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Exploring the spatial pattern of renewable energy technology innovation: evidence from China

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Abstract

Considering the obvious regional differences in China, research on the drivers for renewable energy technology innovation (RETI) needs to fully consider the spatial factors. Based on the expanded function of knowledge production, which includes the human capital, institutional quality, and industrial scale, and using panel data from 29 provinces during 2006–2017, this study examines the factors promoting RETI by employing spatial regression methods. The results show that RETI presents moderate spatial agglomeration and spatial heterogeneity. Human capital, enterprise R&D intensity, and research institution R&D intensity have a significant driving effect on the local RETI, and the university R&D intensity, institutional quality, and industrial scale have no significant contribution. Human capital is the most important factor driving the local RETI, and enterprise R&D intensity has the strongest spatial spillover effect on the RETI of the surrounding provinces. In addition, the R&D intensity of enterprises and research institutions can enhance the local RETI and also significantly promote RETI in surrounding provinces through the spatial spillover effect. In contrast, human capital has played a significant driving role in the local RETI, whereas its spatial spillover effect on the surrounding provinces is not obvious. Therefore, the direct and spatial spillover effects of enterprise R&D intensity and research institution R&D intensity should be fully considered in policy making. In addition, effective policies should be formulated to break the block division of human capital investment and to promote the optimized allocation of talented people in order to better promote RETI in China.

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Data availability

The datasets used or analyzed during this study are available from the corresponding author on reasonable request.

Notes

  1. By 2018, China’s main renewable energy sources, including hydropower, wind, and solar power, have been ranked the first worldwide in aspects of new and cumulative installed capacity. In China’s total energy consumption, the proportion of renewable energy has been continually increasing, and the energy structure adjustment continues to accelerate. In 2018, the generating installed capacity of renewable energy represented 38.4% of the aggregate installed capacity, the generated capacity represented 26.7% in the aggregate generated capacity, and the share of the primary energy consumption increased to 12.4%. China's clean and low-carbon green energy system has taken shape.

  2. Global Renewable Energy Investment Trends in 2019.

  3. www.people.cn. China has invested more than 3 billion yuan in renewable energy technology R&D. http://env.people.com.cn/n1/2019/1225/c1010-31521520.html.

  4. The marketization indicator is defined from five aspects: the game between the government and market, the development and perfection of the product and factor market, the development and status of the non-public economy in the market, the establishment and development of market intermediary organizations, and the laws environment. There are 18 basic indexes used, and they are constructed with principal component analysis as the basic econometric method. In order to ensure objectivity, the calculation of the basic indexes is based on the statistical data of authoritative institutions or the survey data of enterprises and does not depend on subjective factors such as the “expert score.” It is a useful economic analysis tool and is used to analyze the relative relationship between the institutional reform processes in various regions.

  5. This was developed by the World Intellectual Property Organization (WIPO).

  6. According to Freund et al. (2006), it is considered to be acceptable when \(0 < VIF < 10\); it means there is multicollinearity when \(10 \leq VIF < 100\); and it means there is strong multicollinearity when \(VIF \geq 100\).

  7. LeSage and Pace (2009) suggested that we consider the spatial Durbin model in this situation.

  8. http://news.bjx.com.cn/html/20180607/904085.shtml.

Abbreviations

RETI:

Renewable energy technology innovation

R&D:

Research and development

IURC:

Industry-university-research cooperation

FYP:

Five-year-plan

SDM:

Spatial Durbin model

OLS:

Ordinary least squares

IPC:

The International Patent Classification

WIPO:

The World Intellectual Property Organization

REL:

Renewable Energy Law

GDP:

Gross domestic product

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Funding

This study is funded by The National Natural Science Foundation of China, Grant/Award Numbers: 71974083, 71904067; the Humanities and Social Science Fund of the Ministry of Education of China, Grant/Award Number: 19YJA790024; the Jiangsu Social Science Fund, Grant/Award Number: 18EYB014; the Jiangsu Provincial Department of Education, Grant/Award Number: 2018SJZDI089; and the Research Support Project for Doctoral Degree Teachers of Jiangsu Normal University of China, Grant/Award Number: 18XWRS017.

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Authors and Affiliations

  1. School of Economics, Hangzhou Normal University, Hangzhou, 311121, China

    Zhengxia He

  2. Business School, Jiangsu Normal University, Xuzhou, 221116, China

    Leyi Kuai & Wenbo Li

  3. Business School, University of Shanghai for Science & Technology, Shanghai, 200093, China

    Xin Chen

  4. College of Economics and Management, Nanjing Forestry University, Nanjing, 210037, China

    Wenxing Shen

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  1. Zhengxia He
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Contributions

Zheng-Xia He: conceptualization, data curation, writing—original draft preparation. Leyi Kuai: visualization, investigation. Xin Chen: methodology, software, supervision. Wen-Xing Shen: software, validation. Wenbo Li: Writing—reviewing and editing.

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He, Z., Kuai, L., Chen, X. et al. Exploring the spatial pattern of renewable energy technology innovation: evidence from China. Environ Sci Pollut Res 29, 59076–59093 (2022). https://doi.org/10.1007/s11356-022-19841-4

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