Cost–volume–profit analysis under uncertainty: a model with fuzzy estimators based on confidence intervals

In this paper we express the uncertainty existing in cost–volume–profit analysis via a new method that constructs fuzzy estimators for the parameters of a given probability distribution function using statistical data. First we present a fuzzy function for the cost and we search for the optimal solution among alternatives as Finch and Gavirneni [2006, International Journal of Production Research, 44 (20), 4329–4342] do, but here we use fuzzy estimators for the variable costs. As a consequence, we formulate a fuzzy number that represents the difference between the costs of the alternatives. Furthermore, we consider conditions of ‘complete’ uncertainty when a company needs to choose between two products and we express the profits and the risk via fuzzy estimators. Finally, under the same conditions of uncertainty we express the breakeven point when the income equals the total cost.

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