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The impact of task complexity on information use in multi‐attribute decision making
Author(s) -
Timmermans Danielle
Publication year - 1993
Publication title -
journal of behavioral decision making
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 76
eISSN - 1099-0771
pISSN - 0894-3257
DOI - 10.1002/bdm.3960060203
Subject(s) - task (project management) , process (computing) , selection (genetic algorithm) , computer science , psychology , artificial intelligence , economics , management , operating system
This study presents a process analysis of multi‐attribute decision making. The decision problems concerned the selection of the most suitable candidate for a job opening. The problems varied in terms of complexity, i.e. the number of candidates and the number of attributes used to describe these alternatives. Results show that with an increasing number of alternatives, subjects ( N = 48) used fewer attributes for the evaluation of alternatives, and made, on average, less references to the alternatives. The type of judgment most often used was absolute dimensional (comparison of an attribute to an absolute standard) and was used more often at the beginning than toward the end of the decision process. Overall, judgments were predominantly positive. The percentage of positive judgments decreased with increasing complexity, and toward the end of the decision process. Significantly more judgments, particularly positive ones, concerned the finally chosen alternative as compared to the rest of the alternatives. Finally, analysis of subjects' usage of decision rules revealed that increasing the number of alternatives resulted in an increasing use of elimination strategies. Implications of these findings for the design of decision aids will be discussed.