# Decision tree

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Details: An electric power trading company has an option to buy 1,000,000 terawatts of electricity from a producer for $10 per terawatt. Other electric power trading companies have received this option and the company knows a decision must be made quickly. The company estimates it can sell the electricity for $14 per terawatt if it the deal goes through but the government may not approve, in which case the contract would be annulled and penalty of $1.50 per terawatt assessed. The company estimates that the possibility of government approval is 50-50. The $4 million would be a good profit but the 1.5 million loss if the contract is annulled would be serious. The company research division recommends calling an outside decision analyst for assistance. With the analyst's help, the company estimates that if it applies for approval and the approval goes through there is a 30 percent chance that the option to buy will still available after government approval. The company can hire a consultant to provide information on whether or not a license request would be approved for $500,000. The probability that the consultant's report will be favorable in the case that the application is approved is 0.90. The probability that the report will be unfavorable in the case that the application is rejected is only 0.60.

a. Perform an assessment of the uncertain quantities:

1. The probability of being granted approval,

2. The probability that the option to buy is still open if the company waits for government approval, and

3. The amount that the company can get for the electricity ($14 per terawatt).

b. Perform a sensitivity analysis to evaluate the consequences of these uncertainties to the decision.

c. Develop a decision tree to assist the company with this decision.

1. What is the expected value of perfect information,

2. the expected value of sample information, then

3. Interpret and compare

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##### Solution Summary

The solution performs a decision tree analysis (including a sensitivity analysis). It calculates expected value of perfect information and expected value of sample information.

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