THE INNOVATION DIFFUSION PROCESS IN A HETEROGENEOUS POPULATION: AN ANALYTICAL MODEL BASED ON AN INDIVIDUAL LEVEL APPROACH (FORECASTING, INFORMATION INTEGRATION, BAYESIAN LEARNING, ADOPTION)

The pattern of market penetration of an innovation and the factors underlying the diffusion process have been an important subject of study in marketing. This dissertation develops an analytical model of the innovation diffusion process in a heterogeneous population, applicable for high-involvement innovations that are durable in nature. The model employs a Bayesian decision theoretic framework to predict timing of adoption at the individual level, incorporating a potential adopter\u27s preference structure and the dynamics of uncertain perceptions about the innovation. Individual level predictions are then aggregated to yield the penetration curve. In particular, the analytical development of the model considers heterogeneity with respect to initial perceptions, attitude toward risk, susceptibility to information, and the trade-off between price and performance. The impact of variability in information about the innovation\u27s performance is captured by modeling an individual\u27s path to adoption as a stochastic process. We develop a parsimonious basis for classifying potential adopters in terms of their relative timing of adoption. The aggregate-level diffusion model is very flexible in its ability to accommodate a wide variety of possible patterns of diffusion. The model is employed to investigate the effects of heterogeneity in the population, the true performance of the innovation, and the pattern of information on the rate of diffusion and the shape of the diffusion curve. A pilot study is conducted to illustrate an approach to calibrating the model and to provide a preliminary test of its key implications. The results provide tentative support for the predictive performance of the model, and encourage a full-scale application. The model is next employed to derive normative implications for promotional policy. It is shown that, in general, promotional expenditures should decline over time. The model also provides guidelines for selective targetting of promotional effort. The extended model (considering several non-price attributes) provides a basis for determining the attribute(s) to be emphasized in the firm\u27s communication program. Potential managerial applications of the model include (a) pre-launch prediction of the penetration curve, (b) segmentation of the potential adopter population, and (c) planning communication strategy