Decision Model Theory Essay Example for Free

finale Model Theory EssayCaseHere we occasion the Thompson Lumber Company case as an example to illustrate these purpose theory measurings. John Thompson is the devote and president of Thompson Lumber Company, a profitable firm located in Portland, Oregon. tonicity 1The line that John Thompson identifies is whether to expand his product line by manufacturing and marketing a new product, backyard storage sheds.Step 2* The second step is to list the alternate(a). * Thompsons second step is to generate choices that ar purchasable to him . In conclusion theory the alternative is a course of action or strategy that the determination producer can choose .According to him his alternatives be to construct 1 a large new whole works to manufacture the storage sheds 2 a small plant, or3 no plant at all* So, the closing ecclesiastics should try to make all possible alternatives ,on some occasion even the least(prenominal) important alternative might turn out to be the best c hoice.Step 3* leash step is to identify possible outcomes. * The criteria for action are established at this time. According to Thompson there are two possible outcomes the market for the storage sheds could be roaring means there is a blue demand of the product or it could be unfavorable means that there is low demand of the product. * hopeful decision makers tend to ignore bad outcomes where as disheartened managers may discount a favorable outcome. If you dont consider all possibilities, it ordain be difficult to make a legitimate decision, and the result may be undesirable. * There may be some outcomes over which the decision maker has little or no control is k like a shotn as states of nature.Step 4* Fourth step is to list payoffs. * This step is to list payoff resulting from each possible combination of alternatives and outcomes. Because in this case he wants to maximize his profits, he use profits to evaluate each consequences .Not every decision, of course, can be bas e on money alone any appropriate means of measuring benefit is acceptable. In decision theory we call such payoff or profits conditional honors.Step 5 6* The last two steps are to select and apply the decision theory model. * Apply it to the information to help make the decision. Selecting the model depends on the environment in which you are operating and the amount of take a chance and un sure thing involved. * Decision Table with condition observes for ThompsonTYPES OF DECISION MAKING ENVIRONMENTS* The types of decisions people make depends on how much knowledge or information they have about the situation. There are three affable of decision devising environments* Decision making under certainty.* Decision making under risk.* Decision making under uncertainty.Decision Making Under Certainty* Here the decision makers know about the certainty of consequences every alternative or decision choice has. * Naturally they will choose the alternative that will result in the best outcome. * Example Lets say that you have $10000 to drop for a period of one year. And you have two alternatives either to open a savings bet paying 6% interest and another is investing in Govt. Treasury Bond paying 10% interest. If both the investments are secure and guaranteed, the best alternative is to choose the second investment option to pass on uttermost profit.Decision Making Under Risk* Here the decision Maker knows about the several(prenominal) possible outcomes for each alternative and the probability of occurrence of each outcome. * Example The probability of being dealt a club is 0.25. The probability of rolling a 5 on die is 1/6. * In the decision making under risk, the decision maker usually attempts to maximize his or her expected well being. Decision theory models for business problems in this in this environment typically employ two equivalent criteria maximation of expected monetary value and minimization of expected loss. * Expected monetary value is the we ighted value of possible payoffs for each alternativeDecision Making under Uncertainty* Here there are several outcomes for each alternative, and the decision maker does not know the probabilities occurrences of various outcomes. * Example The probability that a Democrat/Republican will be the President of a country 25 Years from now is not known. * The criteria that is covered in this section as follows1 Maximax this bill find the alternative that maximizes the maximum payoffs or consequence for every alternative. Here we first locate the maximum payoff with every alternative and then pick that alternative with the maximum number. This is also known as cheerful decision criterion.* Maximin this criterion finds the alternative that maximizes the tokenish payoff or consequence for every alternative. Here we first locate the minimum outcome within every alternative and then pick that alternative with maximum number. This is called as pessimistic decision criterion. * Criterion o f Realism Also called as weighted average, is a compromise between an optimistic and a pessimistic decision. 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 seeming (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* FormulaEVPI = A BA = expected value with perfect informationB = expected value without perfect informationCalculation of (A) valueA = the best of each outcome x their prob.The best of outc omesBest outcome= (100,000) (30,000)A= 0.6 x 100,000 + 0.4 x 30,000 = 72,000Calculation of (B) valueB = we select the max value of each given below conclusion of each event0.6(50000) + 0.4 (30,000)= 42,0000.6(100,000 -0.4(40,000)= 44,0000.6(30,000) + 0.4(10,000)= 20,000The max value for all computed value = 44,000EVPI = A B= 72,000 44,000= 28,000Expected opportunity LossThe expected opportunity loss is the expected value of the regret for each decision (Minimax)EOL (Apartment) = $50,000(.6) + 0(.4) = 30,000EOL (Office) = $0(.6) + 70,000(.4) = 28,000EOL (Warehouse) = $70,000(.6) + 20,000(.4) = 50,000 bare(a) Analysis* Most of our decisions are made following our marginal analysis of costs and benefits * To achieve a given outcome we often have to make a choice from among alternative means we usually try to make the least costly choice among the available means * Sometimes our decisions result in benefits as well as costs * How much food should you buy?* How many years of trainin g should you have?* How many hours should you work?* How many workers should you hire?* How much should save/invest?