在現今全球性整體供應鏈競爭中，為滿足客戶縮短交期、降低庫存、提升品質與快速反饋等需求，買賣雙方需協同合作才能改善面臨的供應鏈問題。協同規劃、預測與補貨(Collaborative Planning, Forecasting and Replenishment, CPFR)，即緣起於解決供應鏈問題，透過解決買賣雙方供需差異的治本之道，讓合作夥伴運用網際網路分享預測和結果資訊，因此，可以減少供應鏈的庫存成本，並增加商品的可利用率。

目前台灣與國外已有多家公司證明導入CPFR商業模型具有正面成效，但對於實例研究，尤其是電子產業之工業自動化產品之研究甚少，故本研究將以一個案公司為例，探討其透過運用美國產業共同商務標準協會(Voluntary Interindustry Commerce Solutions Association ，VICS)所提供之CPFR商業模型概念，導入指南及九大步驟，分析並說明個案公司導入之步驟與詳細細節，並透過導入CPFR來達到縮短客戶交期、提升工廠交貨準時達交率及降低買賣雙方存貨週轉天數的企業目標。CPFR其核心價值在於供應鏈合作夥伴間的協同合作關係的建立與共享資訊，因應此商業模型所產生的供需及預測資料，亦替未來大數據分析，如應用行業分析、區域出貨分析、專案需求分析及出貨趨勢分析等提供參考數據。

Nowadays, enterprises are facing the global supply chain competition. All the members need to work together to solve the supply chain issues and meet customers' needs for shorter delivery, lower inventory, quality improvement, and faster feedback. However, the Collaborative Planning, Forecasting and Replenishment (CPFR) was imposed to solve problems in the supply chain at the beginning. As it can be used for solving the fundamental problem of the difference in supply and demand between buyers and sellers, partners can use the Internet to share forecasting and results in information. Thus, it will reduce inventory costs in the supply chain and increase the availability of goods.

At present, many worldwide companies have proved that implement CPFR business model has positive effects, but there are few studies on case studies, especially in the electronics industrial automation products. Therefore, an electronics industrial automation products company was chosen as an example to study its application. The CPFR business model concept, introduction guide, and nine steps were provided by Voluntary Interindustry Commerce Solutions Association (VICS). We use it to analyze and explain the actions for the case company's implementation. We implement CPFR to achieve the goal of shortening customers' delivery, improving the delivery on time rate, and reducing the inventory turnover days for both partners. The central core value of CPFR lies in the establishment and sharing of collaborative relationships between supply chain partners. In response to the supply and demand and forecast data generated by this business model, it also provides reference data for future big data analysis, such as application industry analysis, regional shipment analysis, project demand analysis, and shipment trend analysis.

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