Description
Competitive intelligence (CI) is the practice of studying competitors and competitive environment in support of firm’s strategic decision-making process. Currently, competitors are usually studied from business profile information and reports edited by CI professionals. While being inefficient and expensive in labor and resources, their results are often incomplete and lack objectivity. Some existing literatures introduced text mining to leverage Web information for CI usage. Despite improving on coverage, most of these analyses identify competitors using name co-occurrences from a single data source. The validity and reliability of these studies remain questionable. Our experiment demonstrates that syntactic level text mining can lead to improvements on CI performance. It also shows that the selection of different online data sources and competitor name extraction methods have different implications on CI outcome.
Recommended Citation
Dasgupta, Subhasish; Xue, Yuan; and Zhou, Yilu, "Examining Competitive Intelligence Using External and Internal Data Sources: A Text Mining Approach" (2015). AMCIS 2015 Proceedings. 40.
https://aisel.aisnet.org/amcis2015/BizAnalytics/GeneralPresentations/40
Examining Competitive Intelligence Using External and Internal Data Sources: A Text Mining Approach
Competitive intelligence (CI) is the practice of studying competitors and competitive environment in support of firm’s strategic decision-making process. Currently, competitors are usually studied from business profile information and reports edited by CI professionals. While being inefficient and expensive in labor and resources, their results are often incomplete and lack objectivity. Some existing literatures introduced text mining to leverage Web information for CI usage. Despite improving on coverage, most of these analyses identify competitors using name co-occurrences from a single data source. The validity and reliability of these studies remain questionable. Our experiment demonstrates that syntactic level text mining can lead to improvements on CI performance. It also shows that the selection of different online data sources and competitor name extraction methods have different implications on CI outcome.