On the strategy of supply chain collaboration based on dynamic inventory target level management: A theory of constraint perspective

Abstract

After the financial tsunami in 2008, how to adjust the target inventory level dynamically and instantly in order to reduce the risk that an enterprise encountered in a rapid demand changing market has become a crucial issue in the field of supply chain management. This paper explores the strategies of supply chain collaboration by utilizing theory of constraint to achieve the goal of adjusting the target inventory level dynamically. Three time-series-data-mining techniques – Sequential Probability Ratio Test (SPRT), CUSUM chart and Auto-regression Test (AR(1)) are used to detect the timing of market demand change. The results are used to adjust the target inventory level. Simulation techniques are used to explore the relative efficiency of the demand-change detection for the three methods. The techniques are also used to explore the effectiveness of various inventory management strategies on inventory performance based on the three demand change detection methods.