隨著市場競爭愈來愈激烈，產品保固逐漸扮演著重要的角色，其作用不僅在於保障消費者的權益，對廠商而言，也是一個不可忽視的行銷手段，因為附有較佳保固契約的產品對需求有刺激的作用。然而保固同時也會使廠商必須負擔額外的保固成本，所以廠商在產品上市與促銷時必須將其納入整合策略的考量，其中包含產品訂價、生產和產品保固策略等，彼此息息相關。因此，廠商若想提升利潤就不能以單一策略作考量而需做整合的思考。過去，很少有學者根據這些情況去研究廠商應如何制定最佳的決策。再者，新產品可靠度退化的歷史資料可能非常稀少或難以取得，因而無法以傳統的統計方法加以估計其參數並且去進行相關的決策分析。而貝氏決策程序(Bayesian decision)則是提供這種情境下的解決方法，使得相關的決策分析在缺法歷史資料情況下依然能夠進行。因此，本研究提
出以貝式決策程序為基礎的數學規劃(Mathematical programming)模式，幫助廠商在缺乏產品歷史資料的情況下，有系統地決定產品訂價，生產和保固策略。此外，本研究亦提出電腦化之架構設計幫助相關決策者實現決策過程之資訊化。關於產品特性方面，本研究主要設定在產品為可維修且其回廠檢修頻率服從非齊次蒲瓦松過程(Non-homogeneous Poisson process)之假設。

A successful industry strategy should be managed to integrate decisions, such as various managerial pricing, production, warranty, and customer services, in order to
maximize profits. In fact, some research has been carried out to cope with the multiple if sufficient historical data cannot be gathered to confidently estimate the deterioration of a new product, then the solution may not be assertively reliable. In dealing with such a problem for the situation of scarce historical data, a Bayesian analysis should be suitable because it can effectively assess the deterioration based on experts’
opinions and possibly few relevant data. In this study, we employed a mathematical programming approach along with a Bayesian updating process to tackle such a complex decision problem, and the optimal prior and posterior decisions of pricing scheme, production plan, and warranty policy can thus be determined simultaneously. In addition, we provided a computerized architecture to help decision makers in implementing the proposed approach. Besides, a practical application case was used to demonstrate the usefulness of the proposed model.

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