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A hybrid linguistic fuzzy multiple criteria group selection of a chief accounting officer

    Violeta Keršulienė Affiliation
    ; Zenonas Turskis Affiliation

Abstract

In the preceding decade, economic and social costs brought by financial statement fraud have shaken markets, devastated investment portfolios and reduced confidence in financial reporting. A financial department is special in the way it needs to conform to standards. Many individual attributes considered for the selection of a chief accounting officer, such as organisational skills, personality, leadership etc. This paper focuses on a fuzzy multi-criteria decision making (MCDM) algorithm, which integrates the principles of fusion of fuzzy information, additive ratio assessment method with fuzzy numbers (ARAS-F), fuzzy weighted-product model and analytic hierarchy process (AHP). The proposed method is apt to manage information assessed using both linguistic and numerical scales in a decision making problem with a group of information sources. The computational procedure is illustrated through the problem related to the selection of a chief accounting officer.

Keyword : personnel selection, accountant, linguistic representation, ARAS-F, AHP, MCDM, decision making

How to Cite
Keršulienė, V., & Turskis, Z. (2014). A hybrid linguistic fuzzy multiple criteria group selection of a chief accounting officer. Journal of Business Economics and Management, 15(2), 232-252. https://doi.org/10.3846/16111699.2014.903201
Published in Issue
Apr 29, 2014
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This work is licensed under a Creative Commons Attribution 4.0 International License.