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A General Approach to Stochastic Management Planning Models: An Overview.

John F. Kottas¹; Amy Hing-Ling Lan²; Hon-Shiang Lau³

¹ Associate Professor, School of Business Administration, University of Missouri--St. Louis. 1 · ² Washing ton University. 2 · ³ Assistant Professor, School of Business Administration, University of Missouri--St. Louis. 3

This article presents a general framework for handling a large class of stochastic management models that includes the stochastic CVP problem and stochastic present value analysis. After demonstrating the need of more flexibility and realism in risk analysis modeling, the authors consider the "four-moments" approach in describing diverse probability forms. Next, a set of easy-to-use formulas are presented for computing the exact values of the first four moments of the model's objective variable. Finally, methods. are discussed for achieving the two most important purposes of stochastic management modeling: estimating the probability of realizing various objective variable levels and determining the expected utility of a risky project. The entire framework blends several original formulas with some well-established techniques previously little known in the accounting/management literature. Compared to other recently published approaches, this framework permits more realistic modeling, requires less computations and provides more accurate and meaningful managerial information.

DOI

10.2308/tar-4492518

Volume

53 (2)

Pages

389-401

Language

en

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BibTeX

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