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New knowledge in strategic management through visually mining semantic networks

Author

Listed:
  • Gürdal Ertek

    (Dubai Silicon Oasis)

  • Gül Tokdemir

    (Cankaya University)

  • Mete Sevinç

    (Eindhoven University of Technology)

  • Murat Mustafa Tunç

    (The University of Texas at Dallas)

Abstract

Today’s highly competitive business world requires that managers be able to make fast and accurate strategic decisions, as well as learn to adapt to new strategic challenges. This necessity calls for a deep experience and a dynamic understanding of strategic management. The trait of dynamic understanding is mainly the skill of generating additional knowledge and innovative solutions under the new environmental conditions. Building on the concepts of information processing, this paper aims to support managers in constructing new strategic management knowledge, through representing and mining existing knowledge through graph visualization. To this end, a three-stage framework is proposed and described. The framework can enable managers to develop a deeper understanding of the strategic management domain, and expand on existing knowledge through visual analysis. The model further supports a case study that involves unstructured knowledge of profit patterns and the related strategies to succeed using these patterns. The applicability of the framework is shown in the case study, where the unstructured knowledge in a strategic management book is first represented as a semantic network, and then visually mined for revealing new knowledge.

Suggested Citation

  • Gürdal Ertek & Gül Tokdemir & Mete Sevinç & Murat Mustafa Tunç, 2017. "New knowledge in strategic management through visually mining semantic networks," Information Systems Frontiers, Springer, vol. 19(1), pages 165-185, February.
    • Handle: RePEc:spr:infosf:v:19:y:2017:i:1:d:10.1007_s10796-015-9591-0
    DOI: 10.1007/s10796-015-9591-0
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    References listed on IDEAS

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