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The Leaders of the Twin Transition in Asia: Mapping Capabilities through Digital and Green Patents Seoul Center for finanCe and innovation Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized© 2023 International Bank for Reconstruction and Development / The World Bank 1818 H Street NW Washington DC 20433 Telephone: 202-473-1000 Internet: www.worldbank.org This work is a product of the staff of The World Bank with external contributions. The find- ings, interpretations, and conclusions expressed in this work do not necessarily reflect the views of The World Bank, its Board of Executive Directors, or the governments they represent. 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Any queries on rights and licenses, including subsidiary rights, should be addressed to World Bank Publications, The World Bank Group, 1818 H Street NW, Washington, DC 20433, USA; fax: 202-522- 2625; e-mail: pubrights@worldbank.org.The Leaders of the Twin Transition in Asia: Mapping Capabilities through Digital and Green Patents Seoul Center for finanCe and innovation june 2023 World Bank Group Finance, Competitiveness and Innovation Global PracticeAcknowledgment This report was prepared by a team led by Anwar Aridi (Senior Private Sector Specialist, World Bank’s Finance Competitiveness and Innovation Global Practice), which included Pierre-Alexandre Balland (Utrecht University China, Japan and Republic of Korea score highest in the Twin Transition, while Macao SAR, Mongolia, Cambodia and Democratic People’s Republic of Korea score lowest. — The paper identifies 4 types of cities in terms of their patent intensity in Twin Transition tech- nologies: twin leader, green leader, digital leader, and follower. A large majority of Asian cities are followers, and only a limited number of cities are green or digital leaders only, without being a leader in both. Twin leaders are found in China (7 cities), Japan (8 cities) and Republic of Korea (10 cities). Cities in the catching-up economies in East Asia like Malaysia, Thailand, Vietnam and the Philippines belong to the category of followers. It is important to note that by focusing on patent data this report focuses on technology creation rather than adoption. The geography of the Twin Transition technology adoption in Asia might look different. — Econometric models are run to assess the effect of Relatedness Density on the growth of Twin Transition technologies in cities. The result shows that digital capabilities play an important role in the development of both digital and green technologies. Green capabilities are positive- ly related to the development of new green technologies, but do not seem to be strongly linked to the development of digital technologies. — The principle of relatedness is used to identify the cities with the strongest potential to lead the race in Twin Transition technologies. For each digital and green technology, a Relatedness Density map of cities in East and South East Asia is presented. These maps represent the tech- nological Relatedness Density around a Twin Transition technology in each city, indicating the matching of the technology to other technologies in which the city is specialized. For all of the 27 Relatedness Density maps (one for each technology), the higher the potential of a city in a technology, as shown by the Relatedness Density measure, the more specialized the city is in that technology. The maps indicate that the potential to develop digital technologies is more spatially concentrated in East and Southeast Asia than in the case of green technologies. For example, Japanese cities tend to show high potential to develop new battery technology (as well as other green technologies), with four of the top five cities. By contrast, Japanese cities have little presence in digital technologies, where China is dominant— Chinese cities take up seven of the top ten places for the Internet of Things and artificial intelligence. The Leaders of The Twin TransiTion in asia: Mapping CapabiLiTies Through digiT aL and green p a TenTs 7 — A complementarity indicator (Added Relatedness Density) is used to identify potential partner cities that can provide complementary capabilities to a city to develop a green or digital tech- nology. For each technology and city, the top-5 cities are identified that can provide the highest amount of complementary capabilities that the city itself is missing and that are relevant for the city to grow into the Twin Transition technology. The cities with the greatest complementa- ry capabilities in each technology differs by the city absorbing these technologies, although in some cases there is a considerable overlap of the most relevant partners. And for many cities, the cities with the greatest complementary capabilities are located in other countries. This work underlines the importance of cities promoting Twin Transition technologies in which they have high potential. Local capabilities condition which particular transitions can be sup- ported effectively by policy. This implies that cities should refrain from developing Twin Transition technologies in which they have no relevant capabilities (Balland et al. 2019). Cities have different capabilities, and therefore ‘one-size-fits-all’ policies should be avoided. For the catching-up economies that are lagging behind the Twin Transition, policy can be designed to help cities connect with other regions to get access to relevant capabilities. The complementar- ity indicator (Added Relatedness Density) can be used to identify cities that could provide com- plementary capabilities to develop a green or digital technology. In terms of prioritizing the focus areas, the empirical analysis shows that building capabilities in digital has a higher potential to grow into both digital and green technologies. Therefore, connecting with cities that have high re- latedness in the digital space can be more desirable in the short run. Government can aim to facil- itate university-industry linkages and establish new collaborations with other cities, institutions, and universities. The mobility of entrepreneurs and workers to other cities can also help firms and cities accumulate absorptive capacity and skillsets required for the Twin Transition technology. To some extent, attracting external firms such as multinational enterprises (MNEs) and skilled migrants to the region may also help. 8 The Leaders of The Twin TransiTion in asia: Mapping CapabiLiTies Through digiT aL and green p a TenTs01 Introduction The Leaders of The Twin TransiTion in asia: Mapping CapabiLiTies Through digiT aL and green p a TenTs 9Recently many economies and regions have demonstrated strong interest in participating in the Twin Transition (TWI2050 2019; Balogun et al. 2020; Truby 2020; Amoroso et al. 2021; Papadavid 2021; European Commission 2022b). The term ‘Twin Transition’ refers to digital and green transformations, as well as the uniting of the two transitions, which could accelerate nec- essary changes (Muench et al. 2022). Successful green and digital transitions will affect the lives of all citizens, help tackle climate change, and reshape our society. Developing capabilities and technology sovereignty in digital and green technologies also is considered to be crucial to remain competitive in the 21st century, to create jobs, build resilient societies, and meet ambitious sus- tainability goals. Unlocking the potential of synergies between the Twin Transitions and mitigating possible negative effects requires a deep understanding of how the two transitions can mutually reinforce each other, and how to mitigate possible tensions between the two. Despite the rising importance of the Twin Transitions, there is little understanding of which economies and cities have the potential to develop the requisite technologies and the inter- play between the digital and green technologies. In academic research, the focus has been either on the digital or the green transition, and there is little research on their interplay, and findings are mixed. There is concern that some digital technologies have such pervasive envi- ronmental footprints that they might impede achieving the policy targets of the green transition (Vinuesa et al. 2020; Del Rio Castro et al. 2021). Lange et al. (2020) and Jones (2018) conclude that digitalization tends to increase energy consumption. Diemer et al. (2022) focus on the envi- ronmental pollution resulting from the extraction of critical materials used in the digital transition. However, other studies suggest that digital technologies contribute positively to the environment (e.g. Rolnick et al. 2019; Del Rio Castro et al. 2021). Cicerone et al. (2022) find a positive effect of AI as an enabler for regions to develop green technologies. In a recent study on European regions, Bianchini et al. (2022) find that local green technologies reduce greenhouse emissions, especially in regions well-endowed with digital technologies. According to this study, digital technologies (in particular big data and computing infrastructures) have a negative impact on the environment, but this detrimental effect on greenhouse emissions is weakened in regions that are strong in green technologies. The objective of this report is to identify the cities leading the Twin Transition or with a strong potential to lead in the coming years, and the cities that other cities should connect to in order to develop green and digital technologies. 128 cities in 6 East Asian economies (China, Japan, Mongolia, Democratic Peoples Republic of Korea, Republic of Korea, and Taiwan) and 11 01 Introduction 10 The Leaders of The Twin TransiTion in asia: Mapping CapabiLiTies Through digiT aL and green p a TenTs