Lecture 15 Multiattribute Choice

Lecture 15 Multiattribute Choice - Lecture 15 Decision...

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1 Lecture 15 Decision Analysis Multiattribute Utility Theory
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2 Administrative Details Homework Assignment 6 is due  Thursday. Homework Assignment 7 is due  Thursday, 20 March Think about your groups for project! Initial topics/proposals with group members  due on Thursday. Midterm results are not yet available
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3 Complex Choices Multi-Objective Decision Making (MODM) Multiple, Competing Goals Maximize Tax Revenue Minimize Tax Rate Maximize Compliance Multi-Attribute Decision/Utility Theory  (MAUT) Diverse Characteristics Aggregated to Single Value  Measure Price Safety Performance Municipal Fiscal Policy Buying a Car
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4 MAUT MODM is typically dealt with using techniques  such as Goal Programming and the Analytic  Hierarchy Process We will not cover MODM MAUT involves an extension of our existing  techniques to incorporate  trade-offs Trade-offs are expressions of  preference
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5 Attributes Basic Party Problem Everything is reduced to dollars MAUT Party Problem V(x) is the value/utility of x V(Party) = V(Cost) + V(Fun) + V(Attendance) Multiple factors (attributes) influence our preferences for  various outcomes V(Party) is essentially a utility measure with multiple factors MAUT Key:  Can the attributes be traded-off? Could the party still be “good” if the Cost goes up, provided  that Fun and Attendance also go up? THINK: Additive vs Multiplicative Value
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6 Choice Strategies Non-Compensatory Strategies Methods for choosing alternatives that do  not allow for trade-offs between attributes Compensatory Strategies Decision maker can give up/get some of one  attribute in exchange for another attribute or  attributes to increase  total  value
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7 Non-Compensatory Strategies Similar to simple heuristics Easy to apply Prone to biases and can be misleading Lexicographic Elimination-by-Aspects Conjunctive Disjunctive Combinations
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8 Lexicographic Rule Rank the attributes in order of importance Rank all options on the most important attribute Break ties by using next most important  attribute Pick option with best value on most important  attribute Problem: Only considers a single attribute when  other attributes may also be important
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9 Elimination-by-Aspects Rule Rank the attributes in order of importance Establish a minimum acceptable level on each attribute Eliminate alternatives that are unacceptable with  respect to the most important attribute Continue elimination with next most important  attributes until only one alternative remains
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Lecture 15 Multiattribute Choice - Lecture 15 Decision...

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