| As the income level of residents continues to increase,people are paying more and more attention to pursue high quality life.The sense of ceremony in holidays and anniversaries has become increasingly prominent in people's tendencies to consumption.In the report of the 19 th National Congress of the Communist Party of China,General Secretary Xi Jinping proposed the Belt and Road Initiative,which intended to foster new growth points and new growth drivers in medium-to high-end consumption,modern supply chain and other fields.Under the circumstances,many new sales modes have emerged,due to the Internet technology adopted by the catering industry or even the whole fast-moving consumption industry.These modes have largely transformed traditional retail modes in the catering business and enterprises are forced to take more effective modes of optimized distribution.In the thesis,documentary,experiential summary,quantitative analysis methods and Data prediction method have been adopted.Through case study on the current situation of cold chain distribution in AI enterprises,consequent problems of cold chain distribution under O2O(Online to Offline)mode have been found out,including long delivery time,high costs,stockout,damages to cargoes,etc.In terms of these problems,detailed analysis and corresponding countermeasures have been presented.By studying the advanced experience of progressive cold chain distribution at home and abroad,combined with relative countermeasures,a variety of third-party cooperation in the form of warehouse storage have been used to establish separate warehouses to stock up,i.e.the mode that the O2O order forecast products are transported to the warehouse near the consumer.And through the logic and steps of setting up separate warehouses to establish a model,then its effectiveness is verified by examples.By collecting historical data such as historical sales volume and large-scale holiday promotion activities of AI enterprises on the O2O platform,required distribution products and influencing factors are predicted and analyzed.Combined with logistics capacity data of the third-party partners,the classification of warehouses,and the agreement of warehouses,the number of branch warehouses,their located cities,and their coverage areas are calculated through the separate warehouse algorithm.At the same time,in the area where the third-party partners failed to cover and the AI enterprise stores exceeded 5,regional distribution centers were built and the gravity method was used for site selection calculation.At the end of this thesis,based on the system of third-party partners,the inventory situation has been monitored,and systematic or artificial allocation and management has been adopted in due time to resolve the stockout as much as possible.As cold chain distribution is a complex system involving many factors such as links,time nodes,this thesis focuses on making the cold chain distribution optimization more suitable for the actual situation of the enterprise,effectively improving the overall distribution efficiency of O2O orders,reducing distribution costs,and solving the overlong delivery time,serious damages and frequent stockout,so as to enhance the customers' experiences and ultimately achieve the purpose of improving sales performance.It also has certain referential significance for other chain catering enterprises,which are active on the O2O platform,and for logistics enterprises,which take fresh e-commerce as their main source of customers. |
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