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Nestedness Maximization in Complex Networks through the Fitness-Complexity Algorithm
Open AccessArticle

Green Technology Fitness

1
Department of Economics and Finance, University of Rome Tor Vergata, 00133 Rome, Italy
2
INGENIO (CSIC-Universitat Politecnica de Valencia), 46022 Valencia, Spain
3
Institute for Complex Systems, National Research Council, 00185 Rome, Italy
4
Department of Economics and Management, University of Ferrara, 44121 Ferrara, Italy
*
Author to whom correspondence should be addressed.
Entropy 2018, 20(10), 776; https://doi.org/10.3390/e20100776
Received: 31 July 2018 / Revised: 27 September 2018 / Accepted: 8 October 2018 / Published: 10 October 2018
(This article belongs to the Special Issue Economic Fitness and Complexity)
The present study provides an analysis of empirical regularities in the development of green technology. We use patent data to examine inventions that can be traced to the environment-related catalogue (ENV-Tech) covering technologies in environmental management, water-related adaptation and climate change mitigation. Furthermore, we employ the Economic Fitness-Complexity (EFC) approach to assess their development and geographical distribution across countries between 1970 and 2010. This allows us to identify three typologies of countries: leaders, laggards and catch-up. While, as expected, there is a direct relationship between GDP per capita and invention capacity, we also document the remarkable growth of East Asia countries that started from the periphery and rapidly established themselves as key actors. This geographical pattern coincides with higher integration across domains so that, while the relative development of individual areas may have peaked, there is now demand for greater interoperability across green technologies. View Full-Text
Keywords: green technology; fitness; capabilities; economic development green technology; fitness; capabilities; economic development
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Sbardella, A.; Perruchas, F.; Napolitano, L.; Barbieri, N.; Consoli, D. Green Technology Fitness. Entropy 2018, 20, 776.

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