The construction and analysis of Performance Measurement Index for Enterprise’s Knowledge Management

• Main Authors: Liu Tzu Yu, 劉姿妤
• Other Authors: 謝秉蓉
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/96926918526771021029

碩士 === 國立高雄師範大學 === 人力與知識管理研究所 === 100 === Abstract As the continuing development of knowledge economic and network society, the efficiency of the practice and extension of knowledge assets in organizations has become the main competitive factor. To increase organizational performance, enterprises are more focus on knowledge managing, sharing and performance. Most of the past references/researches were focused on individual cases of knowledge management activity in Qualitative analysis method or Quantitative analysis method. However, this approach lacks of establishing systematic structure of Knowledge management evaluation and converting knowledge management into measurable and quantitative objective standard. Consequently, this research is concentrated on the aspect of Knowledge management performance measurement with well-known models to draw up a systematic method which could provide enterprises to measure performance. Research subjects are consisted of top one thousand firms of manufacturing industry and top five hundred companies of service industry in Taiwan and the focal point is to understand how companies value knowledge management performance and what level of satisfactory they present after implementing Knowledge management. The research is preceded with questionnaire investigation and a total of seventy four valid questionnaires are applied to this research. The raw data is analyzed by factor analysis, reliability analysis and Paired-Samples t Test. The result indicated: 1. Knowledge management performance of actual satisfactory level and awareness level in different geographical districts – correlation is not significant. 2. Knowledge management performance of actual satisfactory level and awareness level in different industries - correlation is not significant. Keywords: Knowledge Management, Knowledge Management Performance, Knowledge Management Measurement