博碩士論文 974206025 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:83 、訪客IP:3.141.7.140
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)
相關論文
★ 應用失效模式效應分析於產品研發時程之改善★ 服務品質因子與客戶滿意度關係研究-以汽車保修廠服務為例
★ 家庭購車決策與行銷策略之研究★ 計程車車隊派遣作業之研究
★ 電業服務品質與服務失誤之探討-以台電桃園區營業處為例★ 應用資料探勘探討筆記型電腦異常零件-以A公司為例
★ 車用配件開發及車主購買意願探討(以C公司汽車配件業務為實例)★ 應用田口式實驗法於先進高強度鋼板阻抗熔接條件最佳化研究
★ 以層級分析法探討評選第三方物流服務要素之研究-以日系在台廠商為例★ 變動良率下的最佳化批量研究
★ 供應商庫存管理架構下運用層級分析法探討供應商評選之研究-以某電子代工廠為例★ 台灣地區快速流通消費產品銷售預測模型分析研究–以聯華食品可樂果為例
★ 競爭優勢與顧客滿意度分析以中華汽車為例★ 綠色採購導入對電子代工廠的影響-以A公司為例
★ 以德菲法及層級分析法探討軌道運輸業之供應商評選研究–以T公司為例★ 應用模擬系統改善存貨管理制度與服務水準之研究-以電線電纜製造業為例
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   [檢視]  [下載]
  1. 本電子論文使用權限為同意立即開放。
  2. 已達開放權限電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。
  3. 請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。

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.
8. Chen, J. (2001). “Coordination of the supply chain of seasonal products,” IEEE Transactions on Systems, Vol. 31, No. 6, 524-532.
9. Chun, Y.H. (2003). “Optimal pricing and ordering policies for perishable commodities,” European Journal of Operational Research, Vol. 144, No. 1, 68-82.
10. Chatwin, R.E. (2000). “Optimal dynamic pricing of perishable products with stochastic demand and a finite set of prices,” European Journal of Operational Research, Vol. 125,
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
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明