Applying Data Envelopment Analysis to Evaluating the Influence of Launching ERP System for the Enterprise on the Company’s Operation Performance —An Example of the Listed Companies of the High -Tech Electronic Industry

• Main Authors: You-Lin Shie, 謝侑霖
• Other Authors: Tang, Hui-Chin
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/nv2hnc

碩士 === 國立高雄應用科技大學 === 工業工程與管理系碩士班 === 102 === Along with continue to progress science and technology, information technology has become the most efficient use of system tools, the general electronic manufacturing, information technology degree the generally low, when company want enhance their competitiveness and the need to construct "information technology" to provide basic business elements, and important core architecture of "information technology" is "enterprise resource planning system." as enterprises to import before the erp system must first assess the company's operating performance is helpful, this research company erp system time basis, and to explore from the republic of china 88 years to 99 years a total of 12 years, and using data envelopment analysis (data envelopment analysis, dea ) as a the performance evaluation model; to use as management costs for the four for listed electronic manufacturing industries, number of employees current asset input variables; operating income, the average earnings employees in order to be used as output variables. Statistics show that for the electronics manufacturing industry through four key input-output model, with efficiency analysis, the difference between the variable analysis, correlation coefficient, sensitivity analysis and window analysis, production resource utilization, as well as the direction for the company to improve efficiency and a measure of changes in total productivity across. The empirical results, the analysis by the window period of three years as a benchmark to evaluate the operation of the ERP implementation scenario is showing growth or decline, and finally to shave the input-output sensitivity analysis to identify the appropriate term significant project, as a business measurable indicators.