Financial Performance and Beer Distribution Game with Competition: Comparison of Supply Chains Without Strategy, Simple Moving Average and Single Exponential Smoothing

Abstract

Background: Supply chain management is challenged by demand uncertainty, inventory inefficiency, and rising operational costs. Existing Beer Distribution Game (BDG) studies generally overlook competitive dynamics and consumer trust considerations.

Objective: This study compares the financial performance of BDG scenarios using no forecasting, SMA, and EMA strategies under competitive conditions and evaluates their impact on consumer shifts.

Methods: A quantitative simulation-based experimental approach was employed using a modified Beer Distribution Game model developed in AnyLogic. The model incorporated consumer trust dynamics and competition mechanisms. Three forecasting scenarios were tested through 5,000 simulation replications. Financial performance was measured using total operational costs across retailer, wholesaler, distributor, and factory units. Data were analyzed using one-way ANOVA, followed by Bonferroni and Games-Howell post-hoc tests at a significance level of 0.05.

Results: The results revealed significant differences among the three forecasting scenarios. The Single ES (EMA) strategy achieved the lowest average total operational cost (USD 1,163.07), significantly outperforming SMA (USD 1,771.21) and the no-strategy scenario (USD 1,810.81). EMA consistently reduced costs across all supply chain units, including retailer, wholesaler, distributor, and factory levels. However, EMA also generated the highest average consumer shift rate (32.90%), indicating a trade-off between cost efficiency and customer retention. The findings further suggest that adaptive forecasting improves supply chain stability and partially mitigates the bullwhip effect under competitive conditions.

Conclusion: EMA offers superior cost efficiency, but should be complemented by customer retention strategies to ensure sustainable performance.