IDEAS home Printed from https://ideas.repec.org/a/sae/sagope/v12y2022i2p21582440221105478.html
   My bibliography  Save this article

Threshold Effect of Industry Heterogeneity on Green Innovation Efficiency: Evidence From China

Author

Listed:
  • Congjia Huo
  • Lingming Chen
  • Peipei Dong

Abstract

We scientifically evaluate the efficiency of green innovation in the industry, analyze its changes and development, and study the impact of industry heterogeneity on it. Which will help us grasp the efficiency of green innovation at the industry level, also provides a scientific basis for formulating relevant environmental regulations. Based on industry heterogeneity and green innovation efficiency, this first analyzes industry panel data from 2005 to 2014 in China for 35 industries. It then uses the entropy weight method to calculate the industry heterogeneity and green innovation efficiency of the industry in China. Then, environmental regulations are taken as threshold variables to empirically analyze the correlation between industry heterogeneity and green innovation efficiency. The study found a significant twofold threshold effect that links industry heterogeneity and green innovation efficiency, showing an “inverted N-type†result. Industry heterogeneity negatively impacts green innovation efficiency when the environmental regulation strength is at a higher interval rank and a lower level. However, industry heterogeneity negatively affects the intermediate level of green innovation efficiency.

Suggested Citation

  • Congjia Huo & Lingming Chen & Peipei Dong, 2022. "Threshold Effect of Industry Heterogeneity on Green Innovation Efficiency: Evidence From China," SAGE Open, , vol. 12(2), pages 21582440221, June.
  • Handle: RePEc:sae:sagope:v:12:y:2022:i:2:p:21582440221105478
    DOI: 10.1177/21582440221105478
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/21582440221105478
    Download Restriction: no

    File URL: https://libkey.io/10.1177/21582440221105478?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Edmund Merem & Bennetta Robinson & Joan M. Wesley & Sudha Yerramilli & Yaw A. Twumasi, 2010. "Using GIS in Ecological Management: Green Assessment of the Impacts of Petroleum Activities in the State of Texas," IJERPH, MDPI, vol. 7(5), pages 1-30, May.
    2. Han Jia & Andrea Appolloni & Yunqi Wang, 2017. "Green Travel: Exploring the Characteristics and Behavior Transformation of Urban Residents in China," Sustainability, MDPI, vol. 9(6), pages 1-14, June.
    3. Hansen, Bruce E., 1999. "Threshold effects in non-dynamic panels: Estimation, testing, and inference," Journal of Econometrics, Elsevier, vol. 93(2), pages 345-368, December.
    4. Lingming Chen & Wenzhong Ye & Congjia Huo & Kieran James, 2020. "Environmental Regulations, the Industrial Structure, and High-Quality Regional Economic Development: Evidence from China," Land, MDPI, vol. 9(12), pages 1-22, December.
    5. Nasierowski, W. & Arcelus, F. J., 2003. "On the efficiency of national innovation systems," Socio-Economic Planning Sciences, Elsevier, vol. 37(3), pages 215-234, September.
    6. 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.
    7. 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.
    8. Ebru Alpay & Joe Kerkvliet & Steven Buccola, 2002. "Productivity Growth and Environmental Regulation in Mexican and U.S. Food Manufacturing," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(4), pages 887-901.
    9. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    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. Tianjun Xu & Gangmin Weng & Wei Guo & Yidan Cao, 2023. "Spatio-Temporal Differentiation of Regional Innovation Chain: Evidence From Beijing-Tianjin-Hebei Region," SAGE Open, , vol. 13(4), pages 21582440231, December.
    2. Tian, Jinfang & Sun, Siyang & Cao, Wei & Bu, Di & Xue, Rui, 2024. "Make every dollar count: The impact of green credit regulation on corporate green investment efficiency," Energy Economics, Elsevier, vol. 130(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. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499.
    2. 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 1-22, March.
    3. Yanli Ji & Jie Xue & Kaiyang Zhong, 2022. "Does Environmental Regulation Promote Industrial Green Technology Progress? Empirical Evidence from China with a Heterogeneity Analysis," IJERPH, MDPI, vol. 19(1), pages 1-23, January.
    4. Yang, Shang-Ho & Burdine, Kenneth H. & Hu, Wu-Yueh, 2016. "An Alternative Approach to Estimate the Economic Loss of Porcine Epidemic Diarrhea (PED) via Data Envelopment Analysis: The Case in Taiwan," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235574, Agricultural and Applied Economics Association.
    5. Huaide Wen & Jun Dai, 2021. "The Change of Sources of Growth and Sustainable Development in China: Based on the Extended EKC Explanation," Sustainability, MDPI, vol. 13(5), pages 1-19, March.
    6. 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.
    7. Huayong Niu & Zhishuo Zhang & Yao Xiao & Manting Luo & Yumeng Chen, 2022. "A Study of Carbon Emission Efficiency in Chinese Provinces Based on a Three-Stage SBM-Undesirable Model and an LSTM Model," IJERPH, MDPI, vol. 19(9), pages 1-19, April.
    8. Brown, Rayna, 2006. "Mismanagement or mismeasurement? Pitfalls and protocols for DEA studies in the financial services sector," European Journal of Operational Research, Elsevier, vol. 174(2), pages 1100-1116, October.
    9. Tan, Xiujie & Xiao, Ziwei & Liu, Yishuang & Taghizadeh-Hesary, Farhad & Wang, Banban & Dong, Hanmin, 2022. "The effect of green credit policy on energy efficiency: Evidence from China," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    10. Tavana, Madjid & Ebrahimnejad, Ali & Santos-Arteaga, Francisco J. & Mansourzadeh, Seyed Mehdi & Matin, Reza Kazemi, 2018. "A hybrid DEA-MOLP model for public school assessment and closure decision in the City of Philadelphia," Socio-Economic Planning Sciences, Elsevier, vol. 61(C), pages 70-89.
    11. Nusrate Aziz & Belayet Hossain & Laura Lamb, 2022. "Does green policy pay dividends?," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 24(2), pages 147-172, April.
    12. Avkiran, Necmi K., 2007. "Stability and integrity tests in data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 41(3), pages 224-234, September.
    13. Carla Henriques & Clara Viseu, 2022. "Are ERDFs Devoted to Boosting ICTs in SMEs Inefficient? A Three-Stage SBM Approach," Sustainability, MDPI, vol. 14(17), pages 1-20, August.
    14. Ibrahim Alnafrah, 2021. "Efficiency evaluation of BRICS’s national innovation systems based on bias-corrected network data envelopment analysis," Journal of Innovation and Entrepreneurship, Springer, vol. 10(1), pages 1-28, December.
    15. Vitor Miguel Ribeiro & Celeste Varum & Ana Dias Daniel, 2021. "Introducing microeconomic foundation in data envelopment analysis: effects of the ex ante regulation principle on regional performance," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 12(3), pages 1215-1244, September.
    16. Wang, Zhaohua & Li, Yi & Wang, Ke & Huang, Zhimin, 2017. "Environment-adjusted operational performance evaluation of solar photovoltaic power plants: A three stage efficiency analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 1153-1162.
    17. Beniamina Margari & Fabrizio Erbetta & Carmelo Petraglia & Massimiliano Piacenza, 2007. "Regulatory and environmental effects on public transit efficiency: a mixed DEA-SFA approach," Journal of Regulatory Economics, Springer, vol. 32(2), pages 131-151, October.
    18. Cordero Ferrera, Jose Manuel & Alonso Morán, Edurne & Nuño Solís, Roberto & Orueta, Juan F. & Souto Arce, Regina, 2013. "Efficiency assessment of primary care providers: A conditional nonparametric approach," MPRA Paper 51926, University Library of Munich, Germany.
    19. Meng Ye & Yanan Jin & Fumin Deng, 2022. "Municipal waste treatment efficiency in 29 OECD countries using three-stage Bootstrap-DEA model," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(9), pages 11369-11391, September.
    20. Liwen Sun & Ying Han, 2022. "Spatial Correlation Network Structure and Influencing Factors of Two-Stage Green Innovation Efficiency: Evidence from China," Sustainability, MDPI, vol. 14(18), pages 1-22, September.

    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:sae:sagope:v:12:y:2022:i:2:p:21582440221105478. 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: SAGE Publications (email available below). General contact details of provider: .

    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.