Knowledge management in an agent -based environmental scanning system

• Main Author: Song, Seokwoo
• Format: Dissertation
• Language: English
• Published: ProQuest Dissertations & Theses 01-01-2001
• Subjects: Business administration; Business community; Decision making; Environmental monitoring; Environmental scanning; Information science; Information sources; Information systems; Knowledge management; Software; Strategic planning; Studies
• ISBN: 9780493185804; 0493185801

Precise environmental scanning is critical to organizational success because of the greater uncertainty in today's business environment. Environmental scanning helps an organization adapt to changing external circumstances (Hambrick, 1982), and can provide ‘signals’ for identifying threats and opportunities and gaining competitive advantages. Traditionally, environmental scanning groups included intelligence analysts and area specialists. The results of a scanning process and the performance of an organization primarily depended upon the abilities of these scanning personnel. Today, however, the business world environment has become more complex and uncertain than ever. Most organizations are overwhelmed by the huge volume of internal and external information. The exhaustive search, analysis, and proper interpretation of this information cannot be accomplished by traditional methods. The software agent approach and information retrieval techniques show great potential for effectively managing information for strategic decision making (King and O'Leary, 1996). Little attention, however, has been paid to integrating those technologies into the scanning process related to information acquisition and information dissemination. This study proposes a computer-mediated environmental scanning system, called the Agent-Based Environmental Scanning System (ABESS). ABESS incorporates: (1) Strategies for coordination of agents and utilization of information retrieval techniques in order to manage scanning activities such as information gathering, information filtering, and information dissemination, and (2) Strategies for knowledge management to promote effective knowledge sharing. ABESS includes four major processes for the solution process: (1) building search profile, (2) refining retrieved documents, (3) integrating and organizing knowledge base, and (4) sharing knowledge. ABESS was designed and implemented to validate this architecture. Then, experiments were conducted to examine the effectiveness of the current implementation of ABESS in relation to the information refining process. The results indicated that the automated refining process of ABESS produced a larger number of relevant documents than the manual filtering process and that ABESS could provide great benefits to users for gathering and refining information. Findings also provided valuable insight into computer-mediated system design related to the scanning process.