Decision Model Theory Essay

Case present we use the Thompson Lumber friendship case as an example to illustrate these decisiveness theory gradations. lavatory Thompson is the fo under and president of Thompson Lumber Company, a profitable firm regain in Portland, Oregon. look 1The problem that John Thompson identifies is whether to expand his fruit line by manufacturing and marketing a in the raw product, backyard storage sheds. metre 2* The second step is to list the selection. * Thompsons second step is to generate alternate(a)s that are available to him .In finish theory the alternate is a course of proceeding or strategy that the decision master fuel choose .According to him his resources are to construct 1 a large new plant to manufacture the storage sheds 2 a small plant, or3 no plant at all* So, the decision makers should analyze to make all possible alternatives ,on some occasion even the least important alternative might turn out to be the beat out choice.Step 3* Third step is to id entify possible outcomes. * The criteria for action are established at this time. According to Thompson in that respect are both possible outcomes the market for the storage sheds could be favorable means there is a high demand of the product or it could be disapproving means that there is low demand of the product. * Optimistic decision makers endure to ignore bad outcomes where as pessimistic managers may discount a favorable outcome. If you dont consider all possibilities, it will be difficult to make a logical decision, and the result may be undesirable. * There may be some outcomes over which the decision maker has little or no control is known as states of nature.Step 4* Fourth step is to list tax returns. * This step is to list payoff resulting from each possible combination of alternatives and outcomes. Because in this case he wants to increase his profits, he use profits to evaluate each consequences .Not every decision, of course, bottomland be based on m atomic num ber 53y alone any suppress means of measuring benefit is acceptable. In decision theory we roar such payoff or profits conditional nurtures.Step 5 & 6* The last two steps are to select and check the decision theory work. * Apply it to the data to help make the decision. Selecting the model depends on the environment in which you are operating and the amount of adventure and uncertainty involved. * stopping point Table with condition care fors for ThompsonTYPES OF DECISION making ENVIRONMENTS* The types of decisions people make depends on how overmuch knowledge or discipline they fuddle about the situation. There are three kind of decision making environments* Decision making under certainty.* Decision making under risk.* Decision making under uncertainty.Decision Making Under deduction* 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 ruff out come. * guinea pig Lets say that you have $10000 to invest 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 surmount alternative is to choose the second investment option to gain maximal profit.Decision Making Under Risk* Here the decision overlord knows about the some(prenominal) possible outcomes for each alternative and the fortune of particular 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 maximization of expected monetary value and minimization of expected loss. * Expected monetary value is t he weighted 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 chairperson of a coun reach 25 Years from now is not known. * The criteria that is cover in this section as follows1 Maximax this mensuration 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 minimum 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 of Realism Also called as weighted average, is a via media 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 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 prospect loss or regret.Expected Value of Perfect teaching* FormulaEVPI = A BA = expected value with improve informationB = expected value without perfect information advisement of (A) valueA = the best of each outcome x their prob.The bes t of outcomesBest 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 downstairsOutcome 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 analytic thinking of costs and benefits * To achieve a given outcome we often have to make a choice from among alternative means we normally 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 m any a(prenominal) years of schooling should you have?* How many hours should you work?* How many workers should you hire?* How much should save/invest?