Dynamic production-pricing strategies for multi-generation products under uncertainty

Due to rapid advances in technology and design, firms periodically release new generations of electronic products such as mobile phones and computers. In order to increase product variability, firms may wish to develop a multiple-generation product line rather than replace the older versions with new ones. However, when multiple generations are available in the market, different generations compete with each other as well as other products in the market. Firms need to take joint decisions for the purpose of inventory management and dynamic pricing of multiple generations to tackle impact of uncertain demand and market competition. In this paper, we present a dynamic joint production-pricing decision model to obtain optimal strategies for a firm selling multiple generations of a product. We account for the internal competition among multiple generations by evaluating customer choices. In order to tackle a curse of dimensionality, we introduce a forward dynamic programming approach for approximately solving the joint production-pricing problem. We also propose a two-stage heuristic algorithm as an alternative solution approach. Different pricing rules determined from the abridged model and a price list derived by theoretical bounds are integrated to improve further computational performance of the solution approaches. We design computational experiments to illustrate effectiveness and efficiency of these approximate methods and show the benefit of joint decision-making process in multi-generation product line.