What information does a decision maker need in order to perf

What information does a decision maker need in order to perform an expected-value analysis of a problem

Solution

In certain situations, it is possible to know with more certainty which state of nature of the critical random variable will actually occur in the future. For instance, the choice of location for a restaurant may weigh heavily on whether a new highway will be constructed or whether a zoning permit will be issued. A decision maker may have probabilities for these states of nature; however, it may be possible to delay a decision until it is more clear which state of nature will occur. This might involve taking an option to buy the land. If the state of nature is favourable, the option can be exercised; if it is unfavourable, the option can be allowed to expire. The question to consider is whether the cost of the option will be less than the expected gain due to delaying the decision. Other possible ways of obtaining information about a random variable depend somewhat on the nature of the random variable. Information about consumer preferences might come from market research, additional information could come from product testing, or legal experts might be called on. The expected gain is the expected value of perfect information, or EVPI. Expected value of perfect information (EVPI)—the difference between the expected payoff with perfect information and the expected payoff under risk. To determine the EVPI, one can compute the expected payoff under certainty and subtract the expected payoff under risk. That is, Expected value of Expected payoff Expected payoff perfect information under certainty under risk