479-024-05855-3
AB  - Internal audit is an independent function that provides objective assurance and advisory services to business partners in the form of projects. As the skilled human resources, internal auditors play a significant role in ensuring audit quality and thus should be managed properly. However, there are only very few studies on auditor-project assignment problems at the operational level. Also, many studies on general team formation problems neglect the real-life implications of simplifying mathematical models to enable practitioners to understand and implement. To bridge these gaps, this study presents a new integrated two-phase approach to assign internal auditors to multiple projects. In the designed decision support model, a harmonious level index is firstly proposed, measuring the suitability between auditor capability and project characteristics using a simplified fuzzy filter ranking method. Then, Min–Max multi-choice goal programming (MMCGP) model provides the assignment solution that balances internal auditors’ multi-dimensional fit to the projects and their preferences, and thus optimizes the productivity of internal audit projects and staff’s job satisfaction. A real case study is presented to illustrate the effectiveness of the proposed model and its solution. The comparison results further show that the proposed model outperforms the manual operations and the exiting approaches in the literature. This research extends the existing literature on auditor assignment problem by developing a flexible decision support tool and a practical classification of auditor competency. The MMCGP approach also provides an ideal staff assignment solution by setting multiple aspiration levels for each goal and balancing the unwanted deviations among goals.
ER  -