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A Graph Theory Approach to Comparing Consumer Information Processing Models

A Graph Theory Approach to Comparing Consumer Information Processing Models This study argues the need for, and then develops, some graph theoretic approaches for comparing complex information processing models of individual decisions. Two similarity coefficients are proposed, and a coefficient based on path and reachability structure is shown to be preferable. Some properties of this coefficient are outlined, as well as a computational method. The coefficient is applied to actual information processing models of consumer choice and stock selection. The results of this application are interpreted for insights into process structure, stability of decision processes over time, and possibilities of developing process-oriented typologies. Finally, problems and prospects for this type of approach are assessed. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Management Science INFORMS

A Graph Theory Approach to Comparing Consumer Information Processing Models

Management Science , Volume 18 (4-part-ii): 15 – Dec 1, 1971
16 pages

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Publisher
INFORMS
Copyright
Copyright © INFORMS
Subject
Research Article
ISSN
0025-1909
eISSN
1526-5501
DOI
10.1287/mnsc.18.4.P114
Publisher site
See Article on Publisher Site

Abstract

This study argues the need for, and then develops, some graph theoretic approaches for comparing complex information processing models of individual decisions. Two similarity coefficients are proposed, and a coefficient based on path and reachability structure is shown to be preferable. Some properties of this coefficient are outlined, as well as a computational method. The coefficient is applied to actual information processing models of consumer choice and stock selection. The results of this application are interpreted for insights into process structure, stability of decision processes over time, and possibilities of developing process-oriented typologies. Finally, problems and prospects for this type of approach are assessed.

Journal

Management ScienceINFORMS

Published: Dec 1, 1971

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