Research On CPFR And Collaborative Forcasting Process

Supply chain management (SCM) was initially proposed to further improve the firms competitive and, ever since, has become the hot topic for management practice and academic research. In the accelerating trend of economical goloblization and the following management reengineering in the fields of purchasing, logistics, warehouse management, manufacturing and business development as well, SCM solutions are formatted and consequently researched in different industries.In retailing industry, ECR, CR, VMI, JMI, and CPFR was consequently initiated to downsize the supply chain operation costs and increase customer satisfication as well. CPFR is dedicated to improve internal and external cooperation efficency. Since its first application between Wal-Mart and P&G in 1995, CPFR has been adopted by many world-class firms, which not only saved the supply chain operation costs,but increased the sales as well, and more important, led to supply chain integration by continuously improving the partners' relationship and trust level by extending cooperation scope from inventory management to demand management.In order to help local firms get familiar with and plunge into CPFR's application, this dissertation was contributed to embody and propose resolution to the problems which have been encountered by the forthgoers and will trouble the followers, especially from China. The problems can be divided into: the strategic analysis before CPFR application's decision, the selection of collaborative forecasting model(s), and the development of collaborative forecasting information system.As for strategic analysis of CPFR application, the first chapter makes introduction of the guideline models and critical drivers in detail, and make out the problems which should be addressed before application. The second chapter emphasizes the preconditions of CPFR adoption that it must be fit for the product's characteristics to maximize the efficiency.As for collaborative forecasting mechanism and models, the third chapter conclude that accurate forecasting result coming from revealing the inner rule(s) of demand and (or) constructing appropriate forecasting model. Considering the forecasting process in CPFR, the fourth chapter focused on research of practicing combination forecast models analysis and construction for CPFR. Further, one practical example is presented toillumilate the normal process and prove the efficiency combination forecasting model.The fifth chapter focused on online collaborative forecasting system research and development. Such system is aimed at realizing information sharing between CPFR partners and complex combination forecasting in practice by take full advantage of Java language and Matlab software. Java is equipped with data encapsulation which will enable the partners to reach the aim of sharing important business information and forecast result but no risks of exploding the real data. Meanwhile, the powerful data calculating ability of Matlab software is used resolve the problems of realizing complex combination forecast algorithms in Java. The combining programming of Java and Matlab is based on VC++ to enable combination forecast could be practiced in firms' forecast operation with minimized costs.