Ch 9 Notes.docx

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Department
Information Technology Management
Course
ITM 501
Professor
Selcuk Savas
Semester
Fall

Description
September 22, 2012 ITM501: Chapter 9 Notes - Decision analysis: an analytic and systematic approach to the study of decision making - A good decision is based on logic, considers all possible decision alternatives, examines all available info about the future, and applies the decision modeling approach - A bad decision that is not based on logic, does not use all available info, does not consider all alternatives, and does not employ appropriate decision modeling techniques - 5 steps of decision making: o Clearly define the problem at hand o List all possible decision alternatives o Identify the possible future outcomes for each decision alternative o Identify the payoff (usually profit or cost) for each combination of alternatives and outcomes o Select one of the decision analysis modeling techniques discussed in this chapter. Apply the decision model, and make your decision - Decision alternative: a course of action that is available to the decision maker - Outcomes are also known as states of nature - Payoffs can also be nonmonetary (i.e. # of units sold, # of workers needed) o Payoffs are also called conditional values o Conditional values or payoffs: a consequence or payoff, normally expressed in a monetary value, which occurs as a result of a particular alternative and outcome - Decision table or payoff table: all decision alternatives are listed down the left side of this table, and all the possible outcomes are listed across the top while the body of the table contains the actual payoffs - The types of decision models available for selection depend on the environment in which we are operating and the amount of uncertainty and risk involved - 3 decision making environments: o Decision making under certainty: decision makers know for sure the payoff for every decision alternative; the consequences of every alternative is known  Typically means there is 1 outcome for each alternative o Decision making under uncertainty: decision makers have no info at all about the various outcomes; probabilities for each outcome to occur are not known o Decision making under risk: decision makers have some knowledge regarding the probability of occurrence of each outcome; probabilities are known but they could be precise or an estimate  Decision makers attempt to identify the alternative that optimizes their expected payoff  Decision analysis models for business problems in this environment typically employ 1 of 2 criteria:  Maximization of expected monetary value  Minimization of expected opportunity loss - An environment of decision making under uncertainty exists when a manager cannot assess the probabilities of the different outcomes with confidence, or when virtually no probability data are available o 5 different decision-making criteria to handle such situations:  Maximax  Selects the decision alternative that maximizes the maximum payoff over all alternatives  First locate maximum payoff for each alternative and then select the alternative with the highest value among these maximum payoffs  Also called optimistic criterion  Maximin  Takes an extremely conservative view on the future; exact opposite to maximax  Called pessimistic criterion  Finds the alternative that maximizes the minimum payoff over all decision alternatives  First locate the minimum payoffs for each alternative and then select the alternative with the highest value among those minimum payoffs  Criterion of realism  Also called Hurwicz  Offers a compromise between optimistic and pessimistic decisions  Use a parameter called the coefficient of realism to measure the decision maker’s level of optimism regarding the future o Coefficient is denoted by α, has a value between 0 and 1 o An α value of 0 implies that the decision maker is totally pessimistic about the future while an α value of 1 implies that the decision maker is totally optimistic about the future o Advantage is that it allows the decision maker to build in personal feelings about relative optimism and pessimism  Realism payoff for alternative = α x maximum payoff for alternative + (1- α) x minimum payoff for alternative  Because the realism payoff is just a weighted average for the maximum and minimum payoffs, this criterion is also called the weighted average criterion  Α = 0.5 implies a strictly neutral person  Equally likely  This criterion finds the decision alternative that has the highest average payoff  First we calculate the average payoff for each alternative and then pick the alternative with the maximum average payoff  Minimax regret  This criterion is based on opportunity loss  Opportunity loss also called regret: the difference between the optimal payoff and the actual payoff received  It’s the amount lost by not picking the best alternative  This criterion finds the alternative that minimizes the maximum opportunity loss within each alternative  To use this, first need an opportunity loss table and it’s done by determining the opportunity loss of not choosing the best alternative for each outcome; to do so, subtract each payoff for a specific outcome from the best payoff for that outcome  Once the opportunity loss table is constructed, we first locate the maximum opportunity loss (regret) for each alternative and then pick the alternative with the smallest value among these maximum regrets o In these criteria, we assume that all payoffs represent profits  If the payoffs represent cost, some of the criteria would need to be changed and an easy option is to convert costs in a payoff table to profits by multiplying all cost values by -1 o First 4 criteria can be computed directly from decision/payoff table whereas the minimax regret criterion requires the use f opportunity loss table - When the probability of occurrence of each outcome can be assessed, the problem environment is called decision making under risk o One of the most popular methods of making decisions under risk is : selecting the alternative with
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