需求震盪下之產能擴充策略

Abstract

在近十年內，全球經濟頻繁地發生重大災變，如2008年金融海嘯危機以及2011年發生於日本東北的巨大震災，當此類需求震盪事件發生時，需求無預警地在極短時間內劇烈下跌，廠商不及反應而導致大規模的產能閒置並且產生鉅額損失，由於過去的擴充產能文獻僅處理到需求隨機變異的特性，既有的擴充產能方法已不足以處理動盪日益加劇的產業環境，產業亟需將需求震盪納入擴產決策考量；本研究在處理需求隨機變異特性以外，提出將需求震盪視為獨立的隨機事件，在此模型發展出擴產時點決策模型，情境分析結果顯示當產能壽命短、需求變異小或需求震盪顯著時，本擴產策略將產生較佳的績效表現，本文最後並提出整合兩擴產模型的選擇法則以因應不同的產業環境特性

Significant demand shocks can be found in historical demand data of most industries. The order quantities unexpectedly decrease a large scale within a short period of time. Because the capacity usually has a finite lifetime and is irreversible, the spare capacity makes a considerable loss of profit. The majority of capacity models in the literature use geometric Brownian motion to describe demand data, which consider all magnitudes of fluctuation as homogeneous demand variation. In contrast, we take demand shock as a contingent event which occurs stochastically with a constant decline rate. In this paper, we use exponential growth model superimposed with shock events to represent demand, and develop a one-time capacity expansion model. To compare the performance of this model with the one under GBM assumption, simulation is used in various scenarios of model parameters. Simulation results show that the model with shock events outperforms the equivalent GBM model when the industry environment includes a short capacity lifetime, small demand volatility or significant scope of demand shock. Finally, the importance of including demand shock into capacity expansion strategy is proved in this research.