Abstract
The bullwhip effect is defined as the distortion of demand information as one moves upstream in the supply chain, causing severe inefficiencies in the whole supply chain. Although extensive research has been conducted to study the causes of the bullwhip effect and seek mitigation solutions with respect to several demand processes, less attention has been devoted to the impact of seasonal demand in multi-echelon supply chains. This paper considers a simulation approach to study the effect of demand seasonality on the bullwhip effect and inventory stability in a four-echelon supply chain that adopts a base stock ordering policy with a moving average method. The results show that high seasonality levels reduce the bullwhip effect ratio, inventory variance ratio, and average fill rate to a great extent; especially when the demand noise is low. In contrast, all the performance measures become less sensitive to the seasonality level when the noise is high. This performance indicates that using the ratios to measure seasonal supply chain dynamics is misleading, and that it is better to directly use the variance (without dividing by the demand variance) as the estimates for the bullwhip effect and inventory performance. The results also show that the supply chain performances are highly sensitive to forecasting and safety stock parameters, regardless of the seasonality level. Furthermore, the impact of information sharing quantification shows that all the performance measures are improved regardless of demand seasonality. With information sharing, the bullwhip effect and inventory variance ratios are consistent with average fill rate results.
Highlights
A supply chain is defined as a system of suppliers, manufacturers, distributors, retailers, and customers where raw materials, finances and information flows connect participants in both directions
We adopt a simulation approach since we aim to study the impact of demand seasonality in a multi‐ echelon supply chain, which is a complex system to solve with analytical models
The results show that the bullwhip effect is present in all cases and the demand variability seems to increase geometrically across the supply chain, from the retailer to the factory
Summary
A supply chain is defined as a system of suppliers, manufacturers, distributors, retailers, and customers where raw materials, finances and information flows connect participants in both directions. The lack of coordination among supply chain members and the unavoidable demand uncertainty usually result in severe inefficiencies in supply chains An example of such inefficiency is the bullwhip effect, in which demand variability is amplified as one moves upstream in the supply chain. This can be explained by the tendency of supply chain members to adjust their inventory policies as new changes in demand are detected which might lead to the propagation of distorted information across the supply chain. Forrester [4] was one of the first to study this problem through a set of simulation experiments using system dynamics He concluded that the structure, policies and interactions within supply chains cause demand variability amplification. A number of researchers developed simulation games to illustrate the existence of the bullwhip effect as well as its negative effects in supply chains [5,6]
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