Pursuing excellence in firm core knowledge through intelligent group decision support system

Chinho Lin, Ming Lung Hsu, Andrea Liu, J. C. Ju-Chuan

Research output: Contribution to journalArticle

22 Citations (Scopus)

Abstract

Purpose The paper's objective is to present a group decision support system (GDSS) for facilitating the process of core knowledge selection. Design/methodology/approach The proposed GDSS is developed by taking advantage of the characteristics of certain existing analytical and mathematical methods, including knowledge-based SWOT analysis, knowledge audit instruments, gap analysis, synergy analysis, similarity measures, multi-objective linear programming (MOLP), and fuzzy programming. A case study was performed to identify whether or not the GDSS achieves its designed purpose. Findings The results show that GDSS can be applied effectively in identifying core knowledge that should be developed. Practical implications The proposed GDSS provides a comprehensive procedure for top managers, using a strategy-orientated perspective to determine suitable core knowledge to be developed by appropriately analyzing internal synergy and external gap effects on core knowledge. Top managers need not only be aware of the relationship between core knowledge and other factors but must also consider decision-making problems related to this issue. Originality/value Few prior studies have provided a systematic approach for develops organizational core knowledge by using analytical and mathematical methods. This paper particularly focuses on the question of how firms can actually identify core knowledge and thus develop appropriate strategies.

Original languageEnglish
Pages (from-to)277-296
Number of pages20
JournalIndustrial Management & Data Systems
Volume108
Issue number3
DOIs
Publication statusPublished - 2008 Mar 21

All Science Journal Classification (ASJC) codes

  • Management Information Systems
  • Industrial relations
  • Computer Science Applications
  • Strategy and Management
  • Industrial and Manufacturing Engineering

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