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.