ISSN:0894-3257    

DOI:10.1002/bdm.3960040202

出版商:John Wiley&Sons, Ltd.    

年代:1991

数据来源: WILEY

摘要:

AbstractDecomposition is a common strategy for dealing with the complexity of multiattribute decision problems. A cognitively demanding task is broken down into tasks requiring simpler, perhaps easier, judgments which can then be aggregated. But individual judgments can be inconsistent in systematic or random fashion and when aggregated there is the possibility of propagation of this inconsistency. In this paper inconsistency in the form of random error is investigated in the context of additive decomposition of multiattribute utility. The process of aggregation of random error is studied and a comparison made with random error in holistic estimates of multiattribute utility. Conditions under which decomposition improves the consistency of the multiattribute utility estimate are presented and discussed.

ISSN:0894-3257    

DOI:10.1002/bdm.3960040203

出版商:John Wiley&Sons, Ltd.    

年代:1991

数据来源: WILEY

ISSN:0894-3257    

DOI:10.1002/bdm.3960040204

出版商:John Wiley&Sons, Ltd.    

年代:1991

数据来源: WILEY

ISSN:0894-3257    

DOI:10.1002/bdm.3960040205

出版商:John Wiley&Sons, Ltd.    

年代:1991

数据来源: WILEY

ISSN:0894-3257    

DOI:10.1002/bdm.3960040206

出版商:John Wiley&Sons, Ltd.    

年代:1991

数据来源: WILEY

摘要:

AbstractAn important part of decision making in many contexts is the estimation of numerical values for uncertain quantities, such as the projected costs of a development project or the number of people who use illegal drugs. In previous research, estimation accuracy for such quantities was found to be improved by algorithmic decomposition. The present study examines (a) the estimation performance of individuals using extended algorithms in which component estimates are produced by multiple methods, and (b) the effectiveness of algorithms produced by individuals after receiving training in algorithmic decomposition. The extended algorithm approach yielded some improvement in estimation performance. Subjects trained in algorithmic decomposition were able to produce algorithms, the effectiveness of which were dependent upon the presence of misinformation about components of the quantity to be estimated. The results are discussed in terms of the information processing demands imposed by detailed problem structuring.

ISSN:0894-3257    

DOI:10.1002/bdm.3960040207

出版商:John Wiley&Sons, Ltd.    

年代:1991

数据来源: WILEY

摘要:

AbstractAlgorithmic decomposition is a way of extending thinking. It will help when thinking is otherwise poor, and it may hinder when thinking is otherwise adequate. It may help decision making more than it helps numerical estimation.

ISSN:0894-3257    

DOI:10.1002/bdm.3960040208

出版商:John Wiley&Sons, Ltd.    

年代:1991

数据来源: WILEY

ISSN:0894-3257    

DOI:10.1002/bdm.3960040209

出版商:John Wiley&Sons, Ltd.    

年代:1991

数据来源: WILEY

ISSN:0894-3257    

DOI:10.1002/bdm.3960040210

出版商:John Wiley&Sons, Ltd.    

年代:1991

数据来源: WILEY

摘要:

AbstractSome decision analysts recommend reserving their models for careful, complete study of complex problems. Others believe simple problem analyses provide the greatest gains. To clarify these issues, I tested: (1) whether simple published analyses compared to complex ones, produced results as non‐intuitive; and (2) whether non‐intuitiveness represented analytic gain (or equivalently, intuitive loss). Very limited data also examined (3) the gain from adding model intricacy for a given problemvs.selecting more complex problems for analysis.To assess two non‐intuitiveness measures, 75 subjects (33 physicians and 42) non‐physicians stated their intuitive preferences in40(22 published and 18 unpublished) medical dilemmas. For both physicians and non‐physicians, simpler models (those with lees than 30 terminal branches in the decision tree) had about one third the non‐intuitiveness of more complex ones. Three tests also supported the premise that analyses outperform intuition, therefore that on average the formers' non‐intuitiveness reflects less analytic gain. In addition, for different models of the same problem, tree complexity did not correlate with gain. Thus, simpler trees may not generally gain less because they inadequately describe problems. Instead, simpler analyses may represent simpler problems, with more similar intuitive and formal solutions. If so, these findings may help us avoid some costly but unnecessary si

ISSN:0894-3257    

DOI:10.1002/bdm.3960040211

出版商:John Wiley&Sons, Ltd.    

年代:1991

数据来源: WILEY