A knowledge-based system for participatory competitive intelligence in enterprise decision making


Existing Competitive Intelligence (CI) systems are mostly designed for CI information delivery and lack the extending application for decision support. This study focuses on the improvement of CI’s application for decision and takes participatory decision support as research objective. This study seeks to build a CI knowledge model and to develop an application system by identifying concepts of and relations among the instance types, decision models, rules of thumb, and functional participation from the enterprise organization and CI news about competitors. This study uses knowledge base system development as a solution. This study uses knowledge-based system development as the approach of solving the research problem with the design of knowledge model as the core. Major research design components of this study includes: (1) a Domain Ontology for establishing common knowledge concepts and instances using is-a relations to express the knowledge categorization structure and to provide a standard terminology set for ontology communication; (2) a Task Ontology to establish an objective-oriented knowledge framework using has-a relations to express the combination of questions; and (3) Semantic Rules to develop the rules for inferring implicit knowledge. The case experiment results show that, under the condition of correct delivery of news entries, the individual news entries have achieved close to 100% correctness in Decision Model Correctness Rate and Departmental Weighting Correctness Rate. It is evidenced that the knowledge model proposed in this study has extended the application of CI from information delivery to the extended support for participatory decision.


Business and Information Technology

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Article - Journal

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