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研究生:王勝智
論文名稱:供應鍊長鞭效果之研究--需求信號處理之觀點
指導教授:周世玉周世玉引用關係
學位類別:碩士
校院名稱:國立中興大學
系所名稱:電子商務研究所
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:2004
畢業學年度:92
語文別:英文
論文頁數:104
中文關鍵詞:供應鏈長鞭效果移動平均法指數平滑法ARIMA模型
外文關鍵詞:Supply ChainBullwhip EffectARIMA ModelMoving AverageEWMA
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An effective supply chain management requires collaboration and information sharing of each partner along the chain. Although supply chain management theory emphasizes the significance of a more opening on sharing information, companies do usually a limited sharing in practice. This behavior violates the original intention of supply chain management and therefore brings about increase in variability known as “bullwhip effect.”
Generally, most companies choose a simple method, such as moving average method or EWMA, to forecast their future needs. Many researchers maintain this consideration and analyze the bullwhip effect with these convenient methods on the cause of demand forecast updating. They provide many remedies to reduce fluctuation of demand variability on the bullwhip effect.
This research applies an exact method in demand forecasting for the retailing firm in a supply chain and explores the possibility of reducing the bullwhip effect. This paper also uses both convenient and exact forecast methods to investigate the impact of sharing information on bullwhip effect.
An effective supply chain management requires collaboration and information sharing of each partner along the chain. Although supply chain management theory emphasizes the significance of a more opening on sharing information, companies do usually a limited sharing in practice. This behavior violates the original intention of supply chain management and therefore brings about increase in variability known as “bullwhip effect.”
Generally, most companies choose a simple method, such as moving average method or EWMA, to forecast their future needs. Many researchers maintain this consideration and analyze the bullwhip effect with these convenient methods on the cause of demand forecast updating. They provide many remedies to reduce fluctuation of demand variability on the bullwhip effect.
This research applies an exact method in demand forecasting for the retailing firm in a supply chain and explores the possibility of reducing the bullwhip effect. This paper also uses both convenient and exact forecast methods to investigate the impact of sharing information on bullwhip effect.
TABLE OF CONTENTS
ABSTRACT…………………………………………………………………….……..i
LIST OF TABLES………………………………………………………………...…..v
LIST OF FIGURES…………………………………………………...………………vi
CHAPTER
1.INTRODUCTION
1.1 Significance of the research 1
1.2 Purpose of the research 2
1.3 Framework of the research 2
2. A COMPARISON OF BULLWHIP EFFECT IN A SINGLE-STAGE SUPPLY CHAIN FOR AUTOCORRELATED DEMANDS WHEN USING EXACT, MA, AND EWMA METHODS
2.1 Introduction 4
2.2 Literature Review 6
2.2.1 Bullwhip Effect 6
2.2.2 Time Series Model 10
2.3 The Convenient or Exact Forecasting Techniques of Bullwhip Effect 12
2.3.1 The Assumptions and Notations 12
2.3.2 Demand model description 13
2.3.3 The formula for bullwhip effect 14
2.3.3.1 Correct forecasting method 15
2.3.3.2 The exponential smoothing forecast and moving average forecast 19
2.4 Simulation Results 22
2.5 Conclusion 28
References 30
Appendix 2-A. Quantify the single-stage bullwhip effect in ARIMA(1,0,1) demand model 31
Appendix 2-B. Quantify the single-stage bullwhip effect in MA(1) demand model 36
Appendix 2-C. Quantify the single-stage bullwhip effect for AR(1) model 38
3. A COMPARISON OF BULLWHIP EFFECT IN A TWO-STAGE SUPPLY CHAIN FOR AUTOCORRELATED DEMANDS WITH AND WITHOUT RETAILING DEMAND INFORMATION SHARING AMONG SUPPLY CHAING MEMBERS
3.1 Introduction 40
3.2 Literature review 43
3.2.1 The bullwhip effect 43
3.2.2 Demand forecast updating in the bullwhip effect 44
3.3 Two Stages Supply Chain on the Bullwhip Effect without information sharing 46
3.3.1 Notations 47
3.3.2 Quantify the Bullwhip Effect without Retailing Demand Information Sharing 48
3.3.2.1 The case of serially correlated demand 50
3.3.2.2 The case of time series demand -MA(1) 56
3.3.2.3 The case of time series demand-ARIMA(1,0,1) 61
3.3.3 The Impact of Sharing Information on the Bullwhip Effect 67
3.4 Comparison of forecasting methods and demand processes with or without information sharing 70
3.4.1 Comparison of demand process without information sharing 70
3.4.2 Comparison of Information Sharing 72
3.5 Conclusion 75
References 76
Appendix 3-A. The case of stationary, serially correlated demand 78
Appendix 3-B. Quantify the bullwhip effect for MA(1) model 87
Appendix 3-C. Quantity the bullwhip effect on two-stage supply chain -ARIMA(1,0,1) 94
4 .CONCLUSION AND FUTRUE RESEARCH RECOMMENDATIONS
4.1 Contribution 103
4.2 Further Research Recommendations 103
References 104
Brown R.G., Smoothing, forecasting and prediction, Prentice Hall, Englewood Cliffs, NJ. 1962
Hax A.C. and D. Candea, Production and inventory management, Prentice-Hall , Englewood Cliffs, NJ, 1984
Heyman D. and M. Sobel, Stochastic models in operations research, Vol I, McGraw-Hill, New York, 1984
J. Kahn, Inventories and the volatility of production, Am Econ Rev 77(1987), P667-679
Richard Metters, Quantifying the bullwhip effect in supply chain, Journal of operations management, vol.15(1997), P89-100
H. Lee, V. Padmanabhan, and Seungjin Whang, The bullwhip effect in supply chains, MIT Sloan Management Review, Spring 1997, P.93.
H. Lee, V. Padmanabhan, and Seungjin Whang, In formation distortion in a supply chain: The bullwhip effect, Management science, Apr 1997, P546
F. Chen , Zvi Drezner, Jennifer K. Ryan, David simchi-Levi, Quantify the bullwhip effect in a simple supply chain: The impact of forecasting, lead times, and information, Management science, March 2000, P.436-443
F. Chen, Jennifer K. Ryan, David simchi-Levi, The Impact of exponential smoothing forecasts on the bullwhip effect, Naval research logistics, Vol.47(2000), P.269
X. Kefeng, Yan Dog, Philip T. Evers, Towards better coordination of the supply chain, Transportation research part E, vol.37(2001), P.35-54.
Fu-En Wang, Chu Yen-Fang, and Lan Shaw-Ping, A study of key factors of the bullwhip effect under different demand processes, The International Contemporary Marketing Academic Conference, 2002.
S. goran, The bullwhip effect in intra-organisational echelons, International Journal of Physical Distribution & Logistics Management, vol.33 (2003), P.103
M. Hokey and Gengui Z., Supply chain modeling: past, present and future, Computer & industrial Engineering 43 (2002), P.231-249
G. Kenneth, An ARIMA supply chain Model, 2002.
S.M. Disney and D.R. Towill, On the bullwhip and inventory variance produced by an ordering policy, The International Journal of Management Science, November 2001, P.157-167
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