Technological forecasting & social change does environmental regulation induce green innovation? a panel study of Chinese listed firms

2022 ◽  
Vol 176 ◽  
pp. 121492
Author(s):  
Jingbo Cui ◽  
Jing Dai ◽  
Zhenxuan Wang ◽  
Xiande Zhao
Keyword(s):  
Social Change ◽  
Environmental Regulation ◽  
Panel Study ◽  
Green Innovation ◽  
Listed Firms ◽  
Technological Forecasting

Co-citation, bibliographic coupling and leading authors, institutions and countries in the 50 years of Technological Forecasting and Social Change

2021 ◽  
Vol 165 ◽  
pp. 120487
Author(s):  
Alicia Mas-Tur ◽  
Norat Roig-Tierno ◽  
Shikhar Sarin ◽  
Christophe Haon ◽  
Trina Sego ◽  
...  
Keyword(s):  
Social Change ◽  
Bibliographic Coupling ◽  
Technological Forecasting

Research on green innovation countermeasures of supporting the circular economy to green finance under big data

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Zhao Yaoteng ◽  
Li Xin
Keyword(s):  
Big Data ◽  
Environmental Regulation ◽  
Fixed Time ◽  
Spatial Effect ◽  
Regression Coefficients ◽  
Green Innovation ◽  
Time And Space ◽  
Content Type ◽  
Green Finance ◽  
Lag Model

PurposeThe purpose of this paper is to explore the sustainable development strategy of green finance under the background of big data.Design/methodology/approachFrom the perspective of big data, this paper uses quantitative and qualitative analysis methods to judge the correlation among green finance, environmental supervision and financial supervision. Green finance gives the entropy method to calculate the score of green finance and environmental regulation, and establishes the spatial lag model under the double fixed effects of time and space.FindingsSpatial autocorrelation test shows that economic spatial weight matrix has obvious spatial effect on green innovation. Through the model selection test, the space lag model with fixed time and space is selected. The regression coefficients of green finance, environmental regulation and their interaction are 0.1598, 0.0541 and 0.1763, respectively, which significantly promote green innovation. The regression coefficients of openness, higher education level and per capita GDP are 0.0361, 0.0819 and 0.0686, respectively, which can significantly promote green innovation.Originality/valueIn view of the current situation of large-scale application of big data technology in green innovation of domestic energy-saving and environmental protection enterprises, this paper establishes a fixed time lag evaluation model of green innovation. M-test statistics show that the original hypothesis with no obvious spatial effect is rejected.

scholarly journals Could the Environmental Regulation Promote Green Innovation? Evidence From China

2021 ◽  
Author(s):  
Weiyong Zou ◽  
Yunjun Xiong
Keyword(s):  
Environmental Regulation ◽  
Positive Impact ◽  
Spillover Effect ◽  
Green Innovation ◽  
Coordinated Development ◽  
Innovation Activities ◽  
High Degree ◽  
The Relationship ◽  
D Investment

Abstract Could the environmental regulation promote green innovation? This is a very controversial issue. In view of the fact that the existing literature only studies the relationship between the two, lacks effective heterogeneity research, and pays less attention to the deeper analysis mechanism between the two. This study fills the gap. This paper selects the panel data of 285 prefecture level cities in China from 2000 to 2019 for empirical research. The results show that environmental regulation has a significant and continuous positive impact on green innovation.From the perspective of heterogeneity, we find that cities with higher level of green innovation are suitable to improve the intensity of environmental regulation; Cities with low level of green innovation can not formulate high-intensity environmental regulation policies. The intermediary mechanism shows that under the situation of stricter environmental regulations, producers will pay more attention to the promotion and accumulation of human capital, and provide strong intellectual support for green innovation activities. The adjustment mechanism shows that the cities with high degree of marketization and financial R&D investment are conducive to strengthening the promotion of environmental regulation on green innovation. On the contrary, it weakens the role of environmental regulation in promoting green innovation. In addition, this paper uses SYS-GMM model and selects appropriate instrumental variables to solve the endogeneity problem of the model. We find that after reducing the endogeneity of the model, improving the intensity of environmental regulation can still promote the level of green innovation. Using SDM decomposition model, we find that environmental regulation has spatial spillover effect on green innovation, and the formulation of environmental regulation strategy is conducive to the coordinated development of regional green innovation.

scholarly journals How Do Different Types of Environmental Regulations Affect Green Innovation Efficiency?

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Hui Li ◽  
Chuandang Zhao ◽  
Xiaoying Tang ◽  
Jiawei Cheng ◽  
Guanyang Lu ◽  
...  
Keyword(s):  
Environmental Regulation ◽  
Environmental Regulations ◽  
Evolutionary Relationship ◽  
Command And Control ◽  
Shaanxi Province ◽  
Green Innovation ◽  
Growth Trend ◽  
Different Types ◽  
And Control ◽  
The Impact

Environmental regulation policies are being continuously enriched today. To effectively improve green innovation efficiency through environmental regulations, it is urgent to better understand the impact of different environmental regulations on green innovation efficiency (GIE). However, due to the defects of previous methods for measuring GIE, existing studies may have deviations when analysing the effect of environmental regulations on GIE. To fill this gap, using Shaanxi, China, as a case study, the present study proposes a network data envelopment analysis (DEA) model based on neutral cross-efficiency evaluation to accurately measure the GIE of Shaanxi during the period of 2001–2017. On this basis, this study further analysed the impact of different types of environmental regulations on GIE from three aspects: causality, evolutionary relationships, and effect paths. The results indicate that (1) the GIE of Shaanxi Province showed a “fluctuation-slow growth-steady growth” trend during 2001–2017, and after 2014, the problem of an uncoordinated relationship between technology research and design (R&D) and technology transformation began to appear; (2) there was a linear evolutionary relationship between command-and-control environmental regulation and GIE and a “U”-shaped evolutionary relationship between market-based/voluntary environmental regulation and GIE; and (3) command-and-control environmental regulation and voluntary environmental regulation affected GIE mainly at the technology R&D stage, while market-based environmental regulation ran through the entire process of green innovation activities. This study improves the evaluation methods and theoretical systems of GIE and provides the scientific basis for government decision-makers to formulate environmental regulation policies.

Green innovation to respond to environmental regulation: How external knowledge adoption and green absorptive capacity matter?

2019 ◽  
Vol 29 (1) ◽  
pp. 39-53 ◽  
Author(s):  
Jianming Zhang ◽  
Gongqian Liang ◽  
Taiwen Feng ◽  
Chunlin Yuan ◽  
Wenbo Jiang
Keyword(s):  
Environmental Regulation ◽  
Absorptive Capacity ◽  
Green Innovation ◽  
External Knowledge ◽  
Knowledge Adoption
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