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A Minimax Approach to Cost Variance Investigation with Imperfect Parameter Knowledge |
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| Authors: | David R Finley |
| Institution: | Department of Accountancy and Taxation, College of Business Administration, University of Houston, Houston, TX 77204-6083
David R. Finley is Associate Professor of Accounting at the University of Houston. He holds M.A. and Ph.D. degrees in mathematical statistics from American University and is also a CPA ms). Dr. Finley's publications include articles in Decision Sciences, The Accounting Review, Journal of Accounting Research, Auditing: A Journal of Practice and Theory, and Contemporary Accounting Research. His principal research interests are the application of quantitative methods to auditing and to managerial accounting. |
| Abstract: | Although models of the multiperiod cost variance investigation decision problem have been extensively analyzed, their implementation is hindered by the manager's lack of knowledge of parameter values essential to determining the optimal investigation strategy. This paper develops a minimax approach to determine a reasonable investigation strategy, even without knowledge of certain parameters. Specifically, the Dittman-Prakash Markovian variance investigation model is modified to allow specification of a suitable strategy when neither the probability of staying in the in-control state nor the expected cost for the out-of-control state is known. An objective function based on controllable costs is derived and a solution technique for the resulting minimax problem is developed. Numerical results indicate that the inherently robust minimax approach captures most of the cost savings available from methods that place greater input demands on the manager. |
| Keywords: | Budgeting and Control Systems Markov Processes Quality Control |