Robustness and information levels in case-based multiple criteria sorting |
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Authors: | Rudolf Vetschera Ye Chen Keith W Hipel D Marc Kilgour |
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Institution: | aDepartment of Business Administration, University of Vienna, Bruenner Strasse 72, A-1210 Vienna, Austria;bCollege of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;cDepartment of Systems Design Engineering, University of Waterloo, Waterloo, Ontario, Canada N2L 3G1;dDepartment of Mathematics, Wilfrid Laurier University, Waterloo, Ontario, Canada N2L 3C5 |
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Abstract: | Case-based preference elicitation methods for multiple criteria sorting problems have the advantage of posing rather small cognitive demands on a decision maker, but they may lead to ambiguous results when preference parameters are not uniquely determined. We use a simulation approach to determine the extent of this problem and to study the impact of additional case information on the quality of results. Our experiments compare two decision analysis tools, case-based distance sorting and the simple additive weighting method, in terms of the effects of additional case information on sorting performance, depending on problem dimension – number of groups, number of criteria, etc. Our results confirm the expected benefit of additional case information on the precision of estimates of the decision maker’s preferences. Problem dimension, however, has some unexpected effects. |
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Keywords: | Multiple criteria decision analysis Multiple criteria sorting Case-based preference elicitation Robust analysis Experimental test |
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