Competitive Intelligence Task Analysis And Retrieval: An End-User Approach

Abstract

The Internet, as one of the major resources for competitive intelligence (CI), not only provides a large amount of public data but also exposes a variety of business relations that may not otherwise be well-known. However, finding such information can be tedious and time-consuming for end-users without proper tools or expertise. In this paper, we examine the nature of CI tasks, classify and decompose them based on a task complexity theory, and propose norms for a context-based approach to retrieve CI data. We developed a meta-search engine called Competitive Intelligence Task Analysis and Retrieval (CITAR) to demonstrate the feasibility of the proposed approach. The present study provides a framework to further explore the relationships among CI tasks, interactive search, and context-based search systems design.