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A general structural equation model for representing consumer response to innovation is derived and illustrated. The approach both complements and extends an earlier model proposed by Hauser and Urban. Among other benefits, the model is able to take measurement error into account explicitly, to estimate the intercorrelation among exogenous factors if these exist, to yield a unique solution in a statistical sense, and to test complex hypotheses (e.g., systems of relations, simultaneity, feedback) associated with the measurement of consumer responses and their impact on actual choice behavior. In addition, the procedures permit one to model environmental and managerially controllable stimuli as they constrain and influence consumer choice. Limitations of the procedures are discussed and related to existing approaches. Included in the discussion is a development of four generic response models designed to provide a framework for modeling how consumers behave and how managers might better approach the design of products, persuasive appeals, and other controllable factors in the marketing mix.
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Richard P. Bagozzi (1983) studied this question.
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