Abstract
Since the seminal work of Zadeh (Information Control 8 (1965) 338) fuzzy set theory (FST) has evolved into a valuable extension to traditional techniques, such as regression and decision tree models, for decision analysis conducted under conditions of vagueness and ambiguity. This paper is concerned with the exposition and application of a fuzzy decision tree approach to a problem involving typical accounting data. More specifically, a set of fuzzy ‘if .. then ..’ rules is constructed to classify the level of corporate audit costs based on a number of characteristics of the companies and their auditors. The fuzzy rules enable a decision-maker to gain additional insights into the relationship between firm characteristics and audit fees, through human subjective judgements expressed in linguistic terms. We also extend previous research by developing a more objective semi-automated method of constructing the FST related membership functions which mitigates reliance on the input of human expert opinions.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
