Innovation characteristics and their influence on the rate of diffusion

Prior research suggests that several factors influence the rate in which a new product becomes diffused. Those include channels of communication, time, social networks in the market, and the characteristics of the innovation. Together, these factors play some role in determining the rate of innovation adoption. Yet, to date no research has empirically shown how an innovation's characteristics contribute to the process. The attempt made here is to measure the relationships between innovation characteristics and the parameters used to model diffusion over time.;Since little is known from an empirical perspective regarding how specific innovation characteristics affect the pattern and rate of innovation diffusion this research adds to both the new product development as well as diffusion literatures by establishing a link between innovation characteristics diffusion. A challenge of today's forecasters is to make pre-launch estimates of key diffusion model parameters such as p and q found in the Bass Model. Since the established method of analogy by aspects is currently used by many firms, a new characteristics-based method would provide a competing technique of prediction. These two methods used together are expected to yield an overall better prediction than either one by itself.;By using a jackknife bootstrapping process to regress the variables of interest on Bass Model diffusion parameters it is shown in this research that innovation characteristics do in fact explain variation in diffusion model parameters. The predictive power of innovation characteristics is further illustrated in a three product example using four competing models to estimate diffusion parameters.;In sum several major accomplishments are made in this research. First, a validated set of scales which measures 17 innovation characteristics is developed. Second, the introduction of 13 new products with estimated diffusion parameter values is introduced to the literature. Third, this research is the first to empirically establish the relationship between innovation characteristics and aggregate-level diffusion parameters. Finally, this research illustrates a meaningful approach to estimating new-product sales prior to launch by the development of several deterministic models each of which was used to estimate product sales form three products.