Modeling innovation adoption incorporating time lag between awareness and adoption process

Demand forecasting is an arduous task in today’s competitive world. The changing environment of market structure demands firms to be more cognizant about the customers’ stipulation before the successful introduction of an innovation into the market. Only after being satisfied by the characteristics of the innovation, the potential adopters get positively motivated to buy the product. There is a finite time lag in the adoption process; from the moment potential buyers get information about the innovation and the time they make the actual purchase. Using this fundamental of time lag we have proposed a framework of innovation diffusion where the final purchase is happening in number of stages. Distributed time lag approach methodology has been utilized to capture the time delay between customer’s motivation and its final adoption. In this approach, the contributions of time delay are ascertained as a weighted response measured over a finite interval of past time through appropriate memory kernels. To cater actual adoption process, certain mathematical models with the help of integro-differential equations have been formulated and solved through Laplace transforms. Furthermore, we have validated the model on the real life sales data set.