本論文主要研討決策者銷售季節性商品之生產量和定價問題。一般說來，季節性商品有兩項特色：固定的存貨數量以及有限的銷售時間。因為存貨的前置時間長，無法在短銷售期間內做彈性的補貨動作，故決策者必須在期初即決定存貨生產數量的多寡，因此如何在有限的銷售期間內有效的利用價格機制是很重要的。本研究室以Lee (2001) 和Shao (2007) 的概念為基礎，提出了一個利用貝式方法來更新需求資訊的模型，決策者根據原始的機率模型來決定需要生產的存貨數量以及訂定售價，經過一段銷售時間後，利用此銷售期間所獲得的需求資訊來更新原始的機率模型，並且利用此新模型來更新剩餘存貨的售價，提供決策者一個更好的決策模型。 We consider that a decision maker determines the production quantity and the selling price of a seasonal product to maximize profit. Generally, seasonal products have two features, a fixed inventory of product and a limited sale period. Lee (2001) developed a single period model to study how the decision maker of a seasonal product production system to determine the appropriate cost in forecasting. And Shao (2007) studied optimal pricing strategies for seasonal products by using Dynamic programming. In our study, the decision maker based on the prior information can determine the best production quantity and the best selling price of a seasonal product. With the sales data obtained from the first sale period, we propose a Bayesian method to determine a better pricing strategy for the decision maker.
