An Analytic Approach for Logistics Performance Indicators and Process Relevance

• Main Authors: Hung-Yi Lin, 林泓毅
• Other Authors: Li-Chih Wang
• Format: Others
• Language: zh-TW
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/64154019565423275832

碩士 === 東海大學 === 工業工程與經營資訊學系 === 94 === An effective system to measure the logistics performance should come along with logistics process and performance indicators. Based on these indicators, it is doable to conduct management and improvement of logistics process to enhance its performance. Typically, enterprises judge effectiveness by the exhibition of indexes when they conduct logistics performance indicators. However, it has difficulty in finding out causes according to the exhibition of indicator which has been thought as a result. To enhance business performance, enterprise managers need to review critical factors to get improvements quickly based on various analyses of relevance. Historically, researches have been focused on either connections of performance indicators or relationships between indicator and the frame of process. However, it may face challenges to know relevance without an overall viewpoint. For these reasons, this research suggests a general analytic approach to assist enterprises in analyzing direct and indirect relevance of logistics performance with processes. Based on Supply Chain Operation Reference (SCOR) Model, it will apply Vensim in construction and analysis. To sum up, this research provides three key issues as follows: 1.Address an analytic approach based on process to analyze the relevance between performance indicators and processes. 2.It is insufficient for the business to improve logistics performance without knowing the deficiency actually. Detecting where the variance is in advance will be time-saving for managers to prevent business from abnormal situations. 3.Taking textile industry for a case study, this research concludes a model of processes and logistics performance on the basis of SCOR to process relevance analysis.