JEL Classification: C1 Econometric and statistical methods and methodology: general; C44 Operations research, statistical decision theory.
A major challenge for the managers in business today is to find the expected cost of forecasting error. This cost is the difference between the additional value of the perfect and imperfect information. Marketing managers make daily decisions based on market information, many of which originate from survey researches. To obtain this information generates high costs for the enterprises. Due to this fact, measuring the financial value of these perfect and imperfect information and calculating the expected cost of the prediction error is very important as a tool to assist in the decisionmaking process. In order to underline calculations of the information, a graphical representation, i.e. the decision tree, was used, and later, the problem was analysed using the Expert System Shell SPIRIT software. At the end of the paper, we discuss the results and the conclusions of this research. Methodologically, this paper is an applied research with an exploratory and a quantitative approach, classified as a bibliographical study. The paper contributes to the understanding of a tool that can assist in decision making for the managers in various organisations.
Engineering economics, Probabilistic expert systems, Risk analysis, Costs, Forecasting
