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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.

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.

Binary classification on imbalanced data is a challenge; due to the imbalance of the classes, the minority class is easily masked by the majority class. However, most existing classifiers are better at identifying the majority class, thereby ignoring the minority class, which leads to classifier degradation. To address this, this paper proposes a twin-support vector machines for binary classification on imbalanced data.

In the proposed method, the authors construct two support vector machines to focus on majority classes and minority classes, respectively. In order to promote the learning ability of the two support vector machines, a new kernel is derived for them.

(1) A novel twin-support vector machine is proposed for binary classification on imbalanced data, and new kernels are derived. (2) For imbalanced data, the complexity of data distribution has negative effects on classification results; however, advanced classification results can be gained and desired boundaries are learned by using optimizing kernels. (3) Classifiers based on twin architectures have more advantages than those based on single architecture for binary classification on imbalanced data.

For imbalanced data, the complexity of data distribution has negative effects on classification results; however, advanced classification results can be gained and desired boundaries are learned through using optimizing kernels.

The purpose of this paper is to improve the dyeing effect of fast-growing fir wood dyed with reactive dyes.

In this study, five factors including temperature, the dosage of dye accelerator, dyeing time, the dosage of fixing agent and fixing time were investigated. Then, the color difference and light resistance of the wood surface after dyeing were used as the evaluation indicators; the best dyeing process under the two indicators was obtained through the range analysis. Finally, the two indicators were considered comprehensively, and the fuzzy comprehensive evaluation method was used to obtain the best dyeing process under the comprehensive indicators.

The results show that when the comprehensive index was used as the evaluation index, the optimal dyeing process for reactive red X-3B dyeing fast-growing fir veneer was that the dyeing temperature was 65°C; the amount of dye accelerator was 25 g L⁻¹; the dyeing time was 2 h; the amount of fixing agent was 15 g L⁻¹; and the fixing time was 35 min.

The technique of wood dyeing is an important method to increase the value of wood products. When using different kinds of dyes or dyeing substrates for wood dyeing, the dyeing process is different. This study determined the best process for reactive dye dyeing of fast-growing fir veneer and provided a solution for improving the value of fast-growing fir wood.

This paper constructs the uncertainty analysis model of prefabricated building supply chain risk. The model is designed to study the formation path of prefabricated building supply chain risk and is expected to be used by industry stakeholders for supply chain risk management.

Based on the uncertainty circle model, construct a configuration analysis framework for supply chain risks in prefabricated buildings. The fuzzy set qualitative comparative analysis (fsQCA) is used to study the configuration influence of five uncertain factors, including environment, plan-control, demand-supply, manufacturing and assembly-transportation, on the risk of the prefabricated building supply chain.

There are three paths to promote the high-risk generation of the prefabricated building supply chain: assembly-transportation-oriented, plan-control-oriented and manufacturing-oriented. There is a specific equivalent substitution relationship among the five causal conditions. Under specific conditions, different combinations of conditions have the same effect on promoting supply chain high-risk generation through equivalent substitution.

The multiple concurrent causal relationships of risk conditions in the assembly construction supply chain are studied under the grouping perspective, which helps to expand the research perspective of assembly construction supply chain risk and provides theoretical guidance for supply chain risk management of construction enterprises.

As cross-cultural mergers and acquisitions (M&A) have learning effects on organisations, assessing their impacts on corporate performance is crucial. This study aims to explore the impact of inter-firm cultural differences on long-term post-M&A stock market performance.

The authors select domestic M&A transactions of Chinese listed companies during 2010–2021 as the sample. Then, the authors use the partial least squares structural equation model (PLS-SEM) to construct the latent variable of cultural differences in four dimensions to explore long-term stock market performance.

Cultural differences first positively and then negatively impact post-M&A performance. Three transmissions mechanisms are identified: investor sentiment, takeover premiums and information disclosure quality. Further analysis reveals that acquirer stock performance improves with higher analyst coverage and non-local shareholders but worsens if there are business affiliations between the acquirer and target firms.

This study can help optimise information disclosure systems in M&A transactions for regulatory authorities and aid investors’ understanding of post-M&A performance changes. Furthermore, it can improve acquirers’ understanding of the risks and opportunities in cross-cultural M&A, thereby facilitating the adaptation of management practices to the im-pacts of cultural differences.

By integrating the theories of resource dependence and transaction costs, this study examines the reversal effect of cultural differences between merging companies on post-M&A performance. The authors use a PLS-SEM to empirically analyse the main effects and reveal three transmission mechanisms.

This study aims to identify the attitudes of Chinese residents towards tourists and tourism development. Based on periods of observation, temporary residency and several visits for more than a decade, and supplemented by data collected from 478 residents, the study examines to what extent the rural villagers identify the tourism induced changes as being an outcome of official Chinese policies. The villages, Xidi, Hongcun and Nanping, are three heritage villages in Anhui Province and represent appropriate case studies for such an examination due to their differing histories of tourism administrative procedures. Findings contribute to scholarly knowledge by putting pro-poor tourism and community participation under scrutiny in Chinese context. A change of residents’ perceptions towards tourism could potentially be consequential for tourists’ experience and the sustainability of tourism development, particularly in emerging rural destinations.