Integrating Bass Innovation Diffusion into Inventory Modeling: A Lifecycle Optimization Approach

Abstract

Inventory management for innovative products presents unique challenges because demand is not constant but evolves as consumers adopt new technologies. Traditional inventory models fail to capture this dynamic adoption behavior. This research paper develops a mathematical inventory model that integrates the Bass innovation diffusion model into the inventory decision framework. By explicitly embedding the coefficients of innovation and imitation into demand functions, the model accounts for the time-dependent adoption process. The objective is to minimize the total cost consisting of ordering, holding, shortage, and obsolescence costs under diffusion-driven demand. Analytical derivations, supported by numerical illustrations, demonstrate how adoption dynamics significantly influence inventory decisions. Results show that firms ignoring diffusion effects either overstock in early periods or understock during growth phases. This research paper provides both a theoretical contribution by extending inventory models with diffusion theory and practical insights for firms dealing with high-tech or short lifecycle products.