博碩士論文 974206025 詳細資訊


姓名 沈建儀(Jian-yi Shen)  查詢紙本館藏   畢業系所 工業管理研究所
論文名稱 以貝式更新決定季節性商品之銷售價格
(Determination of the selling price of the seasonal product with Bayesian updating)
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摘要(中) 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。
摘要(英) 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.
關鍵字(中) ★ 季節性商品
★ 貝式方法
★ 價格更新
關鍵字(英) ★ Seasonal products
★ Bayesian method
★ Pricing update
論文目次 中文摘要 i
Abstract ii
Content iii
List of figures v
List of tables vi
1. Introduction 1
1.1 Background and Motivation 1
1.2 Research Objective 2
1.3 Research Framework 2
2. Literature Review 4
2.1 Seasonal Products 4
2.2 Bayesian Method 5
3. The Model 8
3.1 Scenario Setting 8
3.2 Demand function and Notations 8
3.3 The updating model 10
3.4 The retailer’s expected profit model 13
4. Numerical Study 15
4.1 Data Setting 15
4.2 Numerical Analysis 16
4.3 Sensitivity Analysis 19
5. Summary and Future Research 23
5.1 Summary 23
5.2 Future Research 24
Reference 25
Appendix 27
A1. With ordering quantity 27
A2. With ordering quantity 28
參考文獻 1. Azoury, K.S. (1985). “Bayes solution to dynamic inventory models under unknown demand distribution,” Management Science, Vol. 31, No. 9, 1150-1160.
2. Arrow, K.J. (1962). “The economic implications of learning by doing,” The Review of Economic Studies, Vol. 29, No. 3, 155-173.
3. Aviv, Y. and A. Pazgal (2005). “Optimal pricing of seasonal products in the presence of forward-looking consumers,” Manufacturing & Service Operations Management, Vol. 10, No. 3, 339-359.
4. Bitran, G.R. and H.K. Wadhwa (1996). “A methodology for demand learning with an application to the optimal pricing of seasonal products,” Working Paper, MIT Sloan School of Management, 3896-3898.
5. Bitran, G.R. and H.K. Wadhwa (1996). “Some structural properties of the seasonal product pricing problem,” Working Paper, MIT Sloan School of Management, 3896-3897.
6. Bitran, G.R. and S.V. Mondschein (1997). “Pricing perishable products: an application to the retail industry,” Working Paper, Massachusetts Institute of Technology, Cambridge, MA, 3592-3593.
7. Bitran, G.R. and S.V. Mondschein (1997). “Periodic pricing of seasonal products in retailing,” Management Science, Vol. 43, No. 1, 64-79.
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149-174.
11. Fisher, M. and A. Raman (1994). “Making supply meet demand in an uncertainty world,” Harvard Business Rev., Vol. 72, 83–93.
12. Grossman, S.J., R. Kihlstrom and L.J. Mirman (1997). “A Bayesian approach to the production of information and learning by doing,” The Review of Economic Studies, Vol. 44, No. 3, 533-547.
13. Kihlstrom, R. (1974). “A Bayesian model of demand for information about product Quality,” International Economic Review, Vol. 15, No. 1, 99-118.
14. Khouja, M. (1999). “The single-period news-vendor problem: literature review and suggestions for future research,” Omega, Int. J. Mgmt. Sci., Vol. 27, 537-553.
15. Monroe, K.B. (1990). Pricing: making profitable decisions, McGraw-Hill, New York.
16. Park, S., D.L. Ensign and V.S. Pande (2006). “Bayesian update method for adaptive weighted sampling,” Physical Review, Vol. 74, 1-12.
17. Petruzzi, N.C. and M. Dada (1999). “Pricing and the newsvendor problem: a review with extensions,” Operations Research, Vol. 47, No. 2, 183-194.
18. Scarf, H. (1959). “Bayes solutions of the statistical inventory problem,” Annals of Mathematical Statistics, Vol. 30, 490-508.
指導教授 葉英傑(Yingchieh Yeh) 審核日期 2010-6-28
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