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This article investigates the influence of marine ecological compensation policy on enterprises’ environmental investment and explores whether enterprise ownership could impact the said influence.

Using the data of China's A-share listed enterprises for the period 2007–2020, the paper develops a difference-in-differences model and a moderating effect model.

The outcomes corroborate that the marine ecological compensation policy positively influences enterprises' environmental investment, and the effect is nonlinear. Specifically, the marine ecological compensation policy significantly impacts enterprises with lower and higher environmental investment. The empirical evidence from the moderation model shows that the effect of the policy is more significant on the non-state-owned enterprises’ environmental investment.

The findings are based on a sample of 559 listed A-share enterprises in China. Additional studies could focus on data from other countries.

Based on the present scenario of Chinese enterprises' environmental investment, the results report that the marine compensation policy needs to be differentiated for firms having different ownership and different levels of environmental investment. The study provides valuable insights for the government to formulate marine ecological compensation policies.

Marine ecology increasingly affects the economic development of countries, and the study on the influence of relevant environmental policies is of practical significance. However, most scholars concentrate on the research of environmental regulation, and have little focus on the policy effect of marine environmental compensation. This paper studies how marine ecological compensation policy influences the environmental investment behavior of enterprises, and further analyzes the difference in the policy effect caused by the nature of enterprises’ ownership, which not only fills the gap in this field, but also provides a scientific basis for the formulation and adjustment of marine ecological compensation policy.

This paper aims to identify the influence of innovation network and technological learning on innovation performance of high-tech cluster enterprises.

Using a questionnaire, data are collected from Dalian High-tech Industrial park in China. In addition, structural equation model is used to identify the influence of innovation network and technological learning on the innovation performance of high-tech cluster enterprise.

The findings of this study show that the centrality of network location and the strength of the network relationship have a direct positive effect on technology acquisition, technology digestion and technology exploit of high-tech cluster enterprises. Meanwhile, technology acquisition has a direct positive effect on technology digestion, technology digestion has a direct positive effect technology exploit, and technology exploit has a direct positive effect innovation performance of high-tech cluster enterprises.

To improve innovation performance, high-tech cluster enterprises should not only nurture and optimize innovation networks but also improve technological learning ability.

This paper empirically supports the significant influence of innovation network and technological learning on innovation performance. While the results provide guidance for researchers and practitioners, it also adds value to innovation-related research.

The purpose of this paper is to find out the characteristics and evolutionary trends of China’s inter-regional innovation correlation network, the status and roles of each province in China’s inter-regional innovation correlation network and the influencing factors of China’s inter-regional innovation correlation effect.

Based on the patent data of 30 provinces (autonomous regions and municipalities) in China from 1991 to 2017, social network analysis was used to find out the characteristics and evolutionary trends of China’s inter-regional innovation correlation network and the status and roles of each province in China’s inter-regional innovation correlation network. Furthermore, the QAP method was used to find out the influencing factors of China’s inter-regional innovation correlation effect.

China’s inter-regional innovation correlation is becoming increasingly close and inter-regional innovation correlation network is becoming increasingly stable. Jiangsu, Zhejiang, Beijing, Shanghai, Guangdong and other eastern coastal provinces are at the core in the inter-regional innovation correlation network, while the western regions are marginal actors. China’s regional innovation development territory can be divided into four blocks, namely, “bidirectional spillover block,” “net spillover block,” “main beneficial block” and “net beneficial block,” and gradient transfer mechanism is obvious between the blocks. The geographical adjacency and similarity in regional industrial structure, urbanization level and government attention degree have significant positive effect on China’s inter-regional innovation correlation effects.

This paper only uses patent application as a measure of regional innovation level to analyze inter-regional innovation correlation effect. Meanwhile, this paper carries out an empirical study only from the provincial level and not from the city level.

This paper provides the practical basis for further promoting the coordinated development of regional innovation and promoting the construction of regional innovation systems with different characteristics.

This paper contributes to understand the status and role of each province in inter-regional innovation correlation network. Meanwhile, this paper also helps to understand the influence of the proximity and external environmental factors on inter-regional innovation correlation effect.

The purpose of this paper is to analyze the effect of environmental policy China’s national program to address climate change on carbon emission efficiency.

Based on the directional distance function, the provincial total factor carbon emission efficiency was measured. Then, the authors analyzed the effect of environmental policy on carbon emission efficiency based on a difference in difference model.

Carbon emission efficiency has been significantly improved since the environmental policy China’s national program to address climate change was put forwarded, but the positive impact in different periods and regions is different. In addition, the environmental policy improves the carbon emission efficiency through the reduction of energy intensity and adjustment of the industrial structure.

This is the first time to use difference in difference model to use a difference in difference model to quantitatively assess the influence of environmental policy China’s national program to address climate change on carbon emission efficiency.

Environmental regulation policy and cleaner production technology innovation are the key links to achieve sustainable economic development. This paper tests the impact of Two Control Zone (TCZ) environmental regulation policy on cleaner production technology innovation and explains the heterogeneity effect between them from the perspective of regional pollution intensity and R&D investment scale.

This paper takes TCZ policy as an environmental regulation policy and collects the patent data related to coal desulfurization cleaner production technology innovation in prefecture-level cities from 1994 to 2002 in China. This paper also tests the relationship between TCZ environmental regulation policy and cleaner production technology innovation based on difference in difference (DID) model. Take regional R&D investment scale and pollution intensity as category variables and analyze the heterogeneity effect of TCZ environmental regulation policy on cleaner production technology innovation based on difference-in-difference-in-difference (DDD) model.

TCZ environmental regulation policy effectively promotes China's cleaner production technology innovation, but it is more conducive to cleaner production technology innovation in heavy pollution areas. With the increasing of R&D investment scale, the positive effect of TCZ environmental regulation policy on cleaner production technology innovation is stronger.

On the basis of this study, the authors should further explore the regulatory factors of the relationship between TCZ environmental regulation policy and cleaner production technology innovation and further expand the research object, so as to make the research conclusions more practical and instructive.

This paper tests the impact of TCZ environmental regulation policy on cleaner production technology innovation based on the prefecture city level data and DID model, and it handles the endogenous problem caused by the missing variables and provides the accurate conclusions. Moreover, this paper examines the heterogeneity effect of TCZ environmental regulation policy on cleaner production innovation from regional R&D investment scale and pollution intensity two hands and expands the existing theoretical research.

The purpose of this paper is to explore the impact of peer-to-peer (P2P) supply chain financing on companies' innovation efficiency.

This study takes the core companies that invest in the P2P platform as the research background and uses data for Chinese companies and the systematic Generalised Method of Moments (the systematic GMM) to explore the relationship between the improvement of supply chain efficiency, research and development (R&D) investment, and innovation efficiency.

This study indicates that core enterprise investment in P2P can cause a significant improvement in the efficiency of the supply chain and that this improvement can significantly motivate enterprises to increase R&D investment. Although the improvement of supply chain efficiency has no significant effect on improving companies' innovation efficiency, it can have a positive impact on innovation efficiency through the regulating role of R&D investment.

This research shows several limitations such as single industry and few companies involved, but it analyses the impact of P2P supply chain financing on R&D investment, and companies' innovation efficiency and broadens the research field of P2P supply chain financing.

This article provides a theoretical direction for listed companies to invest in P2P platforms and achieve supply chain management. The research on the regulating role of this article provides a new way of thinking for the study of enterprise innovation.

This paper analyses the impact of the core enterprise investment in P2P on R&D investment and its subsequent impact on the companies' innovation efficiency, thus broadening the research field of P2P supply chain financing.

The purpose of this paper is to add to the existing research about how corporate performance is influenced by their basic research (BR) investment. On this basis, the authors examined the moderating effect of human capital structure (HCS) on the relationship between BR investment and corporate performance.

Hypotheses were tested using static and dynamic models to analyze a large-scale data of Chinese A-share listed companies.

This study provides empirical evidence that contributes to the research about how private BR investment influences corporate performance in the digital age. In addition, human resource is an important dynamic ability for enterprise development. Based on the dynamic capability theory, further research finds that the human resources practice on the knowledge stock can enhance the company’s dynamic capability, thereby enhancing the company’s core competitiveness.

The results may be affected by the context of the data set. This study considers the influence of private research investment type on corporate performance, further studies considering the influence of specific contextual variables, such as corporate industry differences, could yield richer insights that would help validate the results of this study.

This study provides useful information for managers. As well as increasing the investment in the BR of enterprise and creating the necessary conditions to increase the competitiveness of enterprise, they should strive to adjust the structure and quality of researchers involved in BR projects.

This research contributes to the enterprise’s BR investment and the management of human capital resource. It points that the investment of BR positively influences the corporate performance. In addition, the increasing of high-skilled labor’s proportion positively promotes the promotion of BR investment on corporate performance.

Prior studies have confirmed market segmentation as an important shackle to China's macroeconomy upgrade, but the systematic analysis of microenterprise upgrade remains inadequate. This paper aims to investigate the nonlinear impact of market segmentation on microenterprise upgrade.

The price method was applied to calculate China's provincial market segmentation, including commodity, capital, labor and energy. The generalized method of moments was employed to examine the nonlinear impact of market segmentation on the upgrading of manufacturing enterprises based on microenterprise data from 2003 to 2019.

First, China’s heterogeneous market segmentations have been significantly reduced. Macroeconomics and policies are critical factors in market integration. Second, there is an inverted U-shaped relationship between China’s total market segmentation and the upgrading of manufacturing enterprises. Third, the relationship between the commodity market segmentation, labor market segmentation, energy market segmentation and manufacturing enterprises' upgrade is shown as an inverted U-shaped. Nevertheless, the relationship between the capital market segmentation and upgrading of manufacturing enterprises exhibits a U-shape.

The impact of market segmentation on the upgrading of manufacturing enterprises in China performs nonlinearly. An inverted U-shaped relationship exists between market segmentation in commodity, labor and energy and the upgrading of manufacturing enterprises, while a U-shaped relationship prevails between capital market segmentation and the upgrading of manufacturing enterprises.