1. A decision tree is simply a tool to assist in the evaluation of sequential decisions. The technique involves
identifying alternative courses of action available, the timing of the alternatives, the events that can
occur under each alternative, and the probability of each event occurring. By tracing through each
alternative, a decision can be make as to which sequence of decisions best meets the objective.
Reconsider the earlier example involving the manufacture of bicycle helmets. The firm is considering
whether it should build a large manufacturing plant requiring an outlay of $600,000 and having a
maximum economic life of two years. In each year the demand for helmets is expected to be either high
or low. However, if demand is low in the first year, it is expected to remain low in the subsequent year.
In addition, the firm has the option at the end of year 1 to abandon the project and the abandonment
value is dependent on the outcome of year 1. Specifically, if year 1 turns out to be a high-demand year,
the abandonment value is $ 200000, whereas if year 1 turns out to be a low-demand year then the
abandonment value is $ 75000. The decision tree commences with the main decision. The cash outlays
associated with each event on high or low demand are stated, along with the probability of that event
occurring, on each branch of tree. Demand for the helmets in the first year can be high, with an
estimated probability of 0.7, or low, with a probability of 0.3. At the end of the first year, two decisions
are required. Regardless of whether demand in the first year turns out to be high or low, the
abandonment choice must be made. At the end of the second year, the net cash inflows are dependents
on the level of demand; with high demand of 1,250,000 or with low demand of $250,000. And in the
context of the project proceeded with the low level of 0.3, the cash inflow in this case is $50,000.
Assume that the required rate of return on the project is 10% per annum.