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Emerging green-tech specializations and clusters – A network analysis on technological innovation at the metropolitan level

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  • Marra, Alessandro
  • Antonelli, Paola
  • Pozzi, Cesare

Abstract

Current models of production and energy use are promoting an effervescent green-technology (green-tech) market focused on innovation and improved environmental performance. Most green-tech firms are innovative start-ups or small and medium-sized enterprises (SMEs) characterized by large intangible assets and technological uncertainty, which makes it difficult to identify their research and development (R&D) and innovation paths. In addition, green-tech companies tend to aggregate spatially and, throughout the world, clusters are increasingly seen as a strategy to foster innovative production and R&D activities and stimulate a sustainable energy transition. This paper investigates green-tech companies in San Francisco, New York and London to identify their specialization and underlying technological and/or market complementarities, and emerging aggregates and specific clusters. Based on information from CrunchBase and the web, we propose a network analysis using metadata on technological innovations produced by green-tech companies in these three metropolitan areas. Metadata are keywords and terms that help to describe an item, and in the database they identify the products, services and technologies driving innovation. The main metrics of the networks identified (at both node and network level) are discussed from an economic perspective. The approach helps in the design and implementation of targeted and information-based local policies and facilitates closer relationships between innovative companies, suppliers and clients, venture capitalists, large corporations and research laboratories involved in the green-tech industry.

Suggested Citation

  • Marra, Alessandro & Antonelli, Paola & Pozzi, Cesare, 2017. "Emerging green-tech specializations and clusters – A network analysis on technological innovation at the metropolitan level," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 1037-1046.
    • Handle: RePEc:eee:rensus:v:67:y:2017:i:c:p:1037-1046
    DOI: 10.1016/j.rser.2016.09.086
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    2. Baoshan Ge & Fan Sheng & Yang Gao & Sang-Bing Tsai & Xiaomin Du, 2018. "“Green Ocean Treasure Hunting” Guided by Policy Support in a Transitional Economy," Sustainability, MDPI, vol. 10(2), pages 1-17, February.
    3. Miao, Chenglin & Fang, Debin & Sun, Liyan & Luo, Qiaoling, 2017. "Natural resources utilization efficiency under the influence of green technological innovation," Resources, Conservation & Recycling, Elsevier, vol. 126(C), pages 153-161.
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    5. Xie, Ronghui & Teo, Thompson S.H., 2022. "Green technology innovation, environmental externality, and the cleaner upgrading of industrial structure in China — Considering the moderating effect of environmental regulation," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    6. Liu, Weiwei & Song, Yifan & Bi, Kexin, 2021. "Exploring the patent collaboration network of China's wind energy industry: A study based on patent data from CNIPA," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    7. Zhao, Pan & Hu, Guoheng & Jin, Peizhen, 2023. "Biased technical change, capital deepening, and efficiency of environmental regulations: Evidence from the Chinese provinces," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
    8. Yongfang Peng & Yingying Fan & Yi Liang, 2021. "A Green Technological Innovation Efficiency Evaluation of Technology-Based SMEs Based on the Undesirable SBM and the Malmquist Index: A Case of Hebei Province in China," Sustainability, MDPI, vol. 13(19), pages 1-19, October.
    9. Michaela Trippl & Simon Baumgartinger-Seiringer & Alexandra Frangenheim & Arne Isaksen & Jan Ole Rypestøl, 2019. "Green path development, asset modification and agency: towards a systemic integrative approach," PEGIS geo-disc-2019_01, Institute for Economic Geography and GIScience, Department of Socioeconomics, Vienna University of Economics and Business.
    10. Tuochen Li & Xinyu Zhou, 2022. "Research on the Mechanism of Government–Industry–University–Institute Collaborative Innovation in Green Technology Based on Game–Based Cellular Automata," IJERPH, MDPI, vol. 19(5), pages 1-25, March.
    11. Kevin Riehl & Florian Kiesel & Dirk Schiereck, 2022. "Political and Socioeconomic Factors That Determine the Financial Outcome of Successful Green Innovation," Sustainability, MDPI, vol. 14(6), pages 1-23, March.
    12. Riehl, Kevin & Kiesel, Florian & Schiereck, Dirk, 2022. "Political and Socioeconomic Factors That Determine the Financial Outcome of Successful Green Innovation," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 132099, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    13. Liyuan Zhang & Xiang Ma & Young-Seok Ock & Lingli Qing, 2022. "Research on Regional Differences and Influencing Factors of Chinese Industrial Green Technology Innovation Efficiency Based on Dagum Gini Coefficient Decomposition," Land, MDPI, vol. 11(1), pages 1-20, January.
    14. Han Han & Huimin Li & Kaize Zhang, 2019. "Spatial-Temporal Coupling Analysis of the Coordination between Urbanization and Water Ecosystem in the Yangtze River Economic Belt," IJERPH, MDPI, vol. 16(19), pages 1-18, October.
    15. Franz Tödtling & Michaela Trippl & Alexandra Frangenheim, 2019. "Policy options for green regional development: applying a production and application perspective," PEGIS geo-disc-2019_16, Institute for Economic Geography and GIScience, Department of Socioeconomics, Vienna University of Economics and Business.
    16. María-Jesús Gutiérrez-Pedrero & María J. Ruiz-Fuensanta & Miguel-Ángel Tarancón, 2020. "Regional Factors Driving the Deployment of Wind Energy in Spain," Energies, MDPI, vol. 13(14), pages 1-13, July.
    17. Maria Clara da Cunha Bezerra & Cláudia Fabiana Gohr & Sandra Naomi Morioka, 2021. "Linking Cluster Characteristics and Organizational Capabilities for Sustainability—Framework Development and Application," Sustainability, MDPI, vol. 13(3), pages 1-26, January.
    18. Chie Hoon Song, 2021. "Exploring and Predicting the Knowledge Development in the Field of Energy Storage: Evidence from the Emerging Startup Landscape," Energies, MDPI, vol. 14(18), pages 1-20, September.
    19. Chenggang Li & Jun Wan & Zhenci Xu & Tao Lin, 2021. "Impacts of Green Innovation, Institutional Constraints and Their Interactions on High-Quality Economic Development across China," Sustainability, MDPI, vol. 13(9), pages 1-19, May.
    20. Aaldering, Lukas Jan & Song, Chie Hoon, 2021. "Of leaders and laggards - Towards digitalization of the process industries," Technovation, Elsevier, vol. 105(C).

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    More about this item

    Keywords

    L52; L86; M13; O52; Green-technology; Green clusters; Green policies; Network analysis; CrunchBase;
    All these keywords.

    JEL classification:

    • L52 - Industrial Organization - - Regulation and Industrial Policy - - - Industrial Policy; Sectoral Planning Methods
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
    • M13 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - New Firms; Startups
    • O52 - Economic Development, Innovation, Technological Change, and Growth - - Economywide Country Studies - - - Europe

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