IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i13p8000-d852641.html
   My bibliography  Save this article

Research on Green Innovation Performance of Manufacturing Industry and Its Improvement Path in China

Author

Listed:
  • Haochang Yang

    (School of Economic and Management, Nanchang University, Nanchang 330047, China)

  • Xuan Zhu

    (School of Economic and Management, Nanchang University, Nanchang 330047, China)

Abstract

Green innovation, which combines “innovation-driven” and “green development,” is one of the most powerful ways to overcome resource and environmental constraints and enhance manufacturing industry sustainability. Based on the innovation value chain perspective, the green innovation process of manufacturing industry is decomposed into two stages: green scientific and technological R&D and achievement transformation. Then, using the three-stage DEA and Malmquist index model to measure the green innovation performance of China’s manufacturing industry, and compare its regional heterogeneity from the dual perspectives of static efficiency and dynamic productivity. In addition, this paper further discusses the improvement path of green innovation performance of China’s manufacturing industry. The findings are as follows: (1) The green innovation efficiency of manufacturing industry in China is at a comparatively low degree and has great potential for improvement. Moreover, it shows apparent regional heterogeneity: The green innovation efficiency in the eastern region is higher than that in the western region, and both are higher than that in the center region, confirming the phenomenon of “central collapse”. (2) The green innovation productivity of China’s manufacturing industry shows a “W-type” dynamic evolution tendency, with green technological progress as the key driving factor, while the green technical efficiency does not clearly exhibit a “catch-up effect”. Additionally, it shows significant regional heterogeneity: green innovation productivity in the western region is higher than that in the central and eastern regions, indicating a potential “backwardness advantage”. (3) The eastern region of China is located in combination IV, which indicates that it has a high rate of green innovation efficiency but a low rate of green innovation productivity; the central region is located in combination III, which indicates that it has a low rate of both green innovation efficiency and productivity; and the western region is located in combination II, which indicates that it has a low rate of green innovation efficiency but a high rate of green innovation productivity. Last but not least, this paper puts forward three kinds of paths for the improvement of the green innovation performance of China’s manufacturing industry: unilateral breakthrough, step-by-step and stimulating jumping type.

Suggested Citation

  • Haochang Yang & Xuan Zhu, 2022. "Research on Green Innovation Performance of Manufacturing Industry and Its Improvement Path in China," Sustainability, MDPI, vol. 14(13), pages 1-21, June.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:13:p:8000-:d:852641
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/13/8000/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/13/8000/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jie Wu & Dacheng Huang & Zhixiang Zhou & Qingyuan Zhu, 2020. "The regional green growth and sustainable development of China in the presence of sustainable resources recovered from pollutions," Annals of Operations Research, Springer, vol. 290(1), pages 27-45, July.
    2. Li, Ke & Lin, Boqiang, 2016. "Impact of energy conservation policies on the green productivity in China’s manufacturing sector: Evidence from a three-stage DEA model," Applied Energy, Elsevier, vol. 168(C), pages 351-363.
    3. Zhijun Feng & Wei Chen, 2018. "Environmental Regulation, Green Innovation, and Industrial Green Development: An Empirical Analysis Based on the Spatial Durbin Model," Sustainability, MDPI, vol. 10(1), pages 1-22, January.
    4. Christian von Hirschhausen & Astrid Cullmann & Andreas Kappeler, 2006. "Efficiency analysis of German electricity distribution utilities - non-parametric and parametric tests," Applied Economics, Taylor & Francis Journals, vol. 38(21), pages 2553-2566.
    5. Fucai Lu & Wei He & Yang Cheng & Sihua Chen & Liang Ning & Xiaoan Mei, 2015. "Exploring the Upgrading of Chinese Automotive Manufacturing Industry in the Global Value Chain: An Empirical Study Based on Panel Data," Sustainability, MDPI, vol. 7(5), pages 1-23, May.
    6. Xinbao Tian & Jiguang Wang, 2018. "Research on the Disequilibrium Development of Output of Regional Innovation Based on R&D Personnel," Sustainability, MDPI, vol. 10(8), pages 1-14, August.
    7. Zeng, Juying & Škare, Marinko & Lafont, Juan, 2021. "The co-integration identification of green innovation efficiency in Yangtze River Delta region," Journal of Business Research, Elsevier, vol. 134(C), pages 252-262.
    8. Kim, Yeong Jae & Brown, Marilyn, 2019. "Impact of domestic energy-efficiency policies on foreign innovation: The case of lighting technologies," Energy Policy, Elsevier, vol. 128(C), pages 539-552.
    9. Ghisetti, Claudia & Quatraro, Francesco, 2017. "Green Technologies and Environmental Productivity: A Cross-sectoral Analysis of Direct and Indirect Effects in Italian Regions," Ecological Economics, Elsevier, vol. 132(C), pages 1-13.
    10. Wei Chen & Xiufeng Wang & Nan Peng & Xuan Wei & Chaoran Lin, 2020. "Evaluation of the Green Innovation Efficiency of Chinese Industrial Enterprises: Research Based on the Three-Stage Chain Network SBM Model," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-11, November.
    11. Wu, Mingran & Zhao, Min & Wu, Zhaodan, 2019. "Evaluation of development level and economic contribution ratio of science and technology innovation in eastern China," Technology in Society, Elsevier, vol. 59(C).
    12. Sally Gee & Andrew McMeekin, 2011. "Eco-Innovation Systems and Problem Sequences: The Contrasting Cases of US and Brazilian Biofuels," Industry and Innovation, Taylor & Francis Journals, vol. 18(3), pages 301-315.
    13. Yu Pei & Yingming Zhu & Suxia Liu & Menglu Xie, 2021. "Industrial agglomeration and environmental pollution: based on the specialized and diversified agglomeration in the Yangtze River Delta," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(3), pages 4061-4085, March.
    14. Huaide Wen & Jun Dai, 2021. "Green Technological Progress and the Backwardness Advantage of Green Development: Taking the Sustainable Development Strategy of Central and Western China as an Example," Sustainability, MDPI, vol. 13(14), pages 1-17, July.
    15. Miao, Cheng-lin & Duan, Meng-meng & Zuo, Yang & Wu, Xin-yu, 2021. "Spatial heterogeneity and evolution trend of regional green innovation efficiency--an empirical study based on panel data of industrial enterprises in China's provinces," Energy Policy, Elsevier, vol. 156(C).
    16. Liang Chun Lu & Yung-ho Chiu & Shih-Yung Chiu & Tzu-Han Chang, 2022. "Do Forests help environmental development of Cities in China?," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(5), pages 6602-6629, May.
    17. H. Fried & C. Lovell & S. Schmidt & S. Yaisawarng, 2002. "Accounting for Environmental Effects and Statistical Noise in Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 17(1), pages 157-174, January.
    18. Miao, Chenglin & Fang, Debin & Sun, Liyan & Luo, Qiaoling, 2017. "Natural resources utilization efficiency under the influence of green technological innovation," Resources, Conservation & Recycling, Elsevier, vol. 126(C), pages 153-161.
    19. Xiaohua Bao & Larry D. Qiu, 2010. "Do Technical Barriers to Trade Promote or Restrict Trade? Evidence from China," Asia-Pacific Journal of Accounting & Economics, Taylor & Francis Journals, vol. 17(3), pages 253-278.
    20. Lin, Boqiang & Chen, Yu, 2020. "Will land transport infrastructure affect the energy and carbon dioxide emissions performance of China’s manufacturing industry?," Applied Energy, Elsevier, vol. 260(C).
    21. Haochang Yang & Faming Zhang & Yixin He, 2021. "Exploring the effect of producer services and manufacturing industrial co-agglomeration on the ecological environment pollution control in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(11), pages 16119-16144, November.
    22. Baoliu Liu & Zhenqing Sun & Huanhuan Li, 2021. "Can Carbon Trading Policies Promote Regional Green Innovation Efficiency? Empirical Data from Pilot Regions in China," Sustainability, MDPI, vol. 13(5), pages 1-15, March.
    23. Wu, Hang & Chen, Jin & Jiao, Hao, 2016. "Dynamic capabilities as a mediator linking international diversification and innovation performance of firms in an emerging economy," Journal of Business Research, Elsevier, vol. 69(8), pages 2678-2686.
    24. Ying Qu & Ying Yu & Andrea Appolloni & Mengru Li & Yue Liu, 2017. "Measuring Green Growth Efficiency for Chinese Manufacturing Industries," Sustainability, MDPI, vol. 9(4), pages 1-18, April.
    25. Caiming Wang & Jian Li, 2020. "The Evaluation and Promotion Path of Green Innovation Performance in Chinese Pollution-Intensive Industry," Sustainability, MDPI, vol. 12(10), pages 1-22, May.
    26. Yang, Zhenbing & Shao, Shuai & Li, Chengyu & Yang, Lili, 2020. "Alleviating the misallocation of R&D inputs in China's manufacturing sector: From the perspectives of factor-biased technological innovation and substitution elasticity," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    27. Yaru Yang & Desheng Liu & Luxiu Zhang & Yingkai Yin, 2021. "Social Trust and Green Technology Innovation: Evidence from Listed Firms in China," Sustainability, MDPI, vol. 13(9), pages 1-18, April.
    28. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    29. Huang, Junbing & Chen, Xiang, 2020. "Domestic R&D activities, technology absorption ability, and energy intensity in China," Energy Policy, Elsevier, vol. 138(C).
    30. Yang, Haochang & Li, Lianshui & Liu, Yaobin, 2022. "The effect of manufacturing intelligence on green innovation performance in China," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    31. Gao, Kang & Yuan, Yijun, 2021. "The effect of innovation-driven development on pollution reduction: Empirical evidence from a quasi-natural experiment in China," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jiazhen Ren & Apurbo Sarkar & Hong Li & Xiaojing Li, 2022. "Does the Host Country’s Foreign Direct Investment (FDI) Restrictiveness Inhibit the Export Sophistication of the Home Country? Evidence from China’s Manufacturing Data," Sustainability, MDPI, vol. 14(22), pages 1-20, November.
    2. Lin, Shu & Yuan, Ying, 2023. "China's resources curse hypothesis: Evaluating the role of green innovation and green growth," Resources Policy, Elsevier, vol. 80(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xinghua Wang & Shunchen Wu & Xiaojuan Qin & Meixiang La & Haixia Zuo, 2022. "Informal Environment Regulation, Green Technology Innovation and Air Pollution: Quasi-Natural Experiments from Prefectural Cities in China," Sustainability, MDPI, vol. 14(10), pages 1-13, May.
    2. Yin, Lei & Du, Shanxing & Chen, Ge, 2024. "The influence of the bank–firm relationship on enterprises’ technological innovation efficiency: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 89(PA), pages 1583-1600.
    3. Pengyu Ren & Zhaoxia Liu, 2021. "Efficiency Evaluation of China’s Public Sports Services: A Three-Stage DEA Model," IJERPH, MDPI, vol. 18(20), pages 1-12, October.
    4. Hao Zhang & Xin Sun & Kailong Dong & Lianghui Sui & Min Wang & Qiong Hong, 2022. "Green Innovation in Regional Logistics: Level Evaluation and Spatial Analysis," IJERPH, MDPI, vol. 20(1), pages 1-20, December.
    5. Jiaoping Yang & Shujun Wang & Shan Sun & Jianhua Zhu, 2022. "Influence Mechanism of High-Tech Industrial Agglomeration on Green Innovation Performance: Evidence from China," Sustainability, MDPI, vol. 14(6), pages 1-20, March.
    6. Yang, Haochang & Li, Lianshui & Liu, Yaobin, 2022. "The effect of manufacturing intelligence on green innovation performance in China," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    7. Luo, Yusen & Lu, Zhengnan & Wu, Chao, 2023. "Can internet development accelerate the green innovation efficiency convergence: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    8. Li, Hongkuan & He, Haiyan & Shan, Jiefei & Cai, Jingjing, 2019. "Innovation efficiency of semiconductor industry in China: A new framework based on generalized three-stage DEA analysis," Socio-Economic Planning Sciences, Elsevier, vol. 66(C), pages 136-148.
    9. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499, March.
    10. Lingzhang Kong & Jinye Li, 2022. "Digital Economy Development and Green Economic Efficiency: Evidence from Province-Level Empirical Data in China," Sustainability, MDPI, vol. 15(1), pages 1-26, December.
    11. Shanwei Li & Yongchang Wu & Qi Yu & Xueyuan Chen, 2023. "National Agricultural Science and Technology Parks in China: Distribution Characteristics, Innovation Efficiency, and Influencing Factors," Agriculture, MDPI, vol. 13(7), pages 1-26, July.
    12. Juan Tang & Fangming Qin, 2022. "Analyzing the impact of local government competition on green total factor productivity from the factor market distortion perspective: based on the three stage DEA model," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(12), pages 14298-14326, December.
    13. Hongwei Liu & Ronglu Yang & Zhixiang Zhou & Dacheng Huang, 2020. "Regional Green Eco-Efficiency in China: Considering Energy Saving, Pollution Treatment, and External Environmental Heterogeneity," Sustainability, MDPI, vol. 12(17), pages 1-19, August.
    14. Jia Li & Yahong Zheng & Bing Liu & Yanyi Chen & Zhihang Zhong & Chenyu Dong & Chaoqun Wang, 2024. "The Synergistic Relationship between Low-Carbon Development of Road Freight Transport and Its Economic Efficiency—A Case Study of Wuhan, China," Sustainability, MDPI, vol. 16(7), pages 1-21, March.
    15. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    16. Xueyang Wang & Xiumei Sun & Haotian Zhang & Chaokai Xue, 2022. "Digital Economy Development and Urban Green Innovation CA-Pability: Based on Panel Data of 274 Prefecture-Level Cities in China," Sustainability, MDPI, vol. 14(5), pages 1-21, March.
    17. Jean Pierre Huiban & Camille Mastromarco & Antonio Musolesi & Michel Simioni, 2016. "The impact of pollution abatement investments on production technology: new insights from frontier analysis," Working Papers hal-01512154, HAL.
    18. Shang, Hua & Jiang, Li & Pan, Xianyou & Pan, Xiongfeng, 2022. "Green technology innovation spillover effect and urban eco-efficiency convergence: Evidence from Chinese cities," Energy Economics, Elsevier, vol. 114(C).
    19. Biao Hu & Kai Yuan & Tingyun Niu & Liang Zhang & Yuqiong Guan, 2022. "Study on the Spatial and Temporal Evolution Patterns of Green Innovation Efficiency and Driving Factors in Three Major Urban Agglomerations in China—Based on the Perspective of Economic Geography," Sustainability, MDPI, vol. 14(15), pages 1-28, July.
    20. Qi, Xiulin & Wu, Zhifang & Xu, Jinqing & Shan, Biaoan, 2023. "Environmental justice and green innovation: A quasi-natural experiment based on the establishment of environmental courts in China," Ecological Economics, Elsevier, vol. 205(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:13:p:8000-:d:852641. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.