New knowledge in strategic management through visually mining semantic networks

Gürdal Ertek, Gül Tokdemir, Mete Sevinç, Murat Mustafa Tunç

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)165-185
Number of pages21
JournalInformation Systems Frontiers
Issue number1
Publication statusPublished - Feb 1 2017
Externally publishedYes


  • Graph visualization
  • Information visualization
  • Knowledge generation
  • Knowledge representation
  • Semantic networks
  • Strategic management

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Information Systems
  • Computer Networks and Communications


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