An Integrated of Earned Value Management on Performance of Purchasing Project

• Main Authors: Shun-Yuan Yao, 姚舜淵
• Other Authors: Nai-Chien Wei
• Format: Others
• Language: en_US
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/5jy759

博士 === 義守大學 === 工業管理學系 === 107 === There are three important management objectives of Project Management: Schedule, Performance and Cost. The success of a project involves ten knowledge Areas and five process groups, when the project is executed, comprehensive monitoring is required to truly implement the project management objectives. However, project team will report the progress of task completion to project manager in percentage way. Because of the different property of the project task, the percentage of the completion of the task is defined in different ways. Therefore, it is difficult for the project manager to control the actual progress of each project task based on the percentage. As a result, all project of schedules and progress are converted to “amounts” using the Earned Value Management (EVM). Compare with the initial budget amount to mean the actual progress of the project task. The EVM can provide an indicator for integrating assessment of schedule performance and cost performance index. But there are still several defects in practicality, such as: (1) will increase management costs. (2) The Earned Value does not provide a forecast of the success or failure for the procurement project. (3) The assessment of index cannot distinguish importance. To handle these defects, the research proposed an integrated EVM perspective which can predict the success rate of procurement projects and rank the importance of the evaluation variables. In order to verify the model of integrated EVM in this study. Introduced by the EVM to evaluation second source of raw materials into the enterprise project procurement. Exploring whether the project schedule is ahead or behind and the project budget is overrun or meets the budget and establishes countermeasures. Then it can use the Logistic Regression Analysis to build a prediction model. With the Expert Weighting Method (EWM), select and analyze the importance ranking of the five variables affecting the project procurement evaluation. The conclusion of this study that the Cost Performance Index "CPI" in the variable affect the probability of successful forecast greatly. When CPI=1 is considered separately in the material second source of evaluation of the implementation. The probability of predicting success is as high as 71.26%. The importance of impact assessment variables is most important with CPI. Purchasing experts pay more attention to CPI in the second source of material assessment. The results can be used as a catalyst for future work related to improving the performance of procurement projects.