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Testing the Relationship Between Information and Knowledge in Computer-Aided Decision-Making

Author

Listed:
  • Yuan Li

    (University of Tennessee)

  • William J. Kettinger

    (Clemson University)

Abstract

Information and knowledge are two foundational concepts in Information Systems (IS) research, but their relationship remains vague, and researchers continue to use them interchangeably in studies. This limits the ability to clearly specify what information is in the systems and how it is used for operations and decisions. We address the issue in the context of computer-aided decision-making. In contrast to the traditional view that information is the input of knowledge, we argue, from the knowledge-based view of information, that information is produced from knowledge and functions as the basis of decisions. Further, cognitive factors such as one’s general knowledge in the task domain and guidance in decision aids influence knowledge and information for decisions. An information-centric framework is developed and tested based on a popular production-planning decision task. The result supports the direct impact of information on decisions and the indirect impact of knowledge via its influence on information. This study is the first to empirically test the relationship between knowledge and information in IS research. It calls for more attention to the information concept and how it is processed in IS.

Suggested Citation

  • Yuan Li & William J. Kettinger, 2022. "Testing the Relationship Between Information and Knowledge in Computer-Aided Decision-Making," Information Systems Frontiers, Springer, vol. 24(6), pages 1827-1843, December.
    • Handle: RePEc:spr:infosf:v:24:y:2022:i:6:d:10.1007_s10796-021-10205-w
    DOI: 10.1007/s10796-021-10205-w
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