Data-Driven Network Visualization for Innovation and Competitive Intelligence

Sarica, Serhad
Yan, Bowen
Bulato, Gerardo
Jaipurkar, Pratik
Luo, Jianxi
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Technology positions of a firm may determine its competitive advantages and innovation opportunities. While a tangible understanding of the technology positions of a firm, i.e., the set of technologies the firm has mastered, can inform innovation and competitive intelligence, yet such positions are heterogeneous, intangible and difficult to analyze. Herein, we present a data-driven network visualization methodology to locate the knowledge positions of a firm as a subspace of the total technology space for innovation and competitive intelligence analytics. The total technology space is empirically constructed as a network map of all patent technology classes and can be overlaid with the knowledge positions of a firm according to its patent records. This paper demonstrates how to use the system to conduct historical, comparative and predictive analyses of the technology positions of individual and different firms. The methodology has been implemented into a cloud-based data-driven visual analytics system – InnoGPS.
Business Intelligence and Big Data for Innovative and Sustainable Development of Organizations, Collaboration Systems and Technologies, Competitive intelligence, data-driven, InnoGPS, innovation, technology space
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