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研究生:李瓊英
研究生(外文):Chiung-Ying, Lee
論文名稱:長鞭效應下,最佳存貨策略的決定與環境變數效果的探討
指導教授:郭瑞祥郭瑞祥引用關係陳正剛陳正剛引用關係
學位類別:碩士
校院名稱:國立臺灣大學
系所名稱:商學研究所
學門:商業及管理學門
學類:一般商業學類
論文種類:學術論文
論文出版年:2000
畢業學年度:88
語文別:中文
中文關鍵詞:長鞭效應存貨控制系統強健性設計實驗設計資訊流通
外文關鍵詞:Bullwhip effectinventory policyRobust designexperimental designinformation sharing
相關次數:
  • 被引用被引用:38
  • 點閱點閱:525
  • 評分評分:
  • 下載下載:118
  • 收藏至我的研究室書目清單書目收藏:1
本研究以整合的方式來研究長鞭效應的問題,並進一步探討主要關鍵性因子的影響效果,作為管理上的依據。
而長鞭效應的成因主要有四:需求預測更新、批量訂購、短缺賽局及價格波動性,而前兩個原因又稱為存貨管理面因素,因為這兩個因素主要是由於企業內部存貨政策所造成的,此亦為本論文主要探討的重點。
為了完整探討存貨政策所造成並影響,本研究主要分成兩個層次作探討,一為下游零售商所能掌握之相關之存貨策略變數,稱之為決策變數,另一則為無法充分掌控之環境變數稱之為情境因子。本研究主要探討四個情境因子:零售商所面對的單位短缺成本、需求波動程度、前置期間及需求預測的準確性。
為了提高分析的可信度,本論文企圖建立一完整的供應鏈成本模型,並利用實驗設計的手法分別進行決策變數與情境因子的效果進行分析。而透過模擬分析,本研究得出以下結論:
一、Q System是一個較佳的存貨控制系統。
二、上下游所認同之最適決策變數水準不一致,反映供應鏈協調整合的必要性。
三、上下游對於情境因子水準的認同度較高,以情境因子作為協調整合的目標是個不錯的策略思考。
四、長鞭效應之主要的受害者為上游供應商,因此由其負責策略的主導是較合理的。
The factors of bullwhip effect include demand forecast updating, order batching, shortage game and price fluctuation. The first two factors are influenced by the inventory policy of a company, so they are also called " the inventory management factors". In this research, we focus on the inventory management factors and study how the inventory policy influences the bullwhip effect.
To investigate completely, we discuss the decision variables that the retailer could control and the scenario factors that are determined by environment.There are four factors that we discuss in the thesis. The four factors are the unit shortage cost of the retailer , demand fluctuation, lead time and the accuracy of demand forecasting.
In order to increase the creditability of our research, we try to make an integrated cost model of supply chain and apply the method of experimental design to analyze the effect of decision variables and scenario factors. After the simulation, we have the following conclusioms:
1. Q system is the best inventory control system to maximize the profit of retailer and manufacturer and to minimize the total cost of supply chian at the same time.
2. The different echelon players have different perception to the optimal level of decision variables, so it''s important to coordinate between different echelon players.
3. The different echelon players have the same perception to some scenario factors, so it''s easy to coordinate to reach the optimum of supply chian,
4. The profit of manufacturer decreases because of bullwhip effect, so it''s reasonable for manufacturer to lead the coordination.
目錄 1
圖次 3
表次 5
第一章 緒論 8
1.1 研究動機 8
1.2 研究目的 9
1.3 論文架構 10
第二章 文獻探討與研究方法 12
2.1 長鞭效應的成因探討與因應策略 12
2.1.1 長鞭效應的成因 12
2.1.2 長鞭效應的因應策略 13
2.2 長鞭效應的成本模型 18
2.2.1 供應鏈之重要成本項目分析 18
2.2.2 現有文獻之供應鏈成本模型 20
2.3 需求預測對於長鞭效應的效果分析 21
2.4 存貨策略對於長鞭效應的效果分析 22
2.4.1 主要的存貨策略 22
2.4.2存貨策略對於總需求變異的影響 24
第三章 供應鏈的基本模型及模擬方法 25
3.1 模型的基本假設 25
3.2 主要成本項目介紹 26
3.3 成本模型的建立 27
3.4存貨控制系統對於成本模型的影響 32
3.5 模型的模擬 33
3.5.1 成本參數的給定 33
3.5.2 情境因子與決策變數的決定: 34
3.5.3 情境的設計 37
3.5.4 模型的模擬 38
第四章 情境內部分析 41
4.1 Q SYSTEM 41
4.1.1 決策變數的效果分析 41
4.1.2二元二次迴歸分析 47
4.1.3 不同情境下決策變數之效果的異同分析 51
4.1.4 Q System小結 55
4.2 P SYSTEM 56
4.2.1 決策變數的效果分析 56
4.2.2二元二次迴歸分析 60
4.2.3 不同情境下決策變數之效果的異同分析 64
4.2.4 P SYSTEM小結 67
4.3 ORDER-UP-TO SYSTEM 68
4.3.1 決策變數的效果分析 68
4.3.2二元二次迴歸分析 73
4.3.3 不同情境下決策變數之效果的異同分析 77
4.3.4 ORDER-UP-TO SYSTEM小結 81
4.4 不同存貨系統間的交叉分析 82
4.5 強健性設計 85
4.5.1 強健性設計的概念 85
4.5.2 Q SYSTEM 87
4.5.3 P SYSTEM 91
4.5.4 ORDER-UP-TO SYSTEM 94
4.6本章小結 98
第五章 情境因子間的交叉分析 99
5.1 Q SYSTEM 100
5.2 P SYSTEM 108
5.3 ORDER-UP-TO SYSTEM 114
5.4 需求資訊流通的影響 119
5.5 本章小結 125
第六章 結論與建議 126
6.1結論 126
6.2 研究限制 128
6.3 未來研究建議 128
參考文獻 129
[1] G''erard P. Cachon, "Managing Supply Chain Demand Variability with Scheduled Ordering Policies," Management Science,p843-856, Vol.45, No.6, June 1999
[2] Gerard P. Cachon," Managing Supply Chain Demand Variability with Scheduled Ordering Policies ",Management Science, Vol.45, No.6, June 1999
[3] Srinagesh Gavirneni, Roman Kapuscinski and Sridhar Tayur, "Value of Information in Capacitated Supply Chains," Management Science, p16-24, Vol.45, No.1, Jan 1999
[4] Frank Chen, Zvi Drezner, Jennifer K. Ryan and David Simchi-Levi, "The bullwhip effect: managerial insights on the impact of forecasting on variability in a supply chain,"
[5] Lee J. Krajewski and Larry P. Ritzman, " Operations Management: Strategy and Analysis", Fifth Edition,1998
[6] Hau L. Lee, V. Padmanabhan, and Seungjin Whang, "Information Distortion in a supply Chain: The Bullwhip Effect," Management Science, Vol.43, No.4, April 1997
[7] Richard Metters," Quantifying the Bullwhip Effect in Supply Chains " ,Journal of Operations Management, Vol. 15, p89-100, 1997
[8] Hau L. Lee, V. Padmanabhan, and Seungjin Whang, "The Bullwhip Effect in Supply Chains," Sloan Management Review, Spring 1997
[9] Richard Metters, "Quantifying the Bullwhip Effect in Supply Chains," Journal of Operations Management," Vol. 15, p89-100, 1997
[10] Haresh Gurnani," Optimal Ordering Policies in Inventory Systems with Random Demand and Random Deal Offerings ",European Journal of Operational Research, p1-15, Vol.94 1996
[11] Carlos F. Daganzo," Logistics Systems Analysis, ?
[12] Abad, P. L." Supplier Pricing When the Buyer''s Annual Requirements are Fixed", Computers Operations Research, vol. 21, 155-167,1994
[13] Douglas M. Lambert and James R. Stock, "Strategic Logistics Management," Third Edition, 1993
[14] Banerjee, A.," A joint economic-lot-size model for purchaser and vendor" Decision Science, vol. 17 292-311,1986
[15] Andrew S. Caplin, "The variability of aggregate demand with (S, s) inventory policies," Econometrica, Vol.53, No. 6, Nov.1985
[16] 李昌雄, 商業自動化與電子商務導論,1998
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