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As an academic discipline in management, supply chain management is a sophisticated branch that offers little control (Katsaliaki et al., 2014). Inadequate understanding of relevant environmental issues and uncertainty factors could affect one’s order placement strategies or even the overall performance of the entire supply chain (Chaharsooghi et al., 2008). Forrester (1961) used a dynamic system to simulate the process of supply chain management and found that given the non-transparent nature of information, upstream vendors tend to amplify the potential customer demand and widen the gap between the forecasted demand and actual demand. In other words, vendors higher up in the supply chain would be susceptible to greater impacts of this discrepancy. Just like the cracking of a whip, the degree of fluctuation towards the tip of the whip would be the greatest (Lee & Wu, 2006). This phenomenon is the Bullwhip effect – one of the most well-known phenomena in supply chain management (Lee et al., 1997).
The bullwhip effect is a common issue in supply chain management and takes place mainly because the numerous uncertain factors in supply chain management (e.g., errors in downstream manufacturers’ orders, delayed information from supply chain partners) give rise to information asymmetry. In practice, for example, a low demand from a most downstream consumer may, as a result of information distortion, cause a most upstream factory to produce an excessively large quantity of products. This phenomenon is analogous to the movement of a bullwhip: the amplitude of the bullwhip is the largest at the tail end. While customers’ order quantities and demands are low, suppliers’ order quantities and demands increase toward the upstream end of the supply chain such that surplus stock emerges after each role in the supply chain has their order filled by their immediate upstream supplier.
The Beer Game developed by Sterman (1989) simulates the process of production and distribution and enables learners to have an extensive experience on the formation and impact of the bullwhip effect (Geary et al., 2006). Previous studies often used the Beer Game for the simulation of supply chain management and explored the relationship between supply chain management and bullwhip effect (Cantor & Macdonald, 2009) and found the behavior of decision-making to be a critical factor that creates the bullwhip effect (Croson & Donohue, 2006). Chaharsooghi et al. (2008) also used the Beer Game as a tool to determine if the Q-learning algorithm based reinforcement learning model were able to enhance learners’ order management for supply chains. Similarly, Coppini et al. (2010) utilized a scenario of bullwhip effect through the Beer Game and proposed a new approach of balancing inventory fluctuation to overcome the issue of constant customer demand amplification by upstream vendors.