A Statistics Empirical Study On The Collaborative Replenishment Management In The Retail Industry

In recent years, the retail industry of China is developing rapidly. Lots of foreign chain retail enterprises come to China and provide some ideas for the development of Chinese retail enterprises. Price competition is fierce in the current retail market, every enterprise is considering how to maintain the stability of supply and reduce costs. As a typical representation of the sales industry, the retail industry pays more and more attention to control and manage the process of purchasing and the inventory, that’s replenishment management. The selection of the replenishment strategies related to the smooth operation and the maximum profit, it is significant. As a new idea of the supply chain management, CPFR includes the replenishment management, the production management and the sales management. It was put forward by many large enterprises since it appeared. But so far, there is not much researchs on the joint replenishment management under CPFR, especially in empirical research. It is difficult to find relevant contents which talks about CPFR application. Therefore, if we can explore more evidence on the collaborative replenishment management and find more ideas, we will improve the imperfect joint replenishment system and reduce the costs, we will promote the development of Chinese retail industry in the future.In this paper, the joint replenishment decision-making process under the CPFR is divided into three stages, each stage of the process is designed by using relevant statistical methods. First of all, we use the model of time series data to solve the problems of joint forecasting. Then we make some statistical indicators and a decision tree to solve the replenishment mode decision problems. Finally we solve the problems of inventory management by using a panel data model. These three stages almost covered all the decision contents which are needed in joint replenishment process of supply chain, the statistics ideas and methods we used to analyze is more scientific and accurate compared to the traditional management mode.