Optimization of EOQ Model for New Products Under Multi-Stage Adoption Process

Abstract

The available literature on new product sales growth models mostly ignores two important aspects of technology diffusion: diffusion of awareness and the actual adoption. This characteristic of technology adoption is extremely important from inventory management perspective as buying decision is often influenced due to time lag between information propagation and actual adoptions. As high-technology market is extremely unpredictable, interactions between technological evolutions and customer feedback effects play an important role in technology diffusion. The demand models mostly considered in inventory literature to develop economic order quantity (EOQ) model ignore this important element of technology diffusion. In this paper, we proposed an EOQ model for high-technology products by incorporating customer feedback effects along with market heterogeneity to optimize the total inventory cost. The demand model considered in the paper follows lifecycle phenomenon and is sensitive to unit selling price. To remove any ambiguity pertaining to costs, fuzzy nature of ordering and inventory carrying cost is considered in the paper.