Multi-Attribute model for audit evaluation;

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A Multi-Attribute Model for Audit Evaluation*
Theodore J. Mock
University of Southern California
Michael G. Samet
Decisionetics, Inc.
Introduction
This paper concerns research directed at the development of a general procedure for assessing an overall, meaningful measure of the quality of an audit engagement from a systematic integration of several evaluative charac­teristics.
Such a measure can serve as a key input for audit planning and cost-benefit analysis in complex assessment situations. The technical approach is based upon the creation and application of a hierarchical multi-attribute evaluation (MAE) model that decomposes an audit into manageable parts which can be analytically assessed and combined.
The importance of the need to parameterize and measure the quality of various audit procedures and their role in the overall process of evaluating audit evidence is widely recognized in the field. Accounting firms and their clients are continually striving to develop and refine useful criteria for assessing audit effectiveness. For example, Peat, Marwick, Mitchell & Co. (1976, p. 150) highlight a research opportunity objective to develop:
. . . measures of effectiveness for individual and related sets of auditing procedures that take into account ... the anticipated quality of evidence derived from their use.
Such auditing procedures include (p. 9):
... all of the tools, techniques and procedures used to examine information . . . The methods for reporting the results of the examina­tion,
because, no matter how thorough and effective the examination, in the end a user can only rely on the assurance that is actually communicated by the auditor's report. Additionally, audit methods encompass all of the supporting functions and procedures used to plan, control, and carry out an audit.
At a more general level, the American Institute of CPAs has shown a continuing interest in audit quality and firm quality control practices. For
* The research underlying this paper was supported, in part, by the Peat, Marwick, Mitchell
Foundation through its Research Opportunities in Auditing Program. Helpful suggestions and
assistance on this project have been provided by Deanna Daniels, William Holder and Valerie
Milliron.
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