A model of the innovation diffusion process is developed using a micromodeling approach that explicitly considers the determinants of adoption at the individual level in a decision analytic framework, and incorporates heterogeneity in the population with respect to initial perceptions, preference characteristics, and responsiveness to information. The micromodelling approach provides a behavioral basis for explaining adoption at the disaggregate level and the consequent pattern of diffusion at the aggregate level. The analytical implications of the model are compared and contrasted with the traditional, aggregate-level, diffusion models. An advantage of our approach is its micro-theory driven flexibility in accommodating various patterns of diffusion. Examples are provided of conditions under which the model yields diffusion patterns identical to those of some well-known aggregate models. A pilot study is reported, outlining procedures for data collection and estimation of the individual-level parameters, and providing a preliminary test of the predictive performance of the model. Measurement of the individual parameters prior to product launch enables potential applications of the model for segmentation of the target population in terms of their expected adoption times.
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