Impacts of Sharing Demand Forecast Information in Seasonal Markets on Supply Chain Performance (ID: CE006)

摘要

This paper discusses the impacts of sharing forecast information about seasonal market demands on supply chain performance. A simulation approach is adopted, considering a 3-echelons distribution supply chain consisting of retailers, distributors and a capacitated manufacturer as a multi-agent system with constituent enterprises as individual agents. Three forecasting models are studied in this simulation. They include 30-period moving average (MA30), 15-period moving average (MA15), and Exponential smoothing model (ES). The experimental results show significant values of sharing forecast information about seasonal market demands on the performances of the entire supply chain and individual agents. However, the benefit to upstream agents (e.g. manufacturer) is not as large as that to downstream agents (e.g. retailers). An important implication from this study is that the supply chain should not only use demand forecasts but also increase the forecasting accuracy in order to gain the best benefits.