Abstract:Environmental regulations (ERs) that can stimulate technological innovation (TI) are the key to enabling a win-win strategy that benefits both economic development and environmental protection. This study seeks to analyze the impacts of ERs on TI. Previous literature highlighted that the black box of TI can be decomposed into technology investment and technology transformation, but empirical studies on such a decomposition have largely been ignored. Moreover, a detailed discussion of the links between ERs and … Show more
“…Wang et al [21] conducted a study of six carbon trading pilot areas in China, and the results show that the impact of emissions trading on technological innovation is regionally different and may also produce different results due to different types of regulations or types of technological innovation. Li et al [22] found that environmental regulations have a non-linear effect on the efficiency of investment in technological innovation but not on their conversion efficiency.…”
Section: Literature Review and Theoretical Analysismentioning
confidence: 99%
“…According to the available literature, there is also abundant evidence that there are three main relationships between environmental regulation and export competitiveness. First, environmental regulations reduce export competitiveness [22,24,[26][27][28]. Second, environmental regulation improves export competitiveness [6,35,36].…”
Section: Hypothesis 1 Environmental Regulation (Er) Is Negatively Cor...mentioning
Environmental regulation has become a significant way to achieve sustainable development. Taking the panel data of China’s high-tech industries from 2007–2016 in 30 provinces and cities as a sample, regression models are established to study the impact of three different types of environmental regulations on international competitiveness and the moderating effect of R&D (research & development) investment. The results show that the impact of environmental regulations on the international competitiveness of high-tech industries is related to the type of environmental regulation. There is a significant negative correlation between economic environmental regulation (EER) and the international competitiveness of high-tech industries, and R&D investment has a significant inhibitory effect on the relationship between the two. For both commanding environmental regulation (CER) and participatory environmental regulation (PER), R&D investment plays a significant moderating role in environmental regulation and the international competitiveness of high-tech industries. The impact of all three environmental regulations on R&D investment was positive but not significant. Finally, based on these research conclusions, a few countermeasures and suggestions are discussed for the formulation of China’s environmental regulation policies and the development of high-tech industries.
“…Wang et al [21] conducted a study of six carbon trading pilot areas in China, and the results show that the impact of emissions trading on technological innovation is regionally different and may also produce different results due to different types of regulations or types of technological innovation. Li et al [22] found that environmental regulations have a non-linear effect on the efficiency of investment in technological innovation but not on their conversion efficiency.…”
Section: Literature Review and Theoretical Analysismentioning
confidence: 99%
“…According to the available literature, there is also abundant evidence that there are three main relationships between environmental regulation and export competitiveness. First, environmental regulations reduce export competitiveness [22,24,[26][27][28]. Second, environmental regulation improves export competitiveness [6,35,36].…”
Section: Hypothesis 1 Environmental Regulation (Er) Is Negatively Cor...mentioning
Environmental regulation has become a significant way to achieve sustainable development. Taking the panel data of China’s high-tech industries from 2007–2016 in 30 provinces and cities as a sample, regression models are established to study the impact of three different types of environmental regulations on international competitiveness and the moderating effect of R&D (research & development) investment. The results show that the impact of environmental regulations on the international competitiveness of high-tech industries is related to the type of environmental regulation. There is a significant negative correlation between economic environmental regulation (EER) and the international competitiveness of high-tech industries, and R&D investment has a significant inhibitory effect on the relationship between the two. For both commanding environmental regulation (CER) and participatory environmental regulation (PER), R&D investment plays a significant moderating role in environmental regulation and the international competitiveness of high-tech industries. The impact of all three environmental regulations on R&D investment was positive but not significant. Finally, based on these research conclusions, a few countermeasures and suggestions are discussed for the formulation of China’s environmental regulation policies and the development of high-tech industries.
“…Clegg (1989) states that power is a capability premised on resource control. In an innovation network, an organization's technology-innovation capability is the most fundamental and important factor determining its influence (Li et al, 2020), and the most influential organization always has stronger capabilities for searching for and absorbing useful knowledge than others (Cohen and Levinthal, 1990;Prajogo et al, 2020).…”
Section: Formation Of Knowledge Power Originmentioning
Inter-organizational power relations have long been considered to be balanced in innovation networks, which are viewed as loosely coupled systems. Some recent studies, however, show that innovation networks are asymmetric and hierarchical, and the power of network actors has become a significant but rarely addressed issue. As knowledge is the most important resource in the network, this paper introduces the concept of knowledge power by combining related research perspectives and conducting some fundamental research on it as follows: (1) knowledge power’s origins are analyzed by proposing the term “activated knowledge” and studying the path through which it is formed over multiple levels of the network; (2) a multilevel framework of characteristics of activated knowledge, which is considered the major determinant of knowledge power, is established, and suggestions are offered for how they impact knowledge power; and (3) a multilevel measurement model for knowledge power is built, and the above propositions are tested by mathematical inference. The purpose of this paper is not only to study knowledge power’s formation, determinants, and measurement but also to offer a comprehensive view, combining multiple network levels and multiple research perspectives, that should be useful to researchers conducting future studies in this field.
“…At the same time, the profit-seeking nature of enterprises makes it less likely for them to take the initiative to achieve green technological innovation. Therefore, there is an urgent need for external imposed or directed intervention, i.e., environmental regulation [4].…”
Green technology innovation is one of the driving forces of industrial structure upgrading. This innovation is thought to be related to environmental regulation. The study uses panel data for 30 Chinese provinces and cities from 2009 to 2020 and presents a comprehensive research-based explanation of how environmental regulations impact green innovation. This study employs the spatial Durbin model to analyze the spillover effect of the region. The results show that the total impact of environmental regulations is 0.223%, of which the direct effect is 0.099%. This impact includes the effects of both formal and informal environmental regulation. It indicates that ecological regulations significantly enhance green technology innovation. Furthermore, the spatial spillover effect is significantly positive at the 1% level with a coefficient of 0.124. Such spillover effects represent a learning effect of regional environmental regulation. Based on the results, the study suggests a few policy measures based on the detailed outcomes.
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