城市气候政策不确定性对企业绿色创新的影响效应研究

杜扬, 钟美瑞, 徐骏

科研管理 ›› 2026, Vol. 47 ›› Issue (10) : 106-117.

PDF(1393 KB)
PDF(1393 KB)
科研管理 ›› 2026, Vol. 47 ›› Issue (10) : 106-117. DOI: 10.19571/j.cnki.1000-2995.2026.10.011  CSTR: 32148.14.kygl.2026.10.011

城市气候政策不确定性对企业绿色创新的影响效应研究

作者信息 +

Research on the impact mechanism of urban climate policy uncertainty on enterprise green innovation

Author information +
文章历史 +

摘要

中国气候政策独特的不确定性表现,引导着企业绿色创新的深度转变。以实物期权理论为主导,结合时间异质视角与组织行为分析,本文系统构建了城市气候政策不确定性(CCPU)影响绿色管理创新(GMI)和绿色技术创新持续性(GTIS)的分析框架。基于2010—2023年中国上市企业数据,运用随机森林回归器和固定效应模型联合检验了CCPU对GMI与GTIS的非线性影响效应。主要结论包括:(1)特征重要性分析与Boruta算法表明,CCPU是影响企业GMI和GTIS的重要因素;(2)部分依赖图结果显示,CCPU对二者的影响曲线分别呈现为“倒U形”与“正U形”;(3)进一步分析发现,企业战略激进度升高将强化CCPU对GMI和GTIS的影响,企业内部薪酬差距扩大则会削弱这一影响,企业拥有专精特新身份后,CCPU对其GMI和GTIS的影响更加显著。研究从行为视角搭建了绿色创新和决策理论的对话桥梁,拓展了绿色创新外部驱动的因素分析,为国家气候政策制定和企业绿色创新贡献了重要认识。

Abstract

The unique uncertainties embodied in China's climate policies are guiding a profound transformation in firms' green innovation. Drawing on real options theory and incorporating a temporal heterogeneity perspective together with organizational behavior analysis, this study systematically constructs an analytical framework for how city-level climate policy uncertainty (CCPU) influences green managerial innovation (GMI) and the persistence of green technological innovation (GTIS). Using data from Chinese listed firms from 2010 to 2023, we employ a random forest regressor and a fixed-effects model to jointly test the nonlinear impact of CCPU on GMI and GTIS. The main findings are as follows:(1) Feature importance analysis and the Boruta algorithm indicate that CCPU is a key factor affecting firms' GMI and GTIS. (2) Partial dependence plots reveal that the effect of CCPU on GMI follows an inverted U-shape, whereas its effect on GTIS exhibits a U-shaped pattern. (3) Further analysis shows that greater strategic aggressiveness amplifies the impact of CCPU on both GMI and GTIS; a larger pay gap within the firm weakens this impact; and for firms designated as "specialized, refined, distinctive and innovative" (SRDI), the marginal effect of CCPU on GMI and GTIS becomes more pronounced. This study builds a dialogue bridge between green innovation and decision-making theories from a behavioral perspective, extends the analysis of external drivers of green innovation, and will provide important insights for national climate policymaking and corporate green innovation.

关键词

城市气候政策不确定性(CCPU) / 企业绿色创新 / 非线性关系 / 随机森林 / 固定效应

Key words

city-level climate policy uncertainty (CCPU) / enterprise green innovation / nonlinear relationship / random forest / fixed effects

引用本文

导出引用
杜扬, 钟美瑞, 徐骏. 城市气候政策不确定性对企业绿色创新的影响效应研究[J]. 科研管理. 2026, 47(10): 106-117 https://doi.org/10.19571/j.cnki.1000-2995.2026.10.011
Du Yang, Zhong Meirui, Xu Jun. Research on the impact mechanism of urban climate policy uncertainty on enterprise green innovation[J]. Science Research Management. 2026, 47(10): 106-117 https://doi.org/10.19571/j.cnki.1000-2995.2026.10.011
中图分类号: F273.1;F49   

参考文献

[1]
EPRS.COP27 climate change conference:Outcomes[EB/OL].(2024-10-01) [2025-05-01] https://www.europarl.europa.eu/RegData/etudes/ATAG/2022/739230/EPRS-AaG-739230-COP27-outcomes-FINAL.pdf.
[2]
Liu Q, Xu C, Liu T. Asymmetric spillovers of climate policy uncertainty on financial markets:Evidence from China[J]. The North American Journal of Economics and Finance, 2025:102513.
[3]
UNDP. Issue brief:China's climate policy documents - 1+N and updated NDC[EB/OL].(2024-10-11) [2025-04-03]. https://www.undp.org/china/publications/issue-brief-chinas-climate-policy-documents-1n-and-updated-ndc.
[4]
Liu P, Peng H. What drives the green and low-carbon energy transition in China? An empirical analysis based on a novel framework[J]. Energy, 2022, 239:122450.
[5]
Li J, Zhang X, Ali S, et al. Eco-innovation and energy productivity:New determinants of renewable energy consumption[J]. Journal of Environmental Management, 2020, 271:111028.
[6]
Chen M, Sinha A, Hu K, et al. Impact of technological innovation on energy efficiency in industry 4.0 era:Moderation of shadow economy in sustainable development[J]. Technological Forecasting and Social Change, 2021, 164:120521.
[7]
Hu Y, Bai W, Farrukh M, et al. How does environmental policy uncertainty influence corporate green investments?[J]. Technological Forecasting and Social Change, 2023, 189:122330.
[8]
Liu J, Zhao M, Wang Y. Impacts of government subsidies and environmental regulations on green process innovation:A nonlinear approach[J]. Technology in Society, 2020, 63:101417.
[9]
Borozan D, Pirgaip B. Climate policy uncertainty and firm-level carbon dioxide emissions:Assessing the impact in the U.S. market[J]. Business Strategy and the Environment, 2024, 33:5920-5938.
[10]
Kong Q, Li R, Wang Z, et al. Economic policy uncertainty and firm investment decisions:Dilemma or opportunity?[J]. International Review of Financial Analysis, 2022, 83:102301.
[11]
Schiederig T, Tietze F, Herstatt C. Green innovation in technology and innovation management:An exploratory literature review[J]. R&D Management, 2012, 42(2):180-192.
[12]
Karimi Takalo S, Sayyadi Tooranloo H, Shahabaldini parizi Z. Green innovation:A systematic literature review[J]. Journal of Cleaner Production, 2021, 279:122474.
[13]
Tan Y, Zhu Z. The effect of ESG rating events on corporate green innovation in China:The mediating role of financial constraints and managers' environmental awareness[J]. Technology in Society, 2022, 68:101906.
[14]
Yang H, Li L, Liu Y. The effect of manufacturing intelligence on green innovation performance in China[J]. Technological Forecasting and Social Change, 2022, 178:121569.
[15]
Sukumar A, Jafari-Sadeghi V, Garcia-Perez A, et al. The potential link between corporate innovations and corporate competitiveness:Evidence from IT firms in the UK[J]. Journal of Knowledge Management, 2020, 24(5):965-983.
[16]
Merton R C. Theory of rational option pricing[J]. The Bell Journal of Economics and Management Science, 1973, 4(1):141-183.
[17]
Ghani U, Zhu B, Qin Q, et al. Forecasting US stock market volatility:Evidence from ESG and CPU indices[J]. Finance Research Letters, 2024, 59:104811.
[18]
Sarkar S, Osiyevskyy O. Organizational change and rigidity during crisis:A review of the paradox[J]. European Management Journal, 2018, 36(1):47-58.
[19]
王慧, 孙慧, 肖涵月, 等. “谨小慎微”抑或“险中求胜”?:环境政策不确定性与污染密集型企业绿色创新[J]. 产业经济研究, 2021(2):30-41+127.
Wang Hui, Sun Hui, Xiao Hanyue, et al. "Be cautious" or "Win in danger"? Environmental policy uncertainty and green innovation of pollution-intensive enterprises[J]. Industrial Economics Research, 2021(2):30-41+127.
[20]
何郁冰, 张思. 技术创新持续性对企业绩效的影响研究[J]. 科研管理, 2017, 38(9):1-11.
He Yubing, Zhang Si. A research on the effect of technological innovation persistence on firm performance[J]. Science Research Management, 2017, 38(9):1-11.
[21]
Zhao X, Zhao Y, Zeng S, et al. Corporate behavior and competitiveness:Impact of environmental regulation on Chinese firms[J]. Journal of Cleaner Production, 2015, 86:311-322.
[22]
李维安, 张耀伟, 郑敏娜, 等. 中国上市公司绿色治理及其评价研究[J]. 管理世界, 2019, 35(5):126-133+160.
Li Weian, Zhang Yaowei, Zheng Minna, et al. Research on green governance of Chinese listed companies and its evaluation[J]. Journal of Management World, 2019, 35(5):126-133+160.
[23]
姚星, 陈灵杉, 张永忠. 碳交易机制与企业绿色创新:基于三重差分模型[J]. 科研管理, 2022, 43(6):43-52.
Yao Xing, Chen Lingshan, Zhang Yongzhong. The carbon trading mechanism and corporate green innovation in China:A study based on the DDD model[J]. Science Research Management, 2022, 43(6):43-52.
[24]
Triguero Á, Córcoles D. Understanding innovation:An analysis of persistence for Spanish manufacturing firms[J]. Research Policy, 2013, 42(2):340-352.
[25]
Ma Y R, Liu Z, Ma D, et al. A news-based climate policy uncertainty index for China[J]. Scientific Data, 2023, 10:881.
Climate policies can have a significant impact on the economy. However, these policies have often been associated with uncertainty. Quantitative assessment of the socioeconomic impact of climate policy uncertainty is equally or perhaps more important than looking at the policies themselves. Using a deep learning algorithm—the MacBERT model—this study constructed indices of Chinese climate policy uncertainty (CCPU) at the national, provincial and city levels for the first time. The CCPU indices are based on the text mining of news published by a set of major newspapers in China. A clear upward trend was found in the indices, demonstrating increasing policy uncertainties in China in addressing climate change. There is also evidence of clear regional heterogeneity in subnational indices. The CCPU dataset can provide a useful source of information for government actors, academics and investors in understanding the dynamics of climate policies in China. These indices can also be used to investigate the empirical relationship between climate policy uncertainty and other socioeconomic factors in China.
[26]
方帅, 程雨涵, 刘知, 等. 企业“一把手”和“二把手”的价值观差异与企业创新:基于机器学习的经验证据[J]. 中国软科学, 2024(S1):203-222.
Fang Shuai, Cheng Yuhan, Liu Zhi, et al. Chairman and CEO value differences and firm innovation:Empirical evidence from a machine learning approach[J]. China Soft Science, 2024(S1):203-222.
[27]
王墨林, 阎海峰, 宋渊洋. 企业数字化程度对战略激进度的影响研究[J]. 管理学报, 2023, 20(5):667-675.
摘要
基于2008~2020年上市企业样本,使用Python对企业年报进行文本挖掘,构建企业数字化程度指数,分析企业数字化程度对战略激进度的影响机理。研究表明:①企业数字化程度对战略激进度有显著的正向影响。②企业数字化程度对战略激进度的影响强度与所有权性质、内部控制质量和冗余资源有关,即企业数字化程度对战略激进度的影响在民营企业比在国有企业更强,在内部控制质量高和冗余资源多的企业更强;进一步比较上述变量调节作用的强度,发现冗余资源的调节强度明显高于企业所有权性质和内部控制质量。③战略激进度在企业数字化程度促进企业成长的过程中起到中介作用。
Wang Molin, Yan Haifeng, Song Yuanyang. Research on the influence of firm digitization on strategic aggressiveness[J]. Chinese Journal of Management, 2023, 20(5):667-675.
Based on the data of listed firms from 2008 to 2020, this study uses Python to mine the keywords of the annual report, constructs the firm-level digitization degree index, and empirically tests the relationship between the firm digitization and the strategic aggressiveness. The results show that, firstly, the higher the degree of digitalization of the firm, the more aggressiveness its strategy is; secondly, the degree of digitization has a stronger positive impact on the strategic aggressiveness for the firm with private ownership, high internal control quality, and abundant redundant resources, and the moderating effects of redundant resources are significantly stronger than the other two; finally, the degree of digitization significantly promotes the growth of the firm, and the above relationship is mediated by strategic aggressiveness.
[28]
张多蕾, 许少山, 薛菲, 等. 战略激进度与企业社会责任履行:基于资源获取的视角[J]. 中国软科学, 2022(6):111-123.
Zhang Duolei, Xu Shaoshan, Xue Fei, et al. Corporate strategy and social responsibility performance:Based on the perspective of resource acquisition[J]. China Soft Science, 2022(6):111-123.
[29]
Tsang A, Wang K T, Liu S, et al. Integrating corporate social responsibility criteria into executive compensation and firm innovation:International evidence[J]. Journal of Corporate Finance, 2021, 70:102070.
[30]
Amore M D, Failla V. Pay dispersion and executive behaviour:evidence from innovation[J]. British Journal of Management, 2020, 31(3):487-504.
[31]
孔东民, 徐茗丽, 孔高文. 企业内部薪酬差距与创新[J]. 经济研究, 2017, 52(10):144-157.
Kong Dongmin, Xu Mingli, Kong Gaowen. Pay gap and firm innovation in China[J]. Economic Research Journal, 2017, 52(10):144-157.
[32]
曹虹剑, 张帅, 欧阳峣, 等. 创新政策与“专精特新”中小企业创新质量[J]. 中国工业经济, 2022(11):135-154.
Cao Hongjian, Zhang Shuai, Ouyang Yao, et al. Innovation policy and the innovation quality of specialized and sophisticated SMEs that produce novel and unique products[J]. China Industrial Economics, 2022(11):135-154.

基金

国家自然科学基金专项(重点项目):“数据资源统计监测与市场价值评估的理论与方法研究”(72442028,2025—2027)
国家自然科学基金面上项目:“数据要素化与数字技术对绿色低碳发展的影响:理论机制、作用路径与政策优化”(72373165,2024—2027)
湖南省教育厅科学研究重点项目:“数据要素与数字技术驱动绿色低碳转型的理论机制与路径研究”(23A0006,2024—2026)

PDF(1393 KB)

Accesses

Citation

Detail

段落导航
相关文章

/

〈 〉