IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i4p1573-d1338255.html
   My bibliography  Save this article

Does Technological Innovation Efficiency Improve the Growth of New Energy Enterprises? Evidence from Listed Companies in China

Author

Listed:
  • Junhua Chen

    (Sichuan Oil and Natural Gas Development Research Center, School of Economics and Management, Southwest Petroleum University, Chengdu 610500, China)

  • Qiaochu Li

    (Sichuan Oil and Natural Gas Development Research Center, School of Economics and Management, Southwest Petroleum University, Chengdu 610500, China)

  • Peng Zhang

    (School of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu 610500, China)

  • Xinyi Wang

    (Sichuan Oil and Natural Gas Development Research Center, School of Economics and Management, Southwest Petroleum University, Chengdu 610500, China)

Abstract

With the implementation of “carbon peaking and carbon neutrality” in China, new energy enterprises, as the vanguard in this strategy, have entered a new era of innovation-driven development. However, enterprises at different lifecycle stages will face different internal and external conditions, and there are differences in their internal mechanisms and business performance. In this case, whether technological innovation efficiency can have an obviously positive effect on their growth and what different effects it can have for enterprises at different lifecycle stages have become issues of great concern to company management, investors, governments, and other stakeholders. This research takes 81 new Chinese energy enterprises as the research objects. First, they are divided into growing, mature, and declining enterprises based on the cash flow combination method. Then, their technological innovation efficiencies from 2016 to 2021 are calculated based on the stochastic frontier method and their growth evaluations are performed by taking both financial and non-financial indicators into consideration. Finally, by taking mediating effects into consideration, the heterogeneity effects of technological innovation efficiency on their growth are studied from the perspective of enterprise lifecycles based on the fixed-effect model. The research results indicate that the technological innovation efficiency of new Chinese energy enterprises has fluctuated around 0.90 in recent years, and is generally at a high level. The efficiency ranking of enterprises at different lifecycle stages is mature period > growing period > declining period. Technological innovation efficiency has a positive impact on their growth, and market share plays a mediating role in this process. The effects of technological innovation efficiency on enterprises at different stages are different, with growing and mature enterprises showing a positive impact. Growing enterprises are more affected by technological innovation efficiency due to their demand for innovation-driven development, while declining enterprises often face difficulties such as unstable operating conditions and outdated equipment, and unreasonable technological innovations may actually accelerate their decline.

Suggested Citation

  • Junhua Chen & Qiaochu Li & Peng Zhang & Xinyi Wang, 2024. "Does Technological Innovation Efficiency Improve the Growth of New Energy Enterprises? Evidence from Listed Companies in China," Sustainability, MDPI, vol. 16(4), pages 1-28, February.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:4:p:1573-:d:1338255
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/4/1573/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/4/1573/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Changhong Chen & Huijie Zhang, 2023. "Evaluation of Green Development Level of Mianyang Agriculture, Based on the Entropy Weight Method," Sustainability, MDPI, vol. 15(9), pages 1-22, May.
    2. Gabriele Pellegrino & Mariacristina Piva, 2020. "Innovation, industry and firm age: are there new knowledge production functions?," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 10(1), pages 65-95, March.
    3. Siran Fang & Xiaoshan Xue & Ge Yin & Hong Fang & Jialin Li & Yongnian Zhang, 2020. "Evaluation and Improvement of Technological Innovation Efficiency of New Energy Vehicle Enterprises in China Based on DEA-Tobit Model," Sustainability, MDPI, vol. 12(18), pages 1-22, September.
    4. Miaomiao Li & Zhaoxing Hao & Meng Luan & Haibo Li & Guikun Cao, 2021. "The Impact of Innovation Investment Volatility on Technological Innovation of Enterprises in Different Life Cycles," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-12, December.
    5. Fangyu Gu & Yu Xie, 2022. "The differential impacts of coercive pressure from environmental law and proactive environmental strategy on corporate environmental performance: The case study of a pulp and paper company," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 29(5), pages 1909-1925, September.
    6. Wang, Zhongcheng & Li, Xinyue & Xue, Xinhong & Liu, Yahuan, 2022. "More government subsidies, more green innovation? The evidence from Chinese new energy vehicle enterprises," Renewable Energy, Elsevier, vol. 197(C), pages 11-21.
    7. Maochun Zhou & Rui Fan, 2023. "The Impact of Green Capital Structure on Enterprise Development and the Regulation of Technological Innovation under Carbon Peaking," Sustainability, MDPI, vol. 15(7), pages 1-19, March.
    8. Yuanyuan Chen & JungHyun Song, 2023. "The Technological Innovation Efficiency of China’s Renewable Energy Enterprises: An Estimation Based on a Three-Stage DEA Model," Sustainability, MDPI, vol. 15(8), pages 1-18, April.
    9. Yongquan Guo & Hua Zou & Zhu Liu, 2021. "Behavioral Analysis of Subjects for Green Technology Innovation: A Tripartite Evolutionary Game Model," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-14, September.
    10. Hongxing Deng & Wen Wen & Jie Zhou, 2023. "Competitiveness Evaluation of Express Delivery Enterprises Based on the Information Entropy and Gray Correlation Analysis," Sustainability, MDPI, vol. 15(16), pages 1-11, August.
    11. Nicolette Matthews & Beatrice Conradie & Jenifer Piesse, 2023. "Technological differences in South African sheep production: a stochastic meta-frontier analysis," Agrekon, Taylor & Francis Journals, vol. 62(1), pages 19-30, January.
    12. 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.
    13. Shuchen Niu & Xiang Luo & Tiantian Yang & Guodong Lin & Chongming Li, 2023. "Does the Low-Carbon City Pilot Policy Improve the Urban Land Green Use Efficiency?—Investigation Based on Multi-Period Difference-in-Differences Model," IJERPH, MDPI, vol. 20(3), pages 1-21, February.
    14. Yaghoub Abdi & Xiaoni Li & Xavier Càmara-Turull, 2022. "Exploring the impact of sustainability (ESG) disclosure on firm value and financial performance (FP) in airline industry: the moderating role of size and age," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(4), pages 5052-5079, April.
    15. Barnabé Walheer, 2022. "Global Malmquist and cost Malmquist indexes for group comparison," Journal of Productivity Analysis, Springer, vol. 58(1), pages 75-93, August.
    16. Kaoru Tone & Miki Tsutsui, 2010. "An epsilon-based measure of efficiency in DEA revisited -A third pole of technical efficiency," GRIPS Discussion Papers 09-21, National Graduate Institute for Policy Studies.
    17. Khanyisa Mabasa & Opeoluwa Akinradewo & Clinton Aigbavboa & Olusegun Oguntona, 2023. "Contributions of Construction Small, Medium, and Micro Enterprises towards the Sustainable Growth of Zambia," Sustainability, MDPI, vol. 15(10), pages 1-14, May.
    18. Homma, Tetsushi & Tsutsui, Yoshiro & Uchida, Hirofumi, 2014. "Firm growth and efficiency in the banking industry: A new test of the efficient structure hypothesis," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 143-153.
    19. SooGeun Ahn & Jeewhan Yoon & YoungJun Kim, 2018. "The innovation activities of small and medium-sized enterprises and their growth: quantile regression analysis and structural equation modeling," The Journal of Technology Transfer, Springer, vol. 43(2), pages 316-342, April.
    20. Karpagam Subramanian & Shauhrat S. Chopra & Weslynne S. Ashton, 2021. "Capital‐based life cycle sustainability assessment: Evaluation of potential industrial symbiosis synergies," Journal of Industrial Ecology, Yale University, vol. 25(5), pages 1161-1176, October.
    21. Molinari, Massimo, 2013. "Joint analysis of the non-linear debt–growth nexus and cash-flow sensitivity: New evidence from Italy," Structural Change and Economic Dynamics, Elsevier, vol. 24(C), pages 34-44.
    22. Liang Li & Hajar Msaad & Huaping Sun & Mei Xuen Tan & Yeqing Lu & Antonio K.W. Lau, 2020. "Green Innovation and Business Sustainability: New Evidence from Energy Intensive Industry in China," IJERPH, MDPI, vol. 17(21), pages 1-18, October.
    23. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    24. Ali M. Oumer & Amin Mugera & Michael Burton & Atakelty Hailu, 2022. "Technical efficiency and firm heterogeneity in stochastic frontier models: application to smallholder maize farms in Ethiopia," Journal of Productivity Analysis, Springer, vol. 57(2), pages 213-241, April.
    Full references (including those not matched with items on IDEAS)

    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. Feng Dong & Chang Qin & Xiaoyun Zhang & Xu Zhao & Yuling Pan & Yujin Gao & Jiao Zhu & Yangfan Li, 2021. "Towards Carbon Neutrality: The Impact of Renewable Energy Development on Carbon Emission Efficiency," IJERPH, MDPI, vol. 18(24), pages 1-23, December.
    2. Franz R. Hahn, 2007. "Determinants of Bank Efficiency in Europe. Assessing Bank Performance Across Markets," WIFO Studies, WIFO, number 31499, April.
    3. Chen, Yufeng & Ni, Liangfu & Liu, Kelong, 2021. "Does China's new energy vehicle industry innovate efficiently? A three-stage dynamic network slacks-based measure approach," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    4. 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.
    5. Gómez-Calvet, Roberto & Conesa, David & Gómez-Calvet, Ana Rosa & Tortosa-Ausina, Emili, 2014. "Energy efficiency in the European Union: What can be learned from the joint application of directional distance functions and slacks-based measures?," Applied Energy, Elsevier, vol. 132(C), pages 137-154.
    6. Tingting Wu & Junjun Chen & Chengchun Shi & Guidi Yang, 2023. "Carbon Emission Efficiency and Reduction Potential Based on Three-Stage Slacks-Based Measure with Data Envelopment Analysis and Malmquist at the City Scale in Fujian Province, China," Sustainability, MDPI, vol. 15(16), pages 1-15, August.
    7. Avkiran, Necmi K., 2006. "Developing foreign bank efficiency models for DEA grounded in finance theory," Socio-Economic Planning Sciences, Elsevier, vol. 40(4), pages 275-296, December.
    8. Avkiran, Necmi K. & Rowlands, Terry, 2008. "How to better identify the true managerial performance: State of the art using DEA," Omega, Elsevier, vol. 36(2), pages 317-324, April.
    9. 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.
    10. Yu, Ming-Miin, 2010. "Assessment of airport performance using the SBM-NDEA model," Omega, Elsevier, vol. 38(6), pages 440-452, December.
    11. Weixin Yang & Lingguang Li, 2017. "Energy Efficiency, Ownership Structure, and Sustainable Development: Evidence from China," Sustainability, MDPI, vol. 9(6), pages 1-26, June.
    12. Guangdi Zhang & Yaojun Ye & Mengya Sun, 2023. "Assessing the Static and Dynamic Efficiency of Digital Economy in China: Three Stage DEA–Malmquist Index Based Approach," Sustainability, MDPI, vol. 15(6), pages 1-17, March.
    13. Kozo Harimaya & Kei Tomimura & Nobuyoshi Yamori, 2015. "Efficiencies of Small Financial Cooperatives in Japan: Comparison of Estimation Methods," Discussion Paper Series DP2015-04, Research Institute for Economics & Business Administration, Kobe University.
    14. Ze Tian & Fang-Rong Ren & Qin-Wen Xiao & Yung-Ho Chiu & Tai-Yu Lin, 2019. "Cross-Regional Comparative Study on Carbon Emission Efficiency of China’s Yangtze River Economic Belt Based on the Meta-Frontier," IJERPH, MDPI, vol. 16(4), pages 1-19, February.
    15. Wu, Tai-Hsi & Chen, Ming-Shiun & Yeh, Jin-Yii, 2010. "Measuring the performance of police forces in Taiwan using data envelopment analysis," Evaluation and Program Planning, Elsevier, vol. 33(3), pages 246-254, August.
    16. Chen, Junlin & Zhang, Ying & Wang, Wenqing & Yang, Can & Li, Jiayue & Wu, Yulun, 2022. "The efficiency of consumption poverty alleviation and improvement measures in Guizhou, China," Energy, Elsevier, vol. 248(C).
    17. Xiang Liu & Jia Liu, 2016. "Measurement of Low Carbon Economy Efficiency with a Three-Stage Data Envelopment Analysis: A Comparison of the Largest Twenty CO 2 Emitting Countries," IJERPH, MDPI, vol. 13(11), pages 1-14, November.
    18. Avkiran, Necmi K., 2007. "Stability and integrity tests in data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 41(3), pages 224-234, September.
    19. 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.
    20. Zhou, Anhua & Li, Jun, 2021. "Investigate the impact of market reforms on the improvement of manufacturing energy efficiency under China’s provincial-level data," Energy, Elsevier, vol. 228(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:16:y:2024:i:4:p:1573-:d:1338255. 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.