This study attempts to determine the relative contribution of each of the causes of the bullwhip effect and to identify which causes of the bullwhip effect have relatively significant impacts on the variability of orders in supply chains.
Computer simulation models are developed. A fractional factorial design is used in collecting data from the simulation models. Statistical analyses are conducted to address the research objectives.
When all of the nine possible causes of the bullwhip effect are present in the simulation models, the following six factors are statistically significant: demand forecast updating, order batching, material delays, information delays, purchasing delays and level of echelons. Among these six factors, demand forecast updating, level of echelons, and price variations are the three most significant ones.
Simulation models for the beer distribution game are developed to represent supply chains. Different supply chain structures can be constructed to examine the causes of the bullwhip effect.
In order to mitigate the bullwhip effect, supply chain managers need to share actual demand information and coordinate production and distribution activities with their partners.
This study measures the relative contribution of each of the causes of the bullwhip effect and provides evidence that transparent and accurate information flow and supply chain coordination could be a key to reduce the amplification of demand in supply chains.
