Standard costing for fuzzy decision support information system: Take product mix for an example

Traditionally, the discussion over standard costing is focusing on: (1) prior control, its purpose is to ensure the cost of production plan to accord with the requirement of cost control, (2) posterior analysis, its purpose is to conduct variance analysis for detecting the causes of unfavorable variance and correcting inefficient process. The success of these two work functions depends on the reasonableness and accuracy of decision-maker’s forecast regarding relative variables. If decision-maker’s forecast is inaccurate, prior control and posterior analysis provides no assistance in reducing decision error. However under an uncertain situation, decision-maker subjectively evaluates and describes the uncertainty, also. provides statement that usually implicates fuzzy factor.Therefore, forecast has become a difficult task. Standard costing and fuzzy theory are consolidated in this study to explain the reason why decision-maker should make standard costing a supporting system in order to improve forecast accuracy. It is found in this study through general corollary that if decision-maker performs forecast under an uncertain situation and fails to make standard costing a supporting system, then: (1)the quantity of product mix will increase or decrease falsely along with the fuzzy tolerance interval defined by decision-maker, moreover, decision-maker may face the risk that he has performed analysis under an unreasonable (or not existed) productivity structure, (2) the value of profit forecast will increase or decrease falsely along with the tolerance interval of fuzzy objective function defined by decision-maker.