A network analysis using metadata to investigate innovation in clean-tech – Implications for energy policy. (November 2015)

• Record Type: Journal Article
• Authors: Marra, Alessandro; Antonelli, Paola; Dell'Anna, Luca; Pozzi, Cesare
• Is Part Of: Energy policy. Volume 86(2015)
• Page Start: 17
• Page End: 26
• Publication Date: 2015-11
• Subjects: Clean-technology -- Industry studies -- Innovation -- Network analysis -- Energy policy -- CrunchBase; Energy policy -- Periodicals; Politique énergétique -- Périodiques; Electronic journals; 333.79
• DOI: 10.1016/j.enpol.2015.06.025
• Languages: English
• ISSNs: 0301-4215

Abstract

Abstract: Clean-technology (clean-tech) is a large and increasing sector. Research and development (R&D) is the lifeline of the industry and innovation is fostered by a plethora of high-tech start-ups and small and medium-sized enterprises (SMEs). Any empirical-based attempt to detect the pattern of technological innovation in the industry is challenging. This paper proposes an investigation of innovation in clean-tech using metadata provided by CrunchBase. Metadata reveal information on markets, products, services and technologies driving innovation in the clean-tech industry worldwide and for San Francisco, the leader in clean-tech innovation with more than two hundred specialised companies. A network analysis using metadata is the employed methodology and the main metrics of the resulting networks are discussed from an economic point of view. The purpose of the paper is to understand specifically specializations and technological complementarities underlying innovative companies, detect emerging industrial clusters at the global and local/metropolitan level and, finally, suggest a way to realize whether observed start-ups, SMEs and clusters follow a technological path of complementary innovation and market opportunity or, instead, present a risk of lock-in. The discussion of the results of the network analysis shows interesting implications for energy policy, particularly useful from an operational point of view. Highlights: Metadata provide information on companies' products and technologies. A network analysis enables detection of specializations and complementarities. An investigation of the network allows to identify emerging industrial clusters. Metrics help to appreciate complementary innovation and market opportunity. Results of the network analysis show interesting policy implications.