The framework of competitive advantage based chance discovery
Chao-Fu Hong, Leuo-hong Wang, Jheng-Long Wu · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · 2008
To analyze the competitive advantage, the analyst has to collect and analyze useful news. Therefore, the text mining technology is necessary for extracting information from the collected news. Both data mining and text mining are, as we know, frequency based methods; the low frequency data are usually deleted to discover the associative rules. As a result, some rare but actually important events for future are also deleted. Chance discovery, a discipline that focuses on revealing rare but important events, can solve the problem mentioned above to some extent. However, the canonical scenarios, which are used to assist in identifying rare events within the chance discovery process, are manually determined by participators. The work would be very complicated while data are numerous. A framework that fuses Porter's five forces and the strategy of competitive advantage has thus been proposed in this paper. Both concepts fused are utilized to automatically define scenarios. Furthermore, the scenarios determined by the proposed framework could be zoomed in / out under the direction of participators. In other words, the amount of data viewed by participators at a time is under control. Cases concerning the optical disk industry in Taiwan have been studied by using our framework. The experimental results indicated that CMC was as good as the Ritek and Prodisk in both CD and DVD techniques. Subsequently, both CMC and Ritek were better than Prodisk in the double layer products. Finally, CMC became the best in developing Blue-Ray products. These analyses verified the company whose competitive advantages are superior to others will have a great chance to success in the market.