Search

This paper is concerned with optimizing the configuration of a set of platform products and the associated supply chain consisting of one manufacturer and multiple suppliers using a three-move dynamic game-theoretic approach. The variants in the product family share a common platform for developing/configuring variant modules which are substitutable in the sense that high-end module options can functionally replace low-end ones at higher prices. As the customer in the supply chain, the manufacturer takes its leading role by making the first move to give decisions on platform products development (PPD) and supplier selection. The concerned suppliers make the second move to optimize their decisions including price discounts and their ordering policies. The manufacturer finishes the game by taking the last move to make his ordering decisions. The ranges of the rational reactions for the players are derived from the analyses of their payoff models, and an enumerative algorithm is developed to find the subgame perfect equilibrium of the game through the technique of backward induction. The game model and the proposed solution procedure are illustrated through a series of simulation experiments and sensitivity analyses using a numerical example. The results have allowed us to draw some meaningful interpretations and useful managerial insights. The use of platform commonality and modularity has been found generally beneficial not only to the supply chain as a whole but also to individual players that are eventually configured into the game. Flexibility of the suppliers' capability is also found to affect the PPD decisions. Index Terms--Commonality, configuration game, game theory, mass customization, modularity, platform product, supply chain.

Byline: George Q. Huang, Xin Yan Zhang, Victor H.Y. Lo This paper deals with the optimal configuration of a multi-stage supply chain for multiple products. We develop a mathematical model for two situations: a single supply chain configured for multiple products sharing a common platform, and multiple supply chains separate for individual products. The model is applied and solved for a case study of a notebook computer manufacturer to study two impacts of product platform commonality. One is the robustness of the supply chain performance against the demand variability and the other is the improvement of the supply chain performance by taking advantage of quantity discounts offered by suppliers. The experimental results have found that the presence of platform commonality encourages the manufacturer to take advantage of the quantity discount to improve its performance. Another important finding is that platform commonality not only improves the supply chain performance (total cost) but also its robustness against the demand variability.