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STOCHASTIC COST‐VOLUME‐PROFIT ANALYSIS WITH A LINEAR DEMAND FUNCTION

STOCHASTIC COST‐VOLUME‐PROFIT ANALYSIS WITH A LINEAR DEMAND FUNCTION In this paper we incorporate a linear demand function to model the price‐volume causal relationship into stochastic cost‐volume‐profit (CVP) analysis. We assume that the objective function is to maximize expected profit; other objective functions are also discussed and compared. A linear stochastic model follows from which probabilistic statements can be easily obtained if the random variables are assumed to be multivariate normal. The basic framework is shown to be a special case of project value maximization where project value is the cash flow of the project discounted for time and risk according to the capital asset pricing model. Moreover, an intertemporal extension that considers inventory is developed. In summary, a new approach to stochastic CVP analysis that incorporates the management decision process in an uncertain environment is developed. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Decision Sciences Wiley

STOCHASTIC COST‐VOLUME‐PROFIT ANALYSIS WITH A LINEAR DEMAND FUNCTION

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References (18)

Publisher
Wiley
Copyright
Copyright © 1981 Wiley Subscription Services, Inc., A Wiley Company
ISSN
0011-7315
eISSN
1540-5915
DOI
10.1111/j.1540-5915.1981.tb00094.x
Publisher site
See Article on Publisher Site

Abstract

In this paper we incorporate a linear demand function to model the price‐volume causal relationship into stochastic cost‐volume‐profit (CVP) analysis. We assume that the objective function is to maximize expected profit; other objective functions are also discussed and compared. A linear stochastic model follows from which probabilistic statements can be easily obtained if the random variables are assumed to be multivariate normal. The basic framework is shown to be a special case of project value maximization where project value is the cash flow of the project discounted for time and risk according to the capital asset pricing model. Moreover, an intertemporal extension that considers inventory is developed. In summary, a new approach to stochastic CVP analysis that incorporates the management decision process in an uncertain environment is developed.

Journal

Decision SciencesWiley

Published: Jul 1, 1981

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