TY - JOUR

T1 - A spatial perspective on green technology adoption in China

T2 - insights from patent licensing data

AU - Losacker, Sebastian

AU - Horbach, Jens

AU - Liefner, Ingo

N1 - Funding Information: Previous versions of this article were presented at the 6th Global Conference on Economic Geography in Dublin (June 2022), at the 6th Geography of Innovation Conference in Milan (July 2022), at the YSI Workshop on the Geography of Innovation in Milan (July 2022) and at the REENEA Workshop in Oldenburg (September 2022). The authors have benefited greatly from feedback received from the participants of these events. In addition, we appreciate the reference to the source of licensing data by researchers at the School of Urban & Regional Science, East China Normal University in Shanghai during a research visit in September 2019. Thanks go to Charlotte Lobensteiner, Boshu Li and Clara-Marie Mühlberger for their excellent research assistance. We would also like to thank Yuefang Si for providing data on Chinese universities. Finally, we would like to thank two anonymous reviewers and the handling editor for a constructive review process. We acknowledge financial support by the German Research Foundation (DFG) and by the German Federal Ministry of Education and Research (BMBF).

PY - 2023/7/7

Y1 - 2023/7/7

N2 - In the transition to more sustainable regional economies, the widespread adoption of green technologies is crucial. However, little is known about the geography of green technology adoption and the relationship between regional demand and supply of green technologies. In this paper, we shed light on the (regional) factors explaining whether innovation adopters use green technologies that have been developed locally or green technologies that have been developed in other places. We analyze a unique data set of 8825 licensing agreements for Chinese patents in green technologies, which we use as an indicator to measure innovation diffusion. Our results suggest that the regional context plays a key role in predicting whether innovation adopters use local or non-local green technologies. We show, among other things, that the use of locally developed green technologies is more likely in regions characterized by green technology specializations and high innovation capacity than in less innovative regions.

AB - In the transition to more sustainable regional economies, the widespread adoption of green technologies is crucial. However, little is known about the geography of green technology adoption and the relationship between regional demand and supply of green technologies. In this paper, we shed light on the (regional) factors explaining whether innovation adopters use green technologies that have been developed locally or green technologies that have been developed in other places. We analyze a unique data set of 8825 licensing agreements for Chinese patents in green technologies, which we use as an indicator to measure innovation diffusion. Our results suggest that the regional context plays a key role in predicting whether innovation adopters use local or non-local green technologies. We show, among other things, that the use of locally developed green technologies is more likely in regions characterized by green technology specializations and high innovation capacity than in less innovative regions.

KW - China

KW - environmental innovation

KW - green technology

KW - Innovation diffusion

KW - patent licensing

UR - http://www.scopus.com/inward/record.url?scp=85164613604&partnerID=8YFLogxK

U2 - 10.1080/2157930X.2023.2233199

DO - 10.1080/2157930X.2023.2233199

M3 - Article

AN - SCOPUS:85164613604

JO - Innovation and Development

JF - Innovation and Development

SN - 2157-930X

ER -