本論文研究單一零售商，針對其販售季節性商品所面臨的訂價決策問題。此類型商品大多探討在固定的存貨下以及有限的銷售期間內，尋求最佳的價格策略以達到商品銷售營收最大化。 本論文是以Bitran 和Mondschein (1997) 的概念為基礎，提出了利用貝式方法來更新需求資訊的模型。然而與此概念不同之處在於，我們設立一個和價格相關的變數 且透過每銷售階段所蒐集的需求資訊，來更新原始的機率模型，並透過此新機率模型來更新剩餘存貨的銷售價格，提供在不同銷售時點下給予不同的銷售價格，最後給予零售商在訂價決策上的建議。In this thesis, we consider the determination of pricing policy for a retailer that maximizes the profit from selling a given inventory of seasonal products by a fixed deadline. The concept of this study is based on Bitran and Mondschein (1997). Different from their concept, we set a scale variable, and use the past history of the demand during the planning horizon to update the scale variable by using Bayesian method and showing how it can be embedded in our updating model. Our aim is trying to estimate the scale variable. Finally, we embed it into optimal pricing model and find the appropriate selling price than the original selling price during each sales period, and even show how it can bring more profit during the sales season for the decision maker.
