Using Attributes to Predict Objectives in Preference Models

Authors:
John C. Butler;James S. Dyer;Jianmin Jia
Affiliations:
Department of Accounting and MIS, Fisher College of Business, The Ohio State University, Columbus, Ohio 43210;Department of Information, Risk and Operations Management, McCombs School of Business, University of Texas at Austin, Austin, Texas 78712;Department of Marketing, Faculty of Business Administration, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong
Venue:
Decision Analysis
Year:
2006

Citing 13
Cited 6

Comparing hierarchical and nonhierarchical weighting methods for eliciting multiattribute value models

Management Science
Estimating utility functions in the presence of response error

Management Science
Preferences for proxy attributes

Management Science
The reliability of subjective probabilities obtained through decomposition

Management Science
The effects of splitting attributes on weights in multiattribute utility measurement

Management Science
Remarks on the analytic hierarchy process

Management Science
Strategic Decision Making

Strategic Decision Making
A Multiattribute Utility Analysis of Alternatives for the Disposition of Surplus Weapons-Grade Plutonium

Operations Research
Common Mistakes in Making Value Trade-Offs

Operations Research
A Multiple Attribute Utility Theory Approach to Ranking and Selection

Management Science
Anniversary Article: Decision Analysis in Management Science

Management Science
A causal mapping approach to constructing Bayesian networks

Decision Support Systems
Negative priorities in the analytic hierarchy process

Mathematical and Computer Modelling: An International Journal

From the Editors...

Decision Analysis
From the Editor...

Decision Analysis
Improving the Generation of Decision Objectives

Decision Analysis
From the Editor---Multiattribute and Intertemporal Preferences, Probability, and Stochastic Processes: Models and Assessment

Decision Analysis
Decision maps: A framework for multi-criteria decision support under severe uncertainty

Decision Support Systems
WholeSoldier Performance Appraisal to Support Mentoring and Personnel Decisions

Decision Analysis

Quantified Score

Hi-index	0.00

Visualization

Abstract

Prescriptive decision analysis suggests identifying the fundamental objectives---what the decision maker really cares about---and then constructing a value hierarchy by decomposing these objectives until quantifiable attributes can be identified. In many decision contexts the decision maker is presented with a list of attributes without an opportunity to consider her fundamental objectives. In this paper we explore an approach where a decision maker is given prespecified attributes and then identifies her objectives. She assesses multiattribute models to predict performance levels on each objective and a preference model over these objectives. We use simulation to explore what happens when a decision maker applies this two-step approach to model the relationships between a given set of attributes and her objectives instead of attempting to directly estimate the attribute weights in a choice problem. These simulation results suggest that the explicit consideration of objectives results in less error in expressions of preference than the direct weighting of attributes unless the number of attributes and objectives in the decision context is small.