A rough set approach to knowledge discovery in analyzing competitive advantages of firms

Competitive advantage analysis (CAA) is still an important issue of strategic management research. Although many studies are developed on this topic, they remain conceptual and descriptive, and it is difficult to make them operational in practice. Therefore, this article proposes an intelligent decision support approach for solving such a difficulty. The proposed approach integrates soft computing, rough set theory, and group decision making technique. In this study, CAA is considered as a multiple criteria sorting problem with multi-granularity linguistic assessment information. An algorithm based on linguistic computing is first presented to construct the decision table of exemplary decisions, and then the extended rough set theory and dominance functions are taken to induce a set of decision rules that satisfy a minimum support threshold. These rules can explicitly describe the relationship between the competitive advantage positions and the key determinant factors of competitive advantage. Finally, a numerical example is used to illustrate the application of the proposed approach.