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Decision Model Theory

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Decision Theory Models
The Six Steps in Decision Theory * Clearly define the problem at hand. * List the possible alternatives. * Identify the possible outcomes or states of nature. * List the payoff or profit of each combination of alternatives and outcomes. * Select one of the mathematical decision theory models. * Apply the model and make your decision.

Case
Here we use the Thompson Lumber Company case as an example to illustrate these decision theory steps. John Thompson is the founder and president of Thompson Lumber Company, a profitable firm located in Portland, Oregon.
Step 1
The problem that John Thompson identifies is whether to expand his product line by manufacturing and marketing a new product, …show more content…

Let the coefficient of realism is ‘a’ selected. The coefficient is between 0 and 1. When ‘a’ is close to 1, the decision maker is optimistic about the future. When ‘a’ is close ‘0’ the decision maker is pessimistic. It helps the decision maker to build feelings about relative optimism and pessimism. * Weighted average =a (maximum in row) + (1-a)(minimum in row). * Equally likely (Laplace)-one criterion that uses all the payoffs for each alternative is the equally likely also called Laplace decision criterion. This is to find alternative with highest payoff. * Minimax Regret • the final decision criterion that we discuss is based on opportunity loss or regret.

Expected Value of Perfect Information * Formula
EVPI = A – B
A = expected value with perfect information
B = expected value without perfect information

Calculation of (A) value: A = the best of each outcome x their prob.
The best of outcomes:

Best outcome = (100,000) (30,000)
A = 0.6 x 100,000 + 0.4 x 30,000 = 72,000

Calculation of (B) value: B = we select the max value of each given below
Outcome of each event:

0.6(50000) + 0.4 (30,000) = 42,000
0.6(100,000 -0.4(40,000) = 44,000
0.6(30,000) + 0.4(10,000) = 20,000
The max value for all computed value = 44,000

EVPI = A – B = 72,000 – 44,000 = 28,000

Expected Opportunity

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