Innovation patterns of big data technology in large companies and start-ups: an empirical analysis

Abstract

With the unprecedented growth in information technology, the importance of big data analytical skills has grown exponentially. Therefore, it is important to understand innovations in big data and related technologies. Since large companies and start-ups are considered the principal sources of innovation, we investigate their innovation patterns pertaining to big data. We analyse all the patents in the G06F-17/30 class in the United States Patent and Trademark Office (USPTO) for 2017 and use hierarchical clustering, word stems analysis and minimum spanning tree to classify the patents as part of an exploratory research. Our results show that large companies concentrate on B2C businesses, such as entertaining and interacting skills, whereas start-ups focus on niche markets, such as materials, components and social media. Our paper contributes to a more a comprehensive understanding of future technologies and the decisions for investments by venture capitalists and governments.