| 研究生: |
梁家隆 Liang, Chia-Lung |
|---|---|
| 論文名稱: |
在資訊不對稱下建構製造商印量決策與合約設計最佳化:以台灣教育出版業為實證研究 Manufacturer’s Printing Decision and Contract Design Optimization under Information Asymmetry: An Empirical Study of Taiwan Educational Publishing |
| 指導教授: |
李家岩
Lee, Chia-Yen |
| 學位類別: |
碩士 Master |
| 系所名稱: |
電機資訊學院 - 製造資訊與系統研究所 Institute of Manufacturing Information and Systems |
| 論文出版年: | 2016 |
| 畢業學年度: | 104 |
| 語文別: | 中文 |
| 論文頁數: | 95 |
| 中文關鍵詞: | 需求預測 、產能規劃 、合約設計 、教育出版業 |
| 外文關鍵詞: | demand forecasting, capacity planning, contract design, Taiwan educational publishing |
| 相關次數: | 點閱:92 下載:0 |
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教育出版是指與學習、教育及培訓有關的出版,這是一種產品最有模式化、標準化,而過程最複雜、計畫性最高的出版。由於其產業特性屬於計畫式生產,預測變數大,導致產生大量庫存,且每年庫存報廢高達上千萬元,由此可見良好的印量預測模型及存貨管理對於教育出版業是相當重要的;在產業供應鏈間資訊不對稱下,製造商並非獲取第一手的銷售資訊,在需求預測及存貨管理更是一大挑戰,透過合約設計促使經銷商願意提供真實資訊,提升整體供應鏈與製造商的獲利,亦利於印量預測模型與決策機制的最佳化。
本研究主要以國中升高中的輔助教材為研究對象,印量決策主要分成兩階段,第一階段為透過資料探勘技術建構教育出版業的輔助教材之印量預測模型;第二階段為分別以綜合訂購、隨機規劃及最小最大悔惜建構決策架構,希望透過良好的印量預測模型與決策機制(包含:印量決策點有初版印量、再版印量與時間點),因應教育出版業現今高退貨率及必須對輔助教材滯銷的困境,找到最佳的利基點。合約設計主要利用篩選機制(Screening)獲取經銷商的資訊,透過合約設計篩選不同資訊的經銷商,以獲取經銷商資訊,進而提升整體供應鏈及製造商獲利。本研究提升預測能力3.7%、降低總成本8.3%、提升整體供應鏈0.5%以及製造商獲利比2.7%。
Educational publication is a kind of publishing which is related to learning, education and training. It’s the most module and standardize product, however the process of this product is the most complex and need to be highly planning. Due to feature of publishing industry which is making to stocks, the predicting variable of the printing volume is huge and also cause huge amount of inventory. Moreover, up to ten billions inventories were scrapped every year. Therefore, developing a good model of printing volume and managing inventory have significant effect of educational publication. Under conditions of asymmetric information, manufacturers cannot acquire the first-hand information, so demand forecasting and inventory management are big challenges for them. So if we can encourage retailers to provide factual information through contract design; profit abilities of overall supply chain and manufacturers may be enhanced and the optimization of prediction on print volume and decision mechanism may be achieved.
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校內:2021-06-20公開