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This paper aims to investigate the relationship between corporate environmental, social and governance (ESG) ratings and leverage manipulation and the moderating effects of internal and external supervision.

The authors draw on a sample of Chinese non-financial A-share-listed firms from 2013 to 2020 to explore the effect of ESG ratings on leverage manipulation. Robustness and endogeneity tests confirm the validity of the regression results.

ESG ratings inhibit leverage manipulation by improving social reputation, information transparency and financing constraints. This effect is weakened by internal supervision, captured by the ratio of institutional investor ownership, and strengthened by external supervision, captured by the level of marketization. The effect is stronger in non-state-owned firms and firms in non-polluting industries. The governance dimension of ESG exhibits the strongest effect, with comprehensive environmental governance ratings and social governance ratings also suppressing leverage manipulation.

Firms should strive to cultivate environmental awareness, fulfil their social responsibilities and enhance internal governance, which may help to strengthen the firm’s sustainability orientation, mitigate opportunistic behaviours and ultimately contribute to high-quality firm development. The top managers of firms should exercise self-restraint and take the initiative to reduce leverage manipulation by establishing an appropriate governance structure and sustainable business operation system that incorporate environmental and social governance in addition to general governance.

Policymakers and regulators should formulate unified guidelines with comprehensive criteria to improve the scope and quality of ESG information disclosure and provide specific guidance on ESG practice for firms. Investors should incorporate ESG ratings into their investment decision framework to lower their portfolio risk.

This study contributes to the literature in four ways. Firstly, to the best of the authors’ knowledge, it is among the first to show that high ESG ratings may mitigate firms’ opportunistic behaviours. Secondly, it identifies the governance factor of leverage manipulation from the perspective of firms’ subjective sustainability orientation. Thirdly, it demonstrates that the relationship between ESG ratings and leverage manipulation varies with the level of internal and external supervision. Finally, it highlights the importance of governance in guaranteeing the other two dimensions’ roles by decomposing overall ESG.

The credit migration process contains important information about the dynamics of a firm's credit quality, therefore, it has a significant impact on its relevant credit derivatives. We present a jump diffusion approach to model the credit rating transitions which leads to a partial integro-differential equation (PIDE) formulation, with defaults and rating changes characterized by barrier crossings. Efficient and reliable numerical solutions are developed for the variable coefficient equation that result in good agreement with historical and market data, across all credit ratings. A simple adjustment in the credit index drift converts the model to be used in the risk-neutral setting, which makes it a valuable tool in credit derivative pricing.

The main theme of this volume is credit risk and credit derivatives. Recent developments in financial markets show that appropriate modeling and quantification of credit risk is fundamental in the context of modern complex structured financial products. Moreover, there is a need for further developments in our understanding of this important area. In particular modeling defaults and their correlation has been a real challenge in recent years, and still is. This problem is even more relevant after the so-called subprime crisis that hit in the summer of 2007. This makes the volume very timely and hopefully useful for researchers in the area of credit risk and credit derivatives.

The purpose of this paper is to investigate the superior relationship between blood lipid- and cardiovascular disease (CVD)-related hematological parameters using superior grey relational analysis (GRA).

A total of 294 individuals who underwent simultaneous routine blood examination and blood lipid examination in the Physical Examination Center of the First Affiliated Hospital of Shantou University Medical College were included in this study. Superior GRA was performed to find out the superior factor in CVD-related hematological parameters and blood lipids. CVD-related hematological parameters included red blood cell distribution width, white cell count, and platelet count, platelet distribution width, mean platelet volume, as well as platelet crit. The indicators of blood lipids analyzed here consist of low-density lipoprotein, high-density lipoprotein, triglyceride and total cholesterol.

The results showed that all the grey relational degree of hematological parameters and blood lipids were over 0.8; the superior factor in hematological parameters was PLT, whereas TC was the superior factor in blood lipids.

Findings of this study suggested that hematological parameters are closely related to blood lipids and a potential role for hematological parameters in the prediction of dyslipidemia, which need further study; TC has the greatest influence on hematological parameters, whereas TG displays a minimal impact.

To the authors’ best knowledge, it was the first study to analyze the relationship between various CVD-related hematological parameters and blood lipids via superior GRA.

Electricity demand forecasting has always been a key issue, and inaccurate forecasts may mislead policymakers. To accurately predict China’s electricity demand up to 2030, this paper aims to establish a cross-validation-based linear model selection system, which can consider many factors to avoid missing useful information and select the best model according to estimated out-of-sample forecast performances.

With the nine identified influencing factors of electricity demand, this system first determines the parameters in four alternative fitting procedures, where for each procedure a lot of cross-validation is performed and the most frequently selected value is determined. Then, through comparing the out-of-sample performances of the traditional multiple linear regression and the four selected alternative fitting procedures, the best model is selected in view of forecast accuracy and stability and used for forecasting under four scenarios. Besides the baseline scenario, this paper investigates lower and higher economic growth and higher consumption share.

The results show the following: China will consume 7,120.49 TWh, 9,080.38 TWh and 11,649.73 TWh of electricity in 2020, 2025 and 2030, respectively; there is hardly any possibility of decoupling between economic development level and electricity demand; and shifting China from an investment-driven economy to a consumption-driven economy is greatly beneficial to save electricity.

Following insights are obtained: reasonable infrastructure construction plans should be made for increasing electricity demand; increasing electricity demand further challenges China’s greenhouse gas reduction target; and the fact of increasing electricity demand should be taken into account for China’s prompting electrification policies.

This paper aims to explore the promotion decisions of heterogeneous sellers on a decentralized platform under competitive conditions and analyze how seller behaviors impact platform profit, seller revenue, buyer surplus and social welfare.

This paper considers a Cournot model consisting of a platform charging a commission rate and two sellers with different conversion rates and browsing costs. Promotion efforts by sellers can increase traffic, but they also incur promotion costs for sellers. The sellers decide on promotion effort by weighing these two effects. The authors also explore the equilibrium when the platform charges a fixed usage fee.

The seller’s profit improves as its conversion rate increases and worsens as browsing costs increase. Also, increasing the commission rate charged by the platform makes the seller invest less in promotional efforts. Therefore, the platform must consider this trade-off to determine an optimal rate. The analysis shows that the seller with a high conversion rate and high browsing cost plays a greater role in generating more overall revenue. When the market favors such a seller, the platform tends to charge less in order not to impair its profitability.

This paper incorporates conversion rate, buyer’s browsing cost, unit promotion cost and the fee charged by the platform into the model to study sellers’ promotion decisions on decentralized platforms.

The online Question and Answer community is full of a large number of science and technology topics, the discussion and dissemination of which play an important role in promoting the popularization of new technologies and cultivating public enthusiasm for science. However, the spread of false information and rumors weakens the community's positive effect, making the community more difficult for people to obtain useful information on such topics. Research on the influencing factors and governance of the spread of false information on science and technology topics has become the key to the spread of popular science.

Therefore, this paper uses the Elaboration Likelihood Model as the theoretical framework to examine the role of the factors influencing the spread of false information on science and technology topics in Zhihu community on the information persuasion and the impact on public behavior attitude from the core path and the edge path. This paper compiles a crawler program to capture 12,893 response information under the “Metaverse” topic in Zhihu community as an empirical sample and uses text mining and conducts visual correlation analysis to explore the key factors affecting the persuasive transmission path of information on science and technology topics.

The research finds that the content specialization, content consistency and content coherence of science and technology topics affect personal judgment from the aspect of information content through the core path and have a positive correlation with information persuasion; the number of comments, the length of the text and the publishing authors' influence from the edge image characteristics through the edge path are positively correlated with the information persuasion. Then, from the perspective of topic platform, government and topic participants, this paper puts forward a general plan to improve the information persuasion of science and technology topics so as to deal with false information.

Compared with the small data set of the traditional questionnaire survey, the research based on community empirical big data is more reliable. The model takes into account the attitude and behavior of users and is more suitable for the research on the transmission path of scientific and technological information in the internet era. This research provides a direction for analyzing the text characteristics and development trends of information in the field of science and technology and is conducive to promoting the optimization of the network information environment and building a good ecology, with the spread of rumors about science and technology topics curbed and the governance of false information strengthened.

Nuclear power is a stable and reliable energy source that can improve energy structure while reducing carbon emissions, which is of great significance for environmental protection and combating climate change. As a unique industry, it is facing rare development opportunities in China and has broad market prospects. However, the characteristics of technical difficulty, loose organizational structure and uneven regional distribution limit the expansion of the nuclear power industry. This paper aims to a better understanding of the accumulation process for innovation capability from the perspective of network evolution and provides policy guidance for the market development of the nuclear power industry (NPI).

Methodologically, social network analysis is used to explore the co-evolution of multidimensional collaboration networks. First, the development and policy evolution of the NPI is introduced to divide the evolution periods. Then, the authors identify and analyze the core organizations, technologies and regions that promote nuclear power patent collaboration. Furthermore, three levels of collaboration networks based on organizations, technologies and regions are constructed to analyze the coevolution of patent networks in China’s NPI.

The results show that nuclear power enterprises always play the foremost role in the organizational collaboration network (OCN), and the dominance of foreign enterprises is replaced by Chinese state-owned enterprises in the third period. The technology hotspot has shifted from nuclear power plant construction to the control system. The regional collaboration network was initially formed in the coastal areas and gradually moved inland, with Guangdong and Beijing becoming the two cores of the network. The scale of three collaboration networks is still expanding but the speed has slowed down.

In response to the pain points of the NPI, this research focuses on multidimensional collaborative innovation, investigates the dynamic evolution process of collaborative innovation networks in China’s NPI and links policy evolution with network evolution creatively. The ultimate result not only helps nuclear power enterprises integrate innovative resources in complex environments but also promotes industrial upgrading and market development.

In the information commons (IC) space of library, it is very important to recognize the emotional state of users for better playing the role of IC. In view of this point, this paper aims to discuss the human expression of user emotion.

An emotional state recognition method based on body posture change under video monitoring is proposed. In this method, two parameters are proposed to represent the emotional state of users. Finally, the distribution of users’ overall emotional state is recognized.

It is found that the change of human posture reflects the emotional state of users to a certain extent. The spatial frequency of the user’s average body position change and per capita body position change can reflect the spatial distribution of individual and body position change, respectively.

The method in this paper can effectively overcome the inaccuracy of manual identification of video monitoring images, especially in the case of a large number of users and effectively help the construction of university library IC space and provide a basis for the setting of environmental parameters.