Internal audit planning using spherical fuzzy ELECTRE

Menekse A., Camgöz Akdağ H.

Applied Soft Computing, vol.114, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 114
  • Publication Date: 2022
  • Doi Number: 10.1016/j.asoc.2021.108155
  • Journal Name: Applied Soft Computing
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, INSPEC
  • Keywords: Single-valued spherical fuzzy sets, Interval-valued spherical fuzzy sets, ELECTRE, Multi-criteria decision-making, Internal audit, CRITERIA DECISION-MAKING, MULTIPLE CRITERIA, SELECTION, CHOICE
  • Istanbul Technical University Affiliated: Yes


© 2021 Elsevier B.V.Internal audit is an independent and objective assurance and consulting activity that aims to improve the operations of an organization and add value to them. Planning internal audit by prioritizing the units to be audit is critical in terms of effective use of available audit and financial resources. In this paper, a new ELimination and Choice Translating Reality (ELECTRE) based decision support model is developed for addressing an internal audit prioritization problem. Spherical fuzzy sets are used for modeling the uncertainty in the nature of the problem and three different approaches are proposed within the study. The first approach is constructed with gradual concordance and discordance sets by comparing spherical fuzzy membership, non-membership, and hesitancy degrees of alternatives; the second approach is developed based on a single type of outranking relation obtained by utilizing score and accuracy functions of spherical fuzzy sets, and the third approach provides an increased fuzziness modeling capacity by using interval-valued spherical fuzzy sets. In the application part of the study, the units of an organization are prioritized for internal audit activity based on five components of the internationally recognized Committee of Sponsoring Organizations (COSO) framework. Sensitivity analyses for decision-maker and criterion weights and a comparative analysis with six other state-of-the-art multi-criteria decision making (MCDM) models are also presented to analyze the consistency and validity of the proposed spherical fuzzy ELECTRE model.