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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/33257

    Title: 應用分析網路程序法預測臺灣廢印表機營業量之研究
    Other Titles: Application of ANP in forecasting sales volume of printer in Taiwan.
    Authors: 莊舜翔;Chuang, Shun-hsiang
    Contributors: 淡江大學管理科學研究所碩士班
    時序時;Shih, Hsu-shih
    Keywords: 預測;分析網路程序法;資源回收;印表機營業量;兩兩成對比較;相依性;模糊;Forecasting;Analytic Network Process;resources recycling;sales volume of printer;pair comparison;dependence;Fuzzy
    Date: 2009
    Issue Date: 2010-01-11 03:48:15 (UTC+8)
    Abstract: 本研究利用分析網路程序法 (Analytic Network Process, ANP),透過擷取專家經驗與判斷,進行台灣地區印表機營業量之預測。期望在難以獲得大量歷史資料且涉及社會層面廣泛時,利用關係人的意見以及兩兩成對比較之一模糊方式,建構ANP預測模型。其後再進行敏感度分析以驗證本模型之穩健性後,並與環保署基管會現行統計方法進行比較,以確認本法之適用。
    This research apply Analysis Network Process (ANP) to collect experts’ judgments on forecasting sales volume of printer in Taiwan through pairwise comparison. When lacking of history data and clarity of social impacts, ANP technique can be constructed for forecasting. A sensitive analysis is also made to assure the forecasting model to be robust.
    Because the global warming and our ecological system are changed seriously, our concerns are forced to these issues. In 1971, Environmental Protection Administration (EPA) of R.O.C. government had started some actions on waste clean-up and resources recycling and established some regulations to improve recycling rate to decrease environmental deterioration. The used printers belong to one major part among electronic wastes, and the amount of printers to selling and recycling are difficult to estimate due to the complicated customers’ behavior and economic situation.
    In the year of 2001, Recycling Fund Management Board (RFMB) of EPA initiates the action of recycling used printers in Taiwan. The Board collects funds from manufacturers and importers when they sell or import printers, and subsidize recycling industries with recycling and treatment fee to increase recycling ratio. Sales volume and waste collected volume are the major factors for setting up the fee, and both are relied on forecasting. Therefore, the accuracy of forecasting has a great impact on the performance of recycling.
    There are a couple of limitations in conducting traditional forecasting tools, most of them are statistical methods. The first one is that the methods need sufficient amount of data, which might be impossible sometime. The second one is that they are hard to response the real-time moves. Processing dependence among concerned factors of the real world is the most unfavorable limitation. Hence, we choose ANP to divert the limitations, and establish a forecasting model with good performance and a flexible structure for recycling printers.
    Appears in Collections:[管理科學學系暨研究所] 學位論文

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