Intelligent Business Process Reengineering Support System

• Main Authors: Yiu, Su-Wen, 游淑文
• Other Authors: Wei, Chih-Ping
• Format: Others
• Language: en_US
• Published: 1999
• Online Access: http://ndltd.ncl.edu.tw/handle/53758517086538653813

碩士 === 國立中山大學 === 資訊管理學系 === 87 === In the fast-paced global economy, organizations have aspired to reevaluate their business performance and reengineer (or redesign) their business processes in order to create or maintain competitive advantage. Business process reengineering represents an unstructured problem. In practice, many organizations rely on reengineering experts to develop reengineering strategies for a business process to be redesigned. This thesis adopted the process measure-pathology-reengineering strategy approach to develop an intelligent business process reengineering system. The intelligence feature of the proposed system lies in its inductive learning capability. That is, given a set of previously reengineering cases, the system learns from these examples a set of reengineering knowledge essential to supporting or automating reengineering activities. Due to such unique characteristics as interval-scaled input attributes and multiple decision outcomes possibly with dependencies, this research extended an existing inductive learning algorithm, and proposed the CN2-MD/DD algorithm. The evaluation result showed that CN2-MD/DD could achieve satisfactory learning performance in recall, precision and accuracy measures.