### On Attribute Weighting in Value Trees (1998)On Attribute Weighting in Value Trees (1998)

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 Author Pöyhönen, Mari Source CiteSeerX Content type Text File Format PDF Language English
 Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science Subject Keyword Decision Maker ♦ Large Group ♦ Response Scale ♦ Multiattribute Value Tree Analysis ♦ Weight Change ♦ Structural Variation ♦ Preference Elicitation ♦ Simple Multi Attribute Rating Technique ♦ Attribute Weighting ♦ Attribute Weight Change ♦ Numerical Preference Statement ♦ Different Attribute Weight Elicitation Method ♦ Different Weight ♦ Verbal Expression ♦ Direct Weighting ♦ Value Tree Change ♦ Way Decision Maker ♦ Analytic Hierarchy Process ♦ Attribute Weight ♦ Many Different Problem ♦ Swing Weighting ♦ Theoretical Principle ♦ Value Tree ♦ Different Weight Elicitation Method ♦ Ordinal Information ♦ Individual Behavior Description The thesis focuses on the biases appearing when decision makers are asked to give numerical preference statements on attribute weights in multiattribute value tree analysis (MAVT). The thesis focuses on two problems. First, different attribute weight elicitation methods yield different weights although they are based on the same theoretical principles. Second, the attribute weights change when the structure of a value tree is varied. We run two experiments to study the differences between five different weight elicitation methods (Analytic Hierarchy Process, direct weighting, Simple Multi Attribute Rating Technique, SWING weighting, and tradeoff weighting) and to study how verbal expressions are used in preference elicitation. The weighting methods do yield different weights. These differences originate from the way decision makers restrict their responses depending on the numbers that the methods explicitly or implicitly propose. With the biases related to the structural variation of value trees we first point out that earlier experiments are insufficient because they have drawn conclusions of individual behavior based on averages over large group of subjects. In an experiment we then show that the weights change when the structure of a value tree changes because the subjects again give numbers to describe their preferences so that they clearly favor some response scales. We propose, based on the results from our experiments and earlier observations, that two same origins for many different problems in attribute weighting are that the decision makers give numbers that reflect ordinal information on preferences only and that the weights are normalized to sum up to one. The decision makers' interpretation of the numbers that they use differs from the as... Educational Role Student ♦ Teacher Age Range above 22 year Educational Use Research Education Level UG and PG ♦ Career/Technical Study Learning Resource Type Article Publisher Date 1998-01-01 Publisher Institution Systems Analysis Laboratory, Research Report, A73