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研究生: 潘阮祺福
Phan - Nguyen Ky Phuc
論文名稱: BASS需求模型對供應鏈存貨政策影響之研究
STUDY OF BASS MODEL DEMAND’S EFFECT ON THE INVENTORY POLICY OF THE SUPPLY CHAIN
指導教授: 周碩彥
Shuo-Yan Chou
口試委員: 王孔政
Kung-Jeng Wang
喻奉天
Vincent F. Yu
學位類別: 碩士
Master
系所名稱: 管理學院 - 工業管理系
Department of Industrial Management
論文出版年: 2011
畢業學年度: 99
語文別: 英文
論文頁數: 53
中文關鍵詞: 貝式模型供應鏈管理存量管理
外文關鍵詞: Bass model, supply chain management, inventory management
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  • 貝式模型應用在新產品擴展過程的預測上,非常成功。許多的學者對於貝式模型在顧客需求管理及 存量控制的應用上,也進行了廣泛地研究;本論文則以綜合的觀點,對貝式模型在供應鏈管理上的應用提出看法。本論文所稱的供應鏈,將比照一般性的供應鏈,共 分為三個階段:零售商、供應商及製造商。零售商這個階段,必須處理顧客的需求,本論文假設這個階段會遵循貝式擴散程序。本論文同時假設,每一個階段之間的 資訊是完全分享;在資訊分享的基礎下,每一個階段都試圖追求最大的利潤。本論文藉由適當的問題處理過程以及MATLAB軟體程式運算,可以在訂購時間、訂購次數及定購數量等方面提出建議,進而決定每一個階段的存量政策


    Bass model is a very successful model in forecasting the diffusion process of new product. Its wide applications in managing the customer demand and controlling the inventory level have been studied by several scholars. This thesis gives a synthesis view of using Bass model in supply chain management. Similar other common supply chain, the supply chain in this thesis is divided into 3 stages, namely: retailer, supplier and manufacturer. The retailer is the stage handling the customer demand which is assumed following the Bass diffusion process. Information in this model is assumed being fully shared among stages. Based on this information, each stage tries to maximize their profit. By using appropriate approach- in this thesis, MATLAB software is used to program and solve the problem-this study gives suggestion, e.g. to order, the number of order, order quantities and manufacturing plans, for determining the inventory policies for each stage.

    Content 中文摘要 Abstract Content Figure List Table List CHAPTER 1 INTRODUCTION 1.1 Background and Motivation 1.2 Objective 1.3 Methodologies 1.4 Organization of thesis CHAPTER 2 LITERATURE REVIEW 2.1 Diffusion process 2.2 Bass model 2.3 Other version of Bass model 2.4 Inventory management under Bass model CHAPTER 3 MODEL FORMULATION 3.1 Supply chain framework and common assumptions 3.2 Stage 1: Retailer 3.3 Stage2 : Supplier 3.4 Stage3 : Manufacturer CHAPTER 4 NUMERICAL EXAMPLE 4.1 Stage 1: Retailer 4.2 Stage 2 Supplier 4.3 Stage 3 Manufacturer CHAPTER 5 CONCLUSION 5.1 Conclusion 5.2 Future work REFERENCE

    [1] Bass, F. M., “A New Product Growth Model for Consumer Durables”, Management Science, Vol.15, No. 5, 215–227, (1969).
    [2] Bass, F. M., Krishnan, T.V., Jain, D.C., “Why the Bass model fit without decision variables”, Management Science, Vol. 13, No. 3, 203-223, (1994).
    [3] Chern, M.-S., Teng, J.-T., Yang, H.-L., “Inventory lot-size policies for the Bass diffusion demand models of new durable products.”, Journal of the Chinese Institute of Engineers, Vol. 24, No. 2, 237-244, (2001).
    [4] Dodson, J. A., and Muller, E., “Model of new product diffusion through advertising and word-of-mouth”, Management Science , Vol. 24(15), 1568-1578 (1978).
    [5] Dreyfus, S. E., Law, A. M., The Art and Theory of Dynamic Programming, Academic Press, (1977).
    [6] Fourt, L. A., and Wood Lock, J. W., “Early Prediction of Market Success for New Grocery Products”, Journal of Marketing, 33-38, (1960).
    [7] Ho, T.-H., Savin, S., Terwiesch, C., “Managing Demand and Sales Dynamics in New Product Diffusion Under Supply Constraint”, Management Science, Vol. 48, No. 2, 187–206, (2002).
    [8] Hsiao, J.P.-H., Jaw, C., Huan, T.-C., “Information diffusion and new product consumption: A bass model application to tourism facility management”, Journal of Business Research, Vol. 62(7), 690-697, (2009).
    [9] Jiang, Z., Bass, F.M., Bass, P.I., “Virtual Bass Model and the left-hand data-truncation bias in diffusion of innovation studies”, International Journal of Research in Marketing, Vol. 23, No. 1, 93-106, (2006).
    [10] Kumar, S., Swaminathan, J. M., “Diffusion of innovation under supply constraints“, Operations Research, Vol. 51, No. 6, 866–879, (2003).
    [11] Mahajan, V., Muller, E., and Kerin, R. A., “Introduction strategy for a new product with a positive and negative word-of-mouth”, Management Science, Vol. 30, 1389-1404, (1984).
    [12] Mahajan, V., Muller, E., and Bass, F. M., “New product diffusion models in marketing: A review and directions for research”, Journal of Marketing, Vol. 54, 1-26, (1990).
    [13] Mansfield, E., Hensley, C., “The logistic process: Tables of stochastic epidemic curve and application”, Journal of Royal Statistic Society, 332-337, (1960).
    [14] Niu, S.-C., “A Stochastic Formulation of The Bass Model of New-Product Diffusion”, Mathematical Problems in Engineering Vol. 8, No.3, 249-263, (2002).
    [15] Niu, S.-C., "A Piecewise-Diffusion Model of New-Product Demands.”, Operations Research, Vol. 54, No. 4, 678-695, (2006).
    [16] Nikolopoulos, C.V., Yannacopoulos, A.N., “A model for optimal stopping in advertisement”, Nonlinear Analysis: Real World Applications, Vol. 11, No. 3, 1229-1242, (2010).
    [17] Parker, P., and Gatignon, H.,” Specifying competitive effects in diffusion models: An empirical analysis.” , International Journal of Research in Marketing, Vol. 11(1), 17−39, (1994).
    [18] Peres, R., Muller, E., Mahajan, V., “Innovation diffusion and new product growth models: A critical review and research directions”, International Journal of Research in Marketing, Vol. 27, No. 2, 91-106, (2010).
    [19] Roger, E. M., Diffusion of Innovation, Fourth Edition, The Free Press, New York (1995)
    [20] Savin, S., and Terwiesch, C., “Optimal product launch times in a duopoly: Balancing life-cycle revenues with product cost”. Operations Research, Vol. 53(1), 26−47, (2005).
    [21] Shihai, D., Zhijun, H., “Modeling the brand competition diffusion for consumer durables based on the bass model”, 2010 International Conference on Logistics Systems and Intelligent Management, ICLSIM 2010, Vol. 1, 372-376, (2010)
    [22] Tseng, M.-F., Hu, Y.-C., “Quadratic-interval Bass model for new product sale diffusion”, Expert System with Application, Vol. 36, 8496-8502, (2009)
    [23] Teng, J.-T., “A deterministic inventory replenishment model with a linear trend in demand”, Operation Research Letter, Vol. 19, 33-41, (1996)
    [24] Tsai, B.-H., Li, Y., Lee, G.-H., “Forecasting global adoption of crystal display televisions with modified product diffusion model”, Computers and Industrial Engineering, Vol. 58(4), 553-562, (2010).
    [25] Wang, W., Fergola, P., Lombardo, S., Mulone, G., “Mathematical models of innovation diffusion with stage structure”, Applied Mathematical Modelling, Vol.30, No. 1, 129-146, (2006).
    [26] Wang, F.-W., Chang, K.-K., “Modified diffusion model with multiple products using a hybrid GA approach”, Expert Systems with Application, Vol. 36, 12613-12620, (2009)
    [27] Wagner, H.M., Whitin, T.M., “Dynamic problems in the theory of the firm “, Naval Res. Logist. Quart., 5 (1), 53-74, (1958) .
    [28] Wu, F.-S., Chu, W.-L., “ Difusion model of mobile telephony”, Journal of Business Research, Vol. 63 (5), 497-501, (2010).

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