TY - JOUR
T1 - New knowledge in strategic management through visually mining semantic networks
AU - Ertek, Gürdal
AU - Tokdemir, Gül
AU - Sevinç, Mete
AU - Tunç, Murat Mustafa
N1 - Funding Information:
This work is supported by State Key Laboratory for Mechanical Behavior of Materials under Grant No. 20161808, the Natural Science Foundation of China under Grant No. 51402255, the Jiangsu Natural Science Foundation of China under Grant No. BK20140487 and the Funding of Jiangsu Innovation Program for Graduate Education under Grant No. KYZZ16-0490. This is a project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions and the Testing Center of Yangzhou University and the Testing Center of Yangzhou University.
Publisher Copyright:
© 2015, Springer Science+Business Media New York.
PY - 2017/2/1
Y1 - 2017/2/1
N2 - 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.
AB - 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.
KW - Graph visualization
KW - Information visualization
KW - Knowledge generation
KW - Knowledge representation
KW - Semantic networks
KW - Strategic management
UR - http://www.scopus.com/inward/record.url?scp=84944710295&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84944710295&partnerID=8YFLogxK
U2 - 10.1007/s10796-015-9591-0
DO - 10.1007/s10796-015-9591-0
M3 - Article
AN - SCOPUS:84944710295
SN - 1387-3326
VL - 19
SP - 165
EP - 185
JO - Information Systems Frontiers
JF - Information Systems Frontiers
IS - 1
ER -