A novel Bass-type model for product life cycle quantification using aggregate market data

Product Life Cycle (PLC) is a widely accepted concept that has been given significant attention in operations management and marketing literature. However, its quantification remains a major challenge. This study aims to develop a unique and original analytical model for quantifying PLCs using aggregate market data. The Bass diffusion model is used to forecast consumers׳ first purchases of the product. Next, the Novelty–Loyalty Based Consumer Utility (NLBCU) theory, which has a confirmed neuropsychological basis, is used to model repeat (or replacement) purchases. The unique contribution of this work is that it synthesizes the prevailing innovation diffusion theory and the NLBCU theory to provide a distinct, dynamic and endogenous perspective on consumer purchasing behavior across the entire PLC. The model׳s advantages include its simple mathematical formulation, its minimal use of data and its harmony with the predominating ideas of the innovation diffusion literature. Through simulation studies and empirical investigations, the descriptive power and data-fitting performance of the model are demonstrated. •Developing an analytical model for Product Life Cycle quantification.•Using Bass model to predict the first purchases.•Using the Novelty–Loyalty Based Consumer Utility theory to model repeat purchases.•Conducting simulation studies to derive various types of product lifecycle.•Empirical studies show good data fitting capacity.