Big data and supply chain decisions: the impact of volume, variety and velocity properties on the bullwhip effect
通过仿真分析大数据三个属性（速度、数量、多样性）对缓解供应链牛鞭效应的潜力，发现速度属性效果最佳，为供应链管理应用大数据提供依据。
The bullwhip effect is causing inefficiencies in today’s supply chains. This study deals with the potential of big data on the improvement of the various supply chain processes. The aim of this paper is to elaborate which characteristic of big data (lever) has the greatest potential to mitigate the bullwhip effect. From previous research, starting points for big data applications are derived. By using an existing system dynamics model, the big data levers ‘velocity’, ‘volume’ and ‘variety’ are transferred into a simulation. Overall, positive impacts of all the big data levers are elaborated. Findings suggest that the data property ‘velocity’ relatively bears the greatest potential to enhance performance. The results of this research will help in justifying the application of big data in supply chain management. The paper contributes to the literature by operationalising big data in the control engineering analyses.