Measure of bullwhip effect in supply chains: The case of high order autoregressive demand process

Abstract Bullwhip effect – the phenomenon in which variance of demand is amplified when moving upstream – has attracted the attention of many researchers for the last few decades. Although the main sources that cause bullwhip effect have been identified, quantifying the bullwhip effect still remains a challenge. In the past, measuring the bullwhip effect for supply chains with autoregressive demand process has been conducted by some researchers. However, most past researches focused mainly on the simple AR(1) model. In many practical situations, autoregressive models with higher order should be employed because they might better represent the demand process. Up to now, very little effort has been spent on this matter. Therefore, this research is conducted to fill this gap by first dealing with AR(2) demand process and investigating the behavior of the developed measure with respect to autoregressive coefficients and order lead-time. Extension to the general AR( p ) demand process is then considered.