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A Graph Theory Approach to Comparing Consumer Information Processing Models

  • Computer Science


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.

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