| 研究生: |
游騰熙 Yu, Teng-hsi |
|---|---|
| 論文名稱: |
前置時間變動資訊分享下供應鏈長鞭效應之研究 Studying the Bullwhip Effect on the Supply Chain Management by Sharing Lead Time Variation Information |
| 指導教授: |
王泰裕
Wang, Tai-Yue |
| 學位類別: |
碩士 Master |
| 系所名稱: |
管理學院 - 工業與資訊管理學系 Department of Industrial and Information Management |
| 論文出版年: | 2008 |
| 畢業學年度: | 96 |
| 語文別: | 中文 |
| 論文頁數: | 60 |
| 中文關鍵詞: | 前置時間 、長鞭效應 、供應鏈管理 |
| 外文關鍵詞: | supply chain management, bullwhip effect, lead time |
| 相關次數: | 點閱:87 下載:2 |
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面對全球化的競爭環境下,企業與企業間的競爭演變成供應鏈與供應鏈的競爭,因此,供應鏈相關議題與現象的探討愈顯重要。由於供應鏈上存貨補貨方式所產生的長鞭效應(bullwhip effect)對於整體存貨成本有很大的影響,所以已有許多學者進行長鞭效應相關的探討。以往的研究多以固定前置時間為前提,著重在不同需求型態或是不同的預測方式等進行探討,對於前置時間發生變動的情形並沒有直接的討論,因此,本研究將探討在前置時間可能發生變動的情形下造成交貨延遲的長鞭效應。本研究之目的為瞭解前置時間可能發生變動,並且在下一期此延遲資訊會分享給零售商的狀況下,影響長鞭效應的因素,因此,建立了一個二階單一商品的供應鏈模式,並且使用ARIMA預測方法預測未來需求,搭配提出的延遲訂購修正方法來進行訂購量修正。利用模擬產生的時間序列需求資料,模擬不同前置時間長度、延遲時間長度以及發生延遲機率大小的不同對於訂購端與存貨端長鞭效應的影響,由模擬結果可以得知使用訂購修正方法與否在上述不同條件下的長鞭效應變化情形,提出在不同範圍的條件下建議使用的訂購方式。
In the global competition environment, the competition among enterprises has been changed to the competition among supply chain. For this reason, the supply chain management related issues become more and more important. The bullwhip effect in the supply chain will cause the additional inventory costs, so it is a critical issue in supply chain management. Though many scholars have discussed bullwhip effect related issues, most of the studies focused on the different demand distributions or forecasting methods under the assumption of constant lead time. This study discusses how the lead time variation influences on the bullwhip effect. The purpose of this study is to understand how the factors affect the bullwhip effect in the supply chain with sharing lead time variation information. This study constructs a two-stage supply chain model with single product, applies ARIMA to forecast the future demand, and proposes a method to adjust the order quantity when the previous order is delayed. This study applies simulated time series of demand data to simulate with different settings of lead time, delay time, the probability of delay occurrence, and use adjusting method or not, to understand the bullwhip effect changes in the different conditions. Finally, suggesting in what situations should use the adjusting method to get less bullwhip effect.
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