The decision tree method takes into account that an initial planning in to is supplemented by further active actions in the following periods. With the help of the decision tree method, the optimal decision at the initial point in time can be made by taking into account the possible environmental conditions in the following periods and the corresponding subsequent decisions (e.g. additional capital expenditure, disinvestments, price and advertising measures). The graph for representing such a decision sequence problem is called a decision tree. The decision tree contains
- Decision nodes E, which mark a decision event
Random event nodes Z, which mark the occurrence of a random event
- Result node R at the end of each period
- Nodes R / E which indicate that a decision should be made for the following period in connection with the determination of the period result
- Edges e which indicate the alternative decisions
- Edges z, which characterize the alternative states that result from the occurrence of the random event.
When making investment decisions, the optimal decision alternative at the beginning of the planning period is usually determined on the basis of the expected value of the net present value.