A comparative study on the performance of timing and sizing models of capacity expansion under volatile demand growth and finite equipment lifetime

摘要

Competition in global supply chains has become so severe that many suppliers in the high-tech manufacturing industry must shoulder high risk but have negative return on assets. While the literature is abundant with capacity models, there is a need for further research on capacity investment, especially in selecting and correctly using the right model. For a firm with lasting manufacturing operation, capacity expansion has two aspects: the timing and sizing of each expansion. The aim of a sizing method is to determine the scale of capacity expansion and that of a timing method is to determine the right time of the next expansion. The majority of capacity models in the literature can be classified as sizing models. In contrast, timing models have not received as much attention. In this paper, we compare the performance of the two types of models under volatile demand growth in order to find out the more appropriate type for the high-tech manufacturing environment. An empirical analysis of semiconductor demand is first presented. We find that the geometric Brownian motion process is appropriate for characterizing the volatility of demand growth. Based on this finding, simulation is used to compare a canonical timing and a canonical sizing models in various scenarios of demand growth, demand volatility and profit margin. We also advocate using profitability as a capacity investment criterion, in addition to the demand-satisfying criterion that is commonly used in the literature. Simulation results show that the timing model outperforms the sizing model. Finally, the behavior of the timing model is characterized as an aggressive method that can be used to exploit demand volatility for an advantage.