Data-Driven Intelligence on Innovation and Competition: Patent Overlay Network Visualization and Analytics

ABSTRACT

Technology positions of firms may determine their competitive advantages and innovation capabilities. While a tangible understanding of technology positions can inform competitive intelligence, they are heterogeneous, intangible and difficult to analyze. We introduce a data-driven network visualization and analysis methodology to assess and compare the technology positions of firms for competitive intelligence analytics based on patent data. This article demonstrates the methodology via comparative analyses of multiple firms for strategic insights on innovation and competition.

KEYWORDS:

• Patent data
• network analysis
• visualization
• automotive
• general motors
• autonomous vehicle

Acknowledgments

This research is supported by SUTD-MIT International Design Centre.

Notes

1. http://www.onstar.com.

2. https://techcrunch.com/2018/07/17/self-driving-car-startup-zoox-is-raising-500-million-at-a-3-2-billion-valuation/.

3. https://www.theverge.com/2017/10/24/16533534/delphi-nutonomy-acquisition-450-million-self-driving.

Additional information

Notes on contributors

Serhad Sarica

Serhad Sarica received his BSc and MSc in Electrical & Electronics Engineering from Middle East Technical University in 2007 and 2011 respectively. During the period 2007-2016, he worked as a system designer in Aselsan Co., Turkey, where he involved and led several naval communication systems design projects. He is currently pursuing a Ph.D. degree with the Engineering Product Development Pillar, Singapore University of Technology and Design (SUTD). His current research interests include change propagation in complex systems, network analyses and visualizations, semantic relations in the technology and innovation space, and utilization of natural language processing for engineering design and innovation.

Bowen Yan

Bowen Yan is currently a technical director/data scientist at a startup that provides technology intelligence services. She was a data scientist at SUTD-MIT International Design Center, Singapore University of Technology and Design, and also a visiting senior research fellow of Institute for Data, Systems, and Society, at Massachusetts Institute of Technology. Her current research interests are focused on the development of computational methodologies in the fields of network modeling and analysis, and the intersection of network science and data science that applies to innovation practices. She holds MSc and Ph.D. degrees in Computer Science from University of Bristol, UK.

Jianxi Luo

Jianxi Luo holds a Ph.D. degree in Technology Management and Policy from the Engineering Systems Division at Massachusetts Institute of Technology. He is currently an associate professor of engineering product development at Singapore University of Technology and Design (SUTD), where he leads the Data-Driven Innovation Lab (http://ddi.sutd.edu.sg). He is also associate director of the SUTD Technology Entrepreneurship Programme. His current research integrates network science, data science and innovation theories to develop artificial intelligence for innovation. His teaching is focused on technology entrepreneurship and innovation. He is also a chair emeritus of the Technology, Innovation Management and Entrepreneurship Section of the INFORMS.