Comparison of innovation diffusion models: A case study on the DRAM industry

The development of technology accelerates the life cycle of products and the rate of product substitution. Dynamic random access memory (DRAM), which is characterized by generation substitution, is an innovation in technology development that enhances competitive capabilities. In this study of the DRAM industry, the Gompertz model, traditional logistic growth model, Norton and Bass model, and fuzzy piecewise logistic growth model are applied to predict the growth trends of eight generations of the DRAM market. The results show that only the fuzzy piecewise logistic growth model and the Norton and Bass model can effectively forecast the growth trends of coming generations in the DRAM industry. Of these two models, only the fuzzy piecewise logistic growth model that detects change points can be used to reasonably explain the phenomenon and status of generation replacement in the DRAM industry at particular times, and provide an overview of the market situation.