Dependency and time delay based innovation adoption modeling

Abstract

Diffusion modeling has become the driving force for planning and executing marketing strategies in today’s ever changing scenario. The need for understanding this attribute is rapidly increasing and has been acting as a helping hand in dealing with the fluctuating adoption behavior of customers among different sectors of society. This particular work aspires to model innovation adoption by considering the awareness process and adoption process as two different scenarios. After recognizing the time delay prospect in both the stages of the adoption process, the dynamic time delay approach is proposed to draw attention towards the actual adoption of an innovation. The time lag functions are identified corresponding to various distributions to attain the actual adaptability of product in the market. The validation and reliability of the proposed models have been done on two real-life sales data sets. Furthermore, the results of the data analysis reveal that the time delay effect plays a major role in the adoption process.