政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/35199
English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  全文筆數/總筆數 : 113392/144379 (79%)
造訪人次 : 51197370      線上人數 : 888
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    政大機構典藏 > 商學院 > 資訊管理學系 > 學位論文 >  Item 140.119/35199
    請使用永久網址來引用或連結此文件: https://nccur.lib.nccu.edu.tw/handle/140.119/35199


    題名: CPFR流程下之銷售預測方法~混合預測模型
    A Hybrid Modeling Approach for Sales Forecasting in CPFR Process
    作者: 黃蘭禎
    Huang,Lan Chen
    貢獻者: 林我聰
    Lin,Woo-Tsong
    黃蘭禎
    Huang,Lan Chen
    關鍵詞: 協同規劃、預測與補貨
    銷售預測
    混合預測模型
    基因演算法
    Collaborative Planning, Forecasting and Replenishment
    CPFR
    Sales forecasts
    Hybrid forecasting model
    Genetic Algorithm
    日期: 2003
    上傳時間: 2009-09-18 14:25:25 (UTC+8)
    摘要: 協同規劃、預測與補貨(Collaborative Planning, Forecasting and Replenishment,CPFR),在歐美經過一些企業的採用後已經有顯著的成效,目前國內已經有一些企業相繼採用或即將採用CPFR,期望能因此降低供應鏈作業成本及提升供應鏈作業績效,以提升企業競爭力。在CPFR流程與供應鏈協同作業環境下,一個供需雙方協同,且績效良好的的銷售預測具有關鍵的重要性,是管理決策與協同合作時的的重要依據;但是多數的企業並沒有一個結構化、系統化的預測流程及方法,而是各部門透過簡單時間序列方法、天真預測法或人為經驗法則估算需求,進行多點且不同方法之預測,這樣的銷售預測較無穩定的品質,亦較難提供管理者合理的數據解釋。本研究結合時間序列、多元回歸模型與基因演算法發展出一個CPFR流程下之三階段混合預測方法,以買賣方直接之銷售資料、銷售計畫等資訊進行以「週」為單位之個別商品銷售預測。同時本研究中,亦以國內某製造業公司與其顧客(一國際大型零售連鎖店通路商)之產品銷售資料進行方法的驗證;實驗顯示,本研究所提出之預測方法之預測結果較Jeong等人(2002)所提結合多元回歸模型與基因演算法之二階段預測系統之預測結果佳;亦較傳統使用普通最小平方法求解之一般統計回歸方法預測結果佳。
    It has been verified in pilot projects by many European and American Corporations that Collaborative Planning, Forecasting and Replenishment (CPFR) can improve supply chain performance. Enterprises nowadays in Taiwan are implementing or going to implement CPFR, with hopes to reduce their supply chain operation cost, enhance logistic performance and increase their competition capability consequently. Under CPFR process and supply chain collaboration environment, a supply and demand both sides promised identical sales forecast with well forecasting performance for order decision making and cooperation is very important. Due to the dynamic complexities of both internal and external co-operate environment, many firms resort to qualitative, navie forecasting or other simple quantitative forecasting techniques and have many forecasts in their organization. However, these forecasting techniques lack the structure and extrapolation capability of quantitative forecasting models or without stable performance, while multi-forecasts providing different views of demand. Forecasting inaccuracies exist and typically lead to dramatic disturbances in sales order and production planning.
    This paper presents a hybrid forecasting model for sales forecasting requirements in CPFR. A three stage model is proposed that integrate the time series model, regression model and use genetic algorithm to determine its coefficients efficiently. Direct sales information and related planned events in both collaborated sides is used for individual product’s “week” sales forecasting. To verify this model, we experiment on two different products and produce forecasts with datum from one manufacturer in Taiwan and its international retailer. The results shows that the hybrid sales forecasting model has better forecasting performance than not only the causal-genetic forecasting model proposed by Jeong et al. (2002), but also ordinary regression model with no genetic training process.
    參考文獻: 中文參考文獻
    1.林郁文,「以產品生命週期為基礎之多世代產品競爭主動式雙贏定價模式」,東海大學工業工程與經營資訊研究所碩士論文,民國92年六月
    2.陳建安,「整合類神經往路與遺傳演算法為輔之模糊類神經網路於智慧型訂單選取之應用」,國立台北科技大學生產系統工程與管理研究所碩士論文,民國89年六月
    3.蘇木村、張孝德,「機器學習類神經網路、模糊系統以及基因演算法則」,全華科技圖書股份有限公司出版,民國92年二版
    4.鄭碧娥,「商情預測」,三民書局,民國82
    5.姚銘忠、張倫、林晏妃、黃曉玲,「工具機業導入協同規劃與補貨模式之探討」,第一屆知識管理與與協同規劃研討會,http://2002.kiucp.ie.thu.edu.tw/
    6.姚銘忠、張倫、黃曉玲、黃茂洲,「由二階製N階的協同計劃、預測與補貨模式之探討」,第一屆知識管理與與協同規劃研討會,http://2002.kiucp.ie.thu.edu.tw/
    7.張炳螣、張晴翔、廖嘉偉,「協同預測應用於IC半導體之整合模式」,第一屆知識管理與與協同規劃研討會,http://2002.kiucp.ie.thu.edu.tw/
    8.廖嘉偉,「前導性協同預測架構與實施系統之研究」,東海大學工業工程與經營資訊研究所碩士論文,民國92年
    英文參考文獻
    1.Anderson, E. & Simester, D. ,” Minding Your Pricing Cues,” Harvard business Review, September , 7pgs,2003
    2.Anderson, D. and Lee, H. ,” White paper: The Internet-enabled supply chain: from the “first click” to the” Last Mile “,1999, available at http://www.manufacturing.net/scm/contents/pdf/anderson_lee_wp.pdf
    3.Arminger, G. ,”Sales and Order Forecasts in the CPFR Process for Retail”,pp.53-68, 2002
    4.Aviv, Y. ,”The Effect of Collaborative Forecasting on Supply Chain Performance,” Management Science, Vol.47, No.10, pp.1326-1343, 2001
    5.Aviv, Y. ,“Gaining Benefits from Joint Forecasting and Replenishment Processes: the Case of Auto-Correlated Demand,” Manufacturing & Service Operations Management,Vol.4, No.1,pp.55-74, 2002
    6.Bajic, V. ,"Automobiles and Implicit Markets: An Estimate of a Structural Demand Model for Automobile Characteristics," Applied Economics,vol.2, pp. 541-551, 1993
    7.Chase, C. W. ,"Business Forecasting: A Process Not An Application," Journal of Business Forecasting,Vol.11, No.3,pp.12-13, 1992
    8.Chase, C. W. and Chase, Jr. ,"The Realities of Business Forecasting," Journal of Business Forecasting, Vol.14, No.1, p.2, 26, 1995
    9.Chase, C. W. and Chase, Jr., "What Do You Need to Know When Building A Sales Forecasting System," Journal of Business Forecasting, Vol.15, No.3, pp.2,23, 1996
    10.Charles, C.W. and Chase, Jr. ,“Composite Forecasting: Combing Forecasts for Improved Accuracy,” The journal of business forecasting, Vol.19, pp.2, 20-22, 2000
    11.Chu, C.W. and Zhang. G. P. ,”A Comparative study of linear and nonlinear models for aggregate retail sale forecasting,” International Journal of Production Economics, Vol.86, pp.217-231, 2003
    12.Diehn, D. ,”Seven Steps to Build a Successful Collaborative Forecasting Process,” The journal of business forecasting, Vol.19,No.4,pp.23-29, 2000-2001
    13.Goldberg, D. E. ,“Generic Algorithms in Search, Optimization and Machine Learning,” Addison-Wesley Publishion, 1989
    14.Jeong, B. ,Jung, H. S. and Park, N. K.,”A computerized casual forecasting system using genetic algorithms in supply chain mgmt,” the Journal of Systems and Software, vol.60, pp. 223-237, 2002
    15.Herrera, M. L. and Verdegay, J. H. ,”Fuzzy connectives based crossover operation to model genetic algorithms population diversity,” Fuzzy Set and Systems 92, pp.21-30, 1997
    16.Helms, M. ,Ettkin, L. P. and Chapman, S. ,“Supply Chain Forecasting—Collaborative forecasting supports supply chain management,” Business Process Management Journal, Vol.6, Iss.5, pp.392-394
    17.Holmström, J. ,Främling, K. ,Kaipia, R. and Saranen, J. ,“Collaborative Planning Forecasting and Replenishment: New Solutions Needed for Mass Collaboration,” the Journal of Supply Chain Management ,Vol.7, No.3, pp.136-145, 2002
    18.Jain, L. ,”Which Forecasting Model should We Use? ,”The journal of business forecasting, Vol.19,No.3,pp.2,28,35, 2000
    19.Jain, L. ,”Benchmarking forecasting models,” The Journal of Business Forecasting, Methods and System,Vol.21,No.3 ,pp.18-20,30, 2002
    20.Kolter, P. ,”Marketing management-Analysis, Planning,Implementation and Control,”9th ed, Englewood Cliffs, N. J., Prentice-Hall Inc., 1991
    21.Lapide, L. ,“New developments in business forecasting : Debunking executive conventional wisdom ,” The journal of business forecasting, vol.19,No.2, pp.16-17, 2000
    22.LeVee, G. S. ,"The Key to Understanding the Forecasting Process, "Journal of Business Forecasting, Vol.11, No.4, pp.12-16, 1992
    23.Makridakis, S. and Wheelwright, S. C. ,“Forecasting Methods for Management,” 5th ed., N.Y.: John Wiley & Sons, pp.571-582, 1979
    24.MaCarthy, T. M. and Golicic, S. L. , ”Implementing Collaborative Forecasting to Improve Supply Chain Performance,” International Journal of Physical Distribution & Logistics Management, Vol.32, No.6, pp.431-454, 2002
    25.Mills, T. C. ,”Time Series Techniques for Economics, ”Cambridge University Press, United Kingdom, 1990
    26.Murray, J. and Sarantis, N. ,” Price-quality relations and hedonic price indexes for cars in the United Kingdom,” International Journal of the Economics of Business, Vol. 6,Iss.1,pp. 5, 23, 1999
    27.Mulhern, F. J.,Williams,J. D. and Leone,R. P. ,“Variability of Brand Price Elasticity across Retail Stores: Ethnic, Income, and Brand Determinants,” Journal of Retailing, Vol.74,No.3,pp.427-446, 1998
    28.Nolan, W. Jr. ,”Game Plan for A Successful Collaboration Forecasting process”, the Journal of Business Forecasting, Spring pp.2-6, 2001
    29.Ozturkmen, Z. A. ,“Forecasting in the Rapid Changing Telecommunications Industry: AT&T’s Experience,” The journal of business forecasting,Vol.19,No.3, pp.3-4, 2000
    30.Rice, G. and Mahmoud, E. , "Political Risk Forecasting by Canadian Firms," International Journal of Forecasting, Vol.6, No.1, pp.89-120, 1990
    31.Safavi, A. ,”Choosing The Right Forecasting Software and System,” The journal of business forecasting, Vol.21,No.3, pp.6-12,14, 2000
    32.Shankar, V. and Krishnamurthi, L. ,“Relating Price Sensitivity to Retail Promotional Variables and Pricing Policy: An Empirical Analysis,” Journal of Retailing, Vol.72,No.3, pp.249-271,1996
    33.Seifert, D. ,“Collaborative Planning, Forecasting and Replenishment,” Preprint Edition, pp.39-52, 2002
    34.Stank, T. P. and Keller, S. B. ,“Supply Chain Collaboration and Logistical Service performance,” Journal of Business Logistics, Vol22, No.1, pp.29-45, 2001
    35.Voss, G. B. and Seiders, K. ,”Exploring the Effect of Retail Sector and Firm Characteristics on Retail Price Promotion Strategy,” Journal of Retailing, Vol. 79, pp.37-52, 2003
    36.Wilson, N. ,”Game Plan for A Successful Collaboration Forecasting process,” the Journal of Business Forecasting, Vol.20,No.1, pp.2-6, 2001
    描述: 碩士
    國立政治大學
    資訊管理研究所
    91356005
    92
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G0091356005
    資料類型: thesis
    顯示於類別:[資訊管理學系] 學位論文

    文件中的檔案:

    檔案 描述 大小格式瀏覽次數
    35600501.pdf39KbAdobe PDF21182檢視/開啟
    35600502.pdf81KbAdobe PDF21246檢視/開啟
    35600503.pdf81KbAdobe PDF21236檢視/開啟
    35600504.pdf109KbAdobe PDF21239檢視/開啟
    35600505.pdf112KbAdobe PDF21513檢視/開啟
    35600506.pdf95KbAdobe PDF22213檢視/開啟
    35600507.pdf221KbAdobe PDF23419檢視/開啟
    35600508.pdf204KbAdobe PDF26340檢視/開啟
    35600509.pdf158KbAdobe PDF22241檢視/開啟
    35600510.pdf84KbAdobe PDF21424檢視/開啟
    35600511.pdf91KbAdobe PDF21891檢視/開啟
    35600512.pdf154KbAdobe PDF21459檢視/開啟


    在政大典藏中所有的資料項目都受到原著作權保護.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回饋