An Evolutionary Information-Processing Theory of Knowledge Creation

Yuan Li, University of South Carolina
William J. Kettinger, University of South Carolina

Abstract

Past Information Systems (IS) research on knowledge creation has not adequately accounted for the evolutionary nature of knowledge. Research limitations also exist in depicting the roles of information in the knowledge creation process. These two problems present difficulties for practitioners when attempting to successfully implement Information Technology (IT) to facilitate knowledge creation. Based on a problem-solving paradigm, this research analyzes knowledge creation from both the evolutionary and information-processing perspectives. The resultant theory outlines a process whereby tentative knowledge is generated from varied existing knowledge and applied to a problem, producing information to test the extent to which the problem can be solved. An iterative process continues until the tentative knowledge with the highest potential to solve the problem is found, yielding the information to best meet the goal. This process is further embedded in an organization-wide problem-solving hierarchy where new knowledge is developed via the integration of knowledge elements of sub-problems. By incorporating the evolutionary nature of knowledge, this research provides a deeper understanding of the knowledge creation process and the key determinants of its success. More importantly, by clearly specifying the roles of information in the process, it offers promise in the better design of IT to improve knowledge creation performance. We develop a framework based on this Evolutionary Information-Processing Theory to aid practitioners in IS design.

Recommended Citation

Li, Yuan and Kettinger, William J. (2006) "An Evolutionary Information-Processing Theory of Knowledge Creation," Journal of the Association for Information Systems: Vol. 7: Iss. 1, Article 25.
Available at: http://aisel.aisnet.org/jais/vol7/iss1/25