Unmanned Retail’s Distribution Strategy Based on Sales Forecasting

With the increasing development of mobile technology and popularity of `New Retail' concept, more and more venture capitalists have been chasing investment opportunities in the unmanned retail business, such as F5 future store, Xiaomai, Xingbianli, CityBox, also and e-commerce firms Alibaba Group Holdings and JD.com. Currently the main forms of unmanned retail are smart vending machines, unmanned convenience stores, and unmanned smart shelves in offices. Additionally, other concepts, such as unmanned cafes and bookstores, continue to emerge. These forms have a great advantage: with the help of new technologies, the cost of unmanned retail is much lower than that of traditional retail forms. However, how to formulate an effective replenishment and distribution strategy is the biggest operational problem, also is the main research question of this paper. Firstly, this paper forecasts the purchase demand of each node based on the analysis of the nodes' historical sales data, and then according to the demand forecast results, optimizes the distribution routes to effectively reduce transportation costs and achieve supply chain optimization.