9th Joint International Conference on Information Sciences (JCIS-06)

Discovering Hidden Blue Ocean Strategy with KeyGraph Machine

Authors
Fang-Cheng Hsu 0, Han_Yuan Lee, Tzong-Heng Chi
Corresponding Author
Fang-Cheng Hsu
0Department of Information Management, Aletheia University
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DOI
https://doi.org/10.2991/jcis.2006.209How to use a DOI?
Keywords
Chance discovery, Blue ocean strategy, Strategy discovery
Abstract
Researchers usually focused on using unstructured documents as input documents of KeyGraph. But the unstructured documents might results in unclear keywords and meaningless keywords. Although traditional document preprocessing could dismiss some of the problems, generating complex and unreadable KeyGraph diagrams were not avoidance. In this research, we applied the concept of chance discovery and KeyGraph to discover hidden blue ocean strategy (BOS) for decision makers who not necessary familiar with the concerned domains. A preprocessing strategy, including develop an operational framework of BOS and design a sentence structure for representing BOS, was proposed to assure the necessary keywords be included in the required documents. Seventy-two documents concerning blue ocean firms were collected as sample cases for developing the operational framework. Three experiences were designed for confirming the performance of the proposed preprocessing strategy.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
9th Joint International Conference on Information Sciences (JCIS-06)
Publication Date
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ISBN
978-90-78677-01-7
DOI
https://doi.org/10.2991/jcis.2006.209How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Fang-Cheng Hsu
AU  - Han_Yuan Lee
AU  - Tzong-Heng Chi
PY  - NaN/NaN
DA  - NaN/NaN
TI  - Discovering Hidden Blue Ocean Strategy with KeyGraph Machine
BT  - 9th Joint International Conference on Information Sciences (JCIS-06)
PB  - Atlantis Press
UR  - https://doi.org/10.2991/jcis.2006.209
DO  - https://doi.org/10.2991/jcis.2006.209
ID  - HsuNaN/NaN
ER  -