Weakening the Bullwhip Effect in the Supply Chain Based on Data Fusion

Abstract

In the increasingly competitive society, as the third profit center of the enterprise, the supply chain makes scholars and industry related with the supply chain more interested in the study of relevant issues. Some scholars believe that the application of predictive analytics could have a tremendous impact on the supply chain. The uncertainty of supply chain demand and bullwhip effect challenge the supply chain. Data fusion can effectively reduce the uncertainty of demand and amplification effect. In this study, a new conceptual model was established on the traditional supply chain based on data fusion. Results show that the conceptual model refers to data fusion for solving the uncertain and inconsistent multi-source data by Bayesian estimation to provide reasonable decision information for supply chain managers.