Data-Driven Network Visualization for Innovation and Competitive Intelligence Sarica, Serhad Yan, Bowen Bulato, Gerardo Jaipurkar, Pratik Luo, Jianxi 2019-01-02T23:38:00Z 2019-01-02T23:38:00Z 2019-01-08
dc.description.abstract 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.
dc.format.extent 9 pages
dc.identifier.doi 10.24251/HICSS.2019.017
dc.identifier.isbn 978-0-9981331-2-6
dc.language.iso eng
dc.relation.ispartof Proceedings of the 52nd Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.subject Business Intelligence and Big Data for Innovative and Sustainable Development of Organizations
dc.subject Collaboration Systems and Technologies
dc.subject Competitive intelligence, data-driven, InnoGPS, innovation, technology space
dc.title Data-Driven Network Visualization for Innovation and Competitive Intelligence
dc.type Conference Paper
dc.type.dcmi Text
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