Decision Sciences Journal
Volume 31, Number 4
Fall 2000
An Analysis of Fuzzy Clustering and a Hybrid Model for the
Auditor’s Going Concern Assessment
Mary Jane Lenard
School of Business, Barton College, Wilson, NC 27893, email:
mlenard@barton.edu
Pervaiz Alam
Accounting Department, Kent State University, Kent, OH 44242,
email: palam@kent.edu
David Booth
Administrative Sciences Department, Kent State University, Kent,
OH 44242, email: dbooth@bsa3.kent.edu
ABSTRACT. This study provides a description and testing
of fuzzy clustering and a hybrid model that can support the decision
an auditor makes when completing the going concern evaluation.
Fuzzy clustering is based on fuzzy logic, and the hybrid system
is designed to address the going concern decision through the
combined use of a statistical model and an expert system. These
models have the capability of identifying categories of firms
with particular characteristics that may indicate whether or
not the audit report of the firms requires a going concern modification.
A prediction of whether or not a firm may go bankrupt is included
as one of the components of the going concern decision. As a
result, if a firm is placed in a particular bankrupt category
by a decision model, it may help in the determination of the
auditor’s opinion regarding the continuity of the business.
Subject Areas: Auditor Judgment, Cluster Analysis,
Decision Support Systems, and Fuzzy Logic. |