Wind energy can contribute to national climate, energy and economic goals by expanding clean energy and supporting economies through new manufacturing industries. However, the mechanisms for achieving these interlinked goals are not well understood. Here we analyse the wind energy manufacturing global value chain, using a dataset on 389 component supplier firms (2006–2016) that work with 13 original equipment manufacturers. We assess how technology complexity, that is, the knowledge intensity and difficulty of manufacturing components, shapes the location of suppliers. For countries without existing wind industries, we find evidence of the emergence of suppliers for only low-complexity components (for example, towers and generators). For countries with existing wind industries, we find that suppliers’ evolution, that is, changes in their international supply relationships, is less likely for high-complexity components (for example, blades and gearboxes). Our findings show the importance of understanding technologies along with firms and countries within global value chains for achieving policy goals.
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The database on the global manufacturing value chain developed for this study was built on third-party reports published by Navigant Consulting, with additional details obtained from Orbis, Amadeus, Bloomberg and Derwent World Patents Index. Restrictions apply to the availability of these third-party data and so the dataset is not publicly available. Data are however available upon reasonable request from the corresponding author. Supplier data (without the supplier company name) are available at https://github.com/kavsurana/tech-complexity-project/. The source data underlying Figs. 1–6 are provided as source data. The source data underlying Supplementary Figs. 1 and 2 are provided as Supplementary Data 1 and 2.
The source and code to replicate the analysis are available at https://github.com/kavsurana/tech-complexity-project/.
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Funding for this research was provided by the US National Science Foundation under grant number 1829252; and the UK Economic and Social Research Council under grant number ES/S010688/1. M. George, L. He, A. Hammerstingl and F. Traimer helped with cleaning and verifying the dataset. D. Li and M. Vigil provided valuable feedback on the concepts behind this paper.
The authors declare no competing interests.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Tables 1–6, Figs. 1 and 2, and refs. 1–7.
Source data for Supplementary Fig. 1. Comparison of technology complexity calculated from different approaches.
Source data for Supplementary Fig. 2. Distribution of wind component suppliers by country and the processed dataset to calculate results.
Data on number of suppliers by country and by component, and the base dataset.
Data points for the product complexity index using HS02 values.
Source data on suppliers and the country of the OEM they supply to, the base dataset and the complexity dataset.
Summary of the number of countries and firms for each component, the base dataset and the complexity dataset.
Statistical model results and the processed dataset to calculate results.
Summary of data on maximum complexity in a country, the base dataset and the complexity dataset.
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Surana, K., Doblinger, C., Anadon, L.D. et al. Effects of technology complexity on the emergence and evolution of wind industry manufacturing locations along global value chains. Nat Energy 5, 811–821 (2020). https://doi.org/10.1038/s41560-020-00685-6
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