標題: | 低溫供應鏈脆弱度之影響因子分析 ─以Y肉品公司為例 The Critical Factors Affecting Vulnerability of Cold Chain : An Empirical Case of a Pork Company |
作者: | 呂佳娣 Lu , Chia-Ti 馮正民 謝承憲 Feng , Cheng-Min Hsieh , Cheng-Hsien 運輸與物流管理學系 |
關鍵字: | 冷鏈;肉品供應鏈;脆弱度;灰關聯分析;灰預測分析;cold chain;meat supply chain;vulnerability;grey relational analysis;grey predictive analysis |
公開日期: | 2013 |
摘要: | 在供應鏈成員日趨複雜的情況下,如何減少干擾事件發生的頻率和減緩其所帶來的損失,針對面臨危害之脆弱部分做防範並且有效地降低自身之脆弱度為管理供應鏈之核心議題。而低溫食品為國內目前生活重要的飲食供應方式之一,該供應鏈在整個過程中皆處於規定的低溫環境,每個環節都有可能出錯進而造成冷鏈斷裂,本研究選定台灣歷年每人肉品消費量比例最高的豬肉供應鏈作為主要研究對象,並以國內一家Y肉品公司進行實例分析。
本研究透過文獻彙整與訪談確認肉品供應鏈各節點之工作流程,並且確立出紙本訂單、作業場環境衛生、人工揀、理貨、倉儲環境衛生、倉儲溫度控管、運輸車溫度控管六項脆弱度指標,另以營業額作為企業績效指標。根據灰關聯分析研究結果顯示,在人工揀、理貨的部分,其實際操作上與其理想狀態的相符的程度為最高,灰預測分析結果亦是以人工揀、理貨之影響最大,為本研究所找出之關鍵脆弱指標。最後透過預測模型進行預測與驗證。本研究之成果,有助於業者改善資源配置之效率,研擬降低脆弱策略時優先順序之考量。 Because of the more complex relationships between members in supply chain, reducing the frequency of incidents, mitigating the damages caused by negative impacts, and protecting the critical elements from hazards to improve vulnerability become a core issue in supply chain management. The low temperature logistics (cold chain) plays an important role in providing domestic food supply chain nowadays, in which all the process should be monitored in the regulated low temperature environments. Any mistake in each node or link would break the clod chain. This study thus discuss the critical factors impacting the cold chain vulnerability and utilize a pork industry, the major meat consumed in Taiwan, as the empirical case. This study develops six cold chain vulnerability indicators including hard copy orders, environmental sanitation in operation sites and warehouse, accuracy of picking along with temperature control in warehouse and transportation, based on the procedures of pork supply chain according to literature review and field interview, and employs the turnover as the performance index. The results of grey relational analysis reveal that the accuracy of picking in actual operation and ideal status are the most consistent. Moreover, the results of grey prediction model determine the accuracy of picking as the most critical vulnerability factor influencing performance. The model proposed in this study is helpful for cold chain operators to efficiently allocate resources and prioritize strategies to improve the cold chain vulnerability. |
URI: | http://140.113.39.130/cdrfb3/record/nctu/#GT070153601 http://hdl.handle.net/11536/74470 |
Appears in Collections: | Thesis |