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

Violeta Keršulienė and Zenonas Turskis

Journal of Business Economics and Management, 2014, vol. 15, issue 2, 232-252

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.

Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://hdl.handle.net/10.3846/16111699.2014.903201 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:jbemgt:v:15:y:2014:i:2:p:232-252

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TBEM20

DOI: 10.3846/16111699.2014.903201

Access Statistics for this article

Journal of Business Economics and Management is currently edited by Izolda Joksiene, Romualdas Ginevicius and Ieva Meidute

More articles in Journal of Business Economics and Management from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().