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Showing papers by "Ward Edwards published in 1981"


Journal ArticleDOI
TL;DR: In this article, rank weighting of dimensions has been examined in three multi-attribute decision-making studies using four rank weight weighting techniques as well as equal weights in order to examine the practical significance of this sensitivity.

378 citations


01 Jun 1981
TL;DR: It is found that subjects feel better taken care of when more attributes are included in the analysis, but that subjects' holistic ratings are better accounted for by analyses with smaller rather than larger number of attributes.
Abstract: : The state-of-the-art in decision software is at a level of data storage, display, and computation as an aid to a sophisticated user. Almost certainly, the emerging generation of decision software will be designed to perform a larger range of analyst functions. We have focused on two potential problems challenging the computerization of decision analysis, and on assessing the extent to which these problems can be over come. First, to what extent can the often ill-defined art of structuring be transformed into software; and secondly, to what extent is past consumers' satisfaction with decision analysis a function of the formal methods and procedures of the theory and rationale of decision theory, and to what degree do other factors such as personal interaction and the establishment of a rapport account for client approval? We compared multiattribute utility analyses of personal decision problems of undergraduates performed by a human analyst vs. those performed by a 'stand-alone' software package, Multi Attribute Utility Decomposition (MAUD 3). Although subjects overwhelmingly yielded more favorable reports for the analyst session than for the MAUD 3 session, agreement with and acceptance of the analyst and MAUD 3 results (implied ordering and most preferred alternative) did not differ. We did find that subjects feel better taken care of when more attributes are included in the analysis, but that subjects' holistic ratings are better accounted for by analyses with smaller rather than larger number of attributes. (Author)

5 citations