AccScience Publishing / IJOCTA / Online First / DOI: 10.36922/IJOCTA025160080
RESEARCH ARTICLE

Green innovation efficiency measurement and its influencing factors in specialized and new enterprises

Mengxue Li1 Ruiyan Gao1 Yaguai Yu1,2* Xiyi Li3 Qizhe Mao4
Show Less
1 Business School, Ningbo University, Ningbo, Zhejiang, China
2 Donghai Academy, Ningbo University, Ningbo, Zhejiang, China
3 Yangming School, Ningbo University, Ningbo, Zhejiang, China
4 State Tobacco Monopoly Administration, Zhoushan, Zhejiang, China
Received: 16 April 2025 | Revised: 17 July 2025 | Accepted: 24 July 2025 | Published online: 26 August 2025
© 2025 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Abstract

Based on data from 40 Specialized and New Enterprises (SNEs) in Zhejiang from 2017 to 2021, green innovation efficiency (GIE) is assessed by Charnes–Cooper–Rhodes and super-Slack-Based Measure models, and influencing factors of GIE are analyzed using the Systematic Generalized Method of Moments Dynamic model to address the improvement of GIE in SNEs. The conclusions include: (i) the GIE is declining from 2017 to 2021 and could be improved in the future, especially for SNEs in Zhejiang. (ii) As for influencing factors, research and development investment, industry-university-research collaboration, and government support have positive effects, while enterprise scale has a negative effect of restraining the development of green innovation of SNEs in Zhejiang. Therefore, several countermeasures, including establishing sound scientific research mechanisms, forming cooperation mechanisms among enterprises, research institutes, and colleges and universities, strengthening government support, and improving the government’s subsidy policy, are being put forward. Scientific basis and practical guidance are provided to enhance the green innovation capability of enterprises and the formulation of relevant policies by the government.

Keywords
Specialized and new enterprises
Green innovation efficiency
Charnes–Cooper–Rhodes and super-Slack-Based Measure models
Measurement
Influencing factors
Funding
This work was supported by 2025 Ningbo Social Science Project “Multiplier Effect of Data Elements Enabling New Quality Productivity: Current Status and Possible Paths in Ningbo (G2025-3-01),” 2025 Ningbo University SRIP project “Multiplier Effect of Data Elements Enabling New Quality Productivity: Logical Mechanisms and Paths to Realization (2025SRIP0112),” 2024 Zhejiang Province Social Science Think Tank Project “Research on the Value Assessment of ocean data assets to Empower the High Quality Development of Zhejiang’s Ocean Economy,” Zhejiang Province Social Science 2023 “Social Science Empowerment Action” Special Project “Research Results of Social Science Empowerment of High Quality Development Action in Mountain (Island) Counties” named “Research on the Mechanism and Integration Path of Digital Economy Empowering the High Quality Development of Zhejiang’s Mountain Economy,” 2023 Ningbo Municipal Industry-Education Integration “Five Batch” Project “Construction of Generative Artificial Intelligence-Based Intelligent Education in Colleges and Universities,” and 2024 Ningbo SoftScience Research Program “Domestic and International Practices of Attracting Social Funds to Invest in Basic Research and Implications for the City (2024R017).”
Conflict of interest
The authors declare they have no competing interests.
References
  1. Energy   Statistical  Review  of World  Energy  2024.  United Kingdom: Energy  Institute;   2024.  Available at: https://www.bp.com/statisticalreview.

 

  1. He Y, Wang YH. Research hot spots and evolutionary trends of green development at home and abroad—a visualization analysis based on CiteSpace. Henan Soc Sci. 2024;32(12):55-66.

 

  1. Li JC, Lian GH, Xu AT. An empirical study of digitization-driven greening as a breakthrough for corporate green transformation under the version of “dual-carbon.” Quant Tech Econ Res. 2023;40(9):27-49. http://dx.doi.org/10.13653/j.cnki.jqte.20230725.009

 

  1. Li QY, Xiao ZH. Heterogeneous environmental regulatory tools and corporate green innovation incentives—evidence from green patents of listed firms. Econ Res. 2020;55(9):192-208.

 

  1. Wang SH, Guo D. Research on the impact of the coupled coordination of digitalization and greening on high-quality innovation of specialized and new enterprises. Res Manag. 2025:1-17.

 

  1. Ernest B, David W. Regulation as a means for the social control of technology. Technol Anal Strateg Manag. 1994;6(3):259-272. http://dx.doi.org/10.1080/09537329408524171

 

  1. Lee KH, Min B. Green R&D for eco-innovation and its impact on carbon emissions and firm performance. J Clean Prod. 2015;108(Pt A):534-542. http://dx.doi.org/10.1016/j.jclepro.2015.05.114

 

  1. Wang FZ, Chen FY. Board governance, environmental regulation and green technology innovation—empirical test based on listed companies in heavy polluting industries in China. Sci Res. 2018;36(2):361-369. http://dx.doi.org/10.16192/j.cnki.1003- 2018.02.019

 

  1. Tao F, Zhao JY, Zhou H. Does environmental regulation achieve “incremental quality improvement” of green technology innovation—evidence from the environmental protection target responsibility system. China’s Ind Econ. 2021;(2):136- 154. http://dx.doi.org/10.19581/j.cnki.ciejournal.2021.02.016

 

  1. Brunnermeier SB, Cohen MA. Determinants of environmental innovation in US manufacturing industries. J Environ Econ Manag. 2003;45(2):278-293. http://dx.doi.org/10.1016/S0095-0696(02)00058-X

 

  1. Zhang G, Zhang XJ. Driven factors of enterprise green innovation strategy: a multi-case comparative study. J Zhejiang Univ (Humanit Soc Sci). 2014;44(1):113-124.

 

  1. Zhang X, Wang Y. Effects of environmental regulation and R&D investment on green technology innovation. Sci Technol Prog Countermeasures. 2017;34(17):9. http://dx.doi.org/10.6049/kjjbydc.2017010494

 

  1. Wang H, Feng Z, Yuan L, Lin WF. Green R&D intervention by public research institutions and green innovation of enterprises—based on the perspective of environmental externalities. China Ind Econ. 2024;(9):81-99. http://dx.doi.org/10.19581/j.cnki.ciejournal.2024.09.005

 

  1. Zhang JX, Zhu L. Research on technological innovation efficiency of industrial enterprises in various regions of China based on green growth. Quant Tech Econ Res. 2012;29(2):113-125. http://dx.doi.org/10.13653/j.cnki.jqte.2012.02.008

 

  1. Qian L, Xiao RQ, Chen ZW. Research on green technology innovation efficiency and regional differences of industrial enterprises in China—based on metafrontier theory and DEA model. Econ Theory Econ Manag. 2015;(1):18. http://dx.doi.org/10.3969/j.issn.1000-596X.2015.01.004

 

  1. Chung YH, Fare R, Grosskopf S. Productivity and undesirable outputs: a directional distance function approach. J Environ Manage. 1997;51(3):229-240. http://dx.doi.org/10.1006/jema.1997.0146

 

  1. Fare R, Grosskopf S, Pasurka J. Accounting for air pollution emissions in measures of state manufacturing productivity growth. J Reg Sci. 2001;41(3):381-409. http://dx.doi.org/10.1111/0022-4146.00223

 

  1. Tone K. A slacks-based measure of efficiency in data envelopment analysis. Eur J Oper Res. 2001;130(3):498-509. http://dx.doi.org/10.1016/S0377-2217(99)00407-5

 

  1. Peng XS. The mechanism and path of green economy promoting innovative development. Econ Vertical Horizontal. 2017;(9):56-61. http://dx.doi.org/10.16528/j.cnki.22-1054/f.201709056

 

  1. Zhang H. Research on the green innovation up- grading path of state-owned manufacturing enter- prises from the perspective of high-quality development—taking Chenming Paper Industry as an example. J Jinan Univ (Soc Sci). 2020;30(4):12.

 

  1. Fu ZK, He WB. Measurement and improvement of innovation efficiency of “specialized, special and new” enterprises—based on the three-stage DEA model. North Finance. 2022;(6):60-65. http://dx.doi.org/10.16459/j.cnki.15-1370/f.2022.06.021

 

  1. Yu YG, Yan YN, Shen PY, Li YT, Ni TH. Green financing efficiency and influencing factors of Chinese listed construction companies against the background of carbon neutralization: a study based on three-stage DEA and system GMM. Axioms. 2022;11(9):467. http://dx.doi.org/10.3390/axioms11090467

 

  1. Yu YG, Shen PY, Yan YN, Ni TH, Chen FY. Construction enterprises’ green financing efficiency and its influencing factors including in- ternal and external—based on four-stage DEA model. PLoS One. 2023;18(6):e0286043. http://dx.doi.org/10.1371/journal.pone.0286043

 

  1. Slater J, Angel T. The impact and implications of environmentally linked strategies on competitive advantage: a study of Malaysian companies. J Bus Res. 2000;47(1):75-89. http://dx.doi.org/10.1016/S0148-2963(98)00053-8

 

  1. Gong JJ, Wang FR, Wang CB. The status and role of government in green technology innovation of SMEs. China Popul Resour Environ. 2002;(1):114-117.

 

  1. Zhou HJ, Bi KX, Xu MK. Approaches to sustainable development of technological innovation in small and medium-sized enterprises. Technol Manag. 2006;(2):130-132. http://dx.doi.org/10.16315/j.stm.2006.02.040

 

  1. Li MP, Xiang G, Gao ZS, Fu Q. A preliminary study on the institutional conditions for the transformation of environmental benefits of green innovation in China’s manufacturing industry to economic benefits of enterprises. Res Manag. 2005;(2):46-49. http://dx.doi.org/10.19571/j.cnki.1000-2995.2005.02.007

 

  1. Horbach J. Determinants of environmental innovation—new evidence from German panel data sources. Res Policy. 2008;37(1):163-173. http://dx.doi.org/10.1016/j.respol.2007.08.006

 

  1. Yu YG, Li YT, Ni TH, Gao C. The impact of internet finance on green technology innovation in manufacturing companies—mediating role based on financing constraint. Front Environ Sci. 2023;11:1122318. http://dx.doi.org/10.3389/fenvs.2023.1122318

 

  1. Li JS, Ke W. How knowledge search and re- configuration promote green technology innovation in specialized small and medium-sized enterprises—the moderating role of strategic flexibility and incentive-based environmental regulation. Sci Technol Prog Countermeasures. 2024;41(7):111- 121.

 

  1. Ling SX, Ji MJ. Enterprise digitalization and green technology innovation in manufacturing. Bus Res. 2023;(4):10-18. http://dx.doi.org/10.13902/j.cnki.syyj.2023.04.007

 

  1. Zhang F, Liu JY. Digital inputs, green technology innovation and green upgrading of exports—experience from China’s manufacturing sector. Explor Econ Issues. 2023;(9):131-145.

 

  1. Li TS. Basic characteristics and cultivation mechanism of small and medium-sized enterprises of specialized, specialized and new—taking Shanghai as an example. Econ Spec Econ Zone. 2012;(7):67-69.

 

  1. Li PE. Small and medium-sized enterprises must take the road of “specialized” development. Chem Manag. 2011;(5):15-16.

 

  1. Liu C, Mei Q. Research on the growth path selection of “specialized, refined, distinctive, and innovative” micro enterprises. Sci Technol Manag Res. 2015;35(5):126-130.

 

  1. Sun WD, Wu ZC. The positive effect of the strategy of “specialization and innovation” on the development of small, medium and micro enter- prises—an example from Changzhou. Jiangnan Forum. 2019;(7):10-12.

 

  1. Hao LF. Research on the Efficiency of Industry Innovation in the Adjustment of Economic Structure in Shanxi—Analysis Bbased on DEA and SFA Methods. Shanxi University; 2011.

 

  1. Ministry of Industry and Information Technology of the People’s Republic of China. Notice No. 300; 2011.

 

  1. Yan PD, Zhang F. Research on the efficiency and spatial characteristics of industrial green innovation in Shandong Peninsula Urban Agglomeration under the constraint of undesirable output. Sci Manag. 2021;41(3):32-41.

 

  1. Charnes A, Cooper WW, Rhodes E. Measuring the efficiency of decision making units. Eur J Oper Res. 1978;2(6):429-444. http://dx.doi.org/10.1016/0377-2217(78)90138-8

 

  1. Tu LL, Huang D. Application of interpolation method in data correction. Math Theory Appl. 2012;32(3):7.

 

  1. Wu YB. China’s industrial R&D output elasticity calculation (1993-2002). Econ Q. 2008;(3):869- 890.

 

  1. Wang H, Wang SQ, Miao Z, Li XC. The heterogeneous threshold effect of R&D investment on green innovation efficiency—based on empirical research on China’s high-tech industry. Res Manag. 2016;37(2):63-71.

 

  1. Qu GJ, Song L, Guo YJ. Research on technological innovation efficiency of listed companies in China—based on the three-stage DEA method. Macroecon Res. 2018;(6):97-106.

 

  1. Yu ZM. Environmental interviews, government environmental subsidies and corporate green innovation. Foreign Econ Manag. 2021;43(7):22-37.

 

  1. Wu SC, Qu D, Guo Y, Dong JC. Ownership concentration, managerial ownership and enterprise green technology innovation. Financ Res. 2023;(6):80-89.

 

  1. Guo XL. Research on the impact of corporate asset-liability ratio on corporate innovation. University of International Business and Economics;

 

  1. Liu WQ. The impact of R&D investment on green innovation efficiency of high-tech industries under the perspective of industrial agglomeration. Jiangxi Soc Sci. 2019;39(11):65-75.

 

  1. Liu MG. Research on the impact of environmental regulation, government science and technology funding on corporate green innovation. Econ Forum. 2019;(7):21-29.
Share
Back to top
An International Journal of Optimization and Control: Theories & Applications, Electronic ISSN: 2146-5703 Print ISSN: 2146-0957, Published by AccScience Publishing