Modelling Innovation Diffusion Using Optimized Marketing Mix Strategies

Abstract

In this paper, we studied the primary limitation of the original Bass Diffusion Model by developing an extension of the Generalized Bass Model (GBM) that introduces key marketing mix variables into the model. Since innovation and imitation are not the only drivers of product adoption given the competitive and technologically advancing nature of markets, the study presents a time-varying marketing influence function as a linear combination of advertising expenditure, customer service quality, product performance, innovation capability, and extension of distribution. Built multiplicatively into the equation of diffusion, this function is designed to reflect the accelerating influence of marketing activities on adoption rates. The study also utilizes Linear Programming (LPP) to maximize marketing impact function under practical constraints, allowing for the computation of optimal resource allocation between marketing variables. This upgraded model is a marketing planning support tool, performance measurement tool, and resource allocation tool, especially in sectors such as smartphones, electric vehicles, and consumer electronics, enabling firms to determine high-impact areas for investments and develop effective marketing campaigns for maximizing product diffusion effect.