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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 1-27, February.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:4:p:1573-:d:1338255
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    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. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. Tone, Kaoru & Tsutsui, Miki, 2010. "An epsilon-based measure of efficiency in DEA - A third pole of technical efficiency," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1554-1563, December.
    9. 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.
    10. Tone, Kaoru & Toloo, Mehdi & Izadikhah, Mohammad, 2020. "A modified slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 287(2), pages 560-571.
    11. 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.
    12. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    13. 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.
    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. 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.
    16. Barnabé Walheer, 2022. "Global Malmquist and cost Malmquist indexes for group comparison," Journal of Productivity Analysis, Springer, vol. 58(1), pages 75-93, August.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. 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.
    25. 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.
    26. 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.
    27. 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.
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