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Based on institutional theory, this paper aims to examine whether, and if so which, institutional forces influence the quality of China’s listed financial institutions’ (FIs) sustainability disclosures.

Using univariate statistical and multiple regression analyses, this study quantitatively examines the impacts of coercive pressure from the government and stock exchanges, imitation within subsectors and normative pressure from industry associations and regulators on the quality of China’s listed FIs’ sustainability disclosures. Assessment of the robustness of regression results uses panel random-effects and generalized methods of moments estimation.

Financial sector corporate social responsibility (CSR) disclosure quality did not increase dramatically following issue of the “Guiding Opinions on Establishing a Green Finance System.” However, a convergence in quality is found over time. State ownership concentration and state links to dominant shareholders negatively impact the quality of financial sector sustainability disclosures, whereas stock exchange index listing requirements and industry association reporting guidance have positive influences.

First, data availability limits the sample to listed financial firms with RKS quality scores. Thus, results may not be generalizable to the broader listed and unlisted financial sector. Second, this study only examines the influence of external forces based on institutional theory. However, internal institutional forces, such as corporate governance, may require examination. This study’s results indicate that coercive pressure, as represented by issue of the “Green Finance” policy, has not yet prompted the financial sector to improve reporting quality; however, normative pressure has had significant influence in influencing FIs’ CSR practices, with China’s banks potentially taking a leading role.

The financial sector has a lower direct environmental impact than traditional polluting industries and different operating and reporting structures, features often used to argue for its exclusion in prior studies. However, its indirect environmental impact via lending and investing activities is significant, suggesting evidence on the determinants of sustainability disclosure quality is required. This study uses evidence from China’s financial sector to reduce this gap in the literature.

Drawing upon the theory of communication visibility, this research intends to investigate the direct effect of enterprise social media (ESM) usage on team members’ knowledge creation capability (KCC) and the mediating effects of psychological safety and team identification. In addition, it aims to untangle how the efficacy of ESM usage varies between pre- and post-COVID-19 periods.

Using two-wave survey data from 240 members nested within 60 teams, this study utilizes a multilevel approach to test the proposed hypotheses.

We discover that ESM usage enhances team members’ KCC. More importantly, the results show that psychological safety and team identification mediate the ESM–KCC linkage. Interestingly, we further find that the impacts of ESM usage on team members’ KCC, psychological safety, and team identification are stronger in the pre-COVID-19 period than those in the post-COVID-19 period.

This research sheds light on the ESM literature by unraveling the mechanisms of psychological safety and team identification underlying the linkage between ESM usage and team members’ KCC. Moreover, it advances our understanding of the differential efficacy of ESM usage in pre- and post-COVID-19 periods.

Adopting the theory of planned behavior, this study attempts to investigate how subjective norms in the supply chain influence a firm's green innovation and how such influences are contingent upon the firm's internal and external factors (i.e. flexibility orientation and environmental dynamism). Two types of subjective norms are examined, i.e. injunctive norms (what supply chain partners say) and descriptive norms (what supply chain partners do).

Using survey data of 178 Chinese small and medium-sized manufacturers, we employ hierarchical linear regression to test the proposed hypotheses.

Our results indicate that both injunctive and descriptive norms are instrumental in stimulating firms to take actions on green innovation. Moreover, the flexibility orientation of a firm can strengthen the effect of descriptive norms. It is also observed that environmental dynamism weakens the efficacy of injunctive norms but strengthens that of descriptive norms on green innovation.

This study is among the first to apply the theory of planned behavior to explain the microfoundations of focal firm's green innovation and distinguish two types of subjective norms in the supply chain. In addition, it extends the theory of planned behavior by revealing internal and external contingent factors (i.e. flexibility orientation and environmental dynamism) of the relationship between subjective norms and firm behaviors.

The aim of this study is to report the effect of different content of calcium oxide on the process of electromelting magnesia.

The process of molten magnesia was analyzed by finite element simulation and proved by scanning electron microscope.

The results show that with the increase of CaO content, the maximum temperature appreciation increases from 3,616°C To 3,729°C, showing an approximate nonlinear evolution. Low thermal conductivity and low specific heat of CaO result in higher temperature. With the increase of CaO content and temperature, the maximum flow velocity of MgO slag increases from 0.043 to 1.34 mm/s. Under different initial CaO contents, the distribution trend of CaO volume fraction is basically the same, and the CaO volume fraction is evenly distributed between 50 and 225 mm in the furnace.

The influence of different contents of impurity calcium oxide on the process of electromelting magnesia was analyzed and a theoretical system was established.

The anticorrosion coatings used in marine and atmospheric environment are subjected to many environmental factors. And the aging failure has been puzzling researchers. The purpose of this study is to find the correlation between the initial aging of epoxy coatings and the typical marine atmospheric environmental factors.

The epoxy coatings were subjected to a one-year exposure in three typical marine atmospheres. Meanwhile, principal component analysis, linear regression and Spearman and gray correlation analysis were applied to quantify the environmental characteristics and establish correlations with the coating aging.

The results indicate that the coating will undergo macroscopic fading and chalking upon exposure to the marine atmosphere, while microscopic examination reveals holes, cracks and partial peeling. The adhesion performance and electrochemical properties of the coating deteriorated with prolonged exposure, coating aging mainly occurs with the generation of O-H bonds and the breakage of molecular chains such as C-N and C-O-C. The coating was most deeply aged after exposure to the Xisha, followed by Zhoushan and finally Qingdao. Environmental factors affect the photooxidative aging and hydrolytic degradation processes of coatings and thus coating aging. To further demonstrate the correlation between environmental factors and coating aging, principal component analysis was used. The correlation model between environmental factors and coating aging was subsequently obtained. The correlation model between the rate of coating adhesion loss (E) and the comprehensive evaluation parameter of environmental factors (Z) is expressed as E = 0.142 + 0.028Z. Meanwhile, the Spearman correlation analysis and gray correlation method were used to investigate the impact of each environmental factor on coating aging. Solar irradiation, relative humidity and wetting time have the highest correlation with coating aging, which are all above 0.8 and have the greatest influence on coating aging; wind speed and temperature have the smallest correlation with coating aging, which are about 0.6 and have the least influence on coating aging.

This paper establishes a correlation between typical marine environmental factors and coating aging performance, which is crucial for predicting the service life of other coatings in diverse environments.

The purpose of this paper is to propose a consensus method for multi-attribute group decision-making (MAGDM) problems based on preference-approval structure and regret theory, which can improve the efficiency of decision-making and promote the consensus level among individuals.

First, a new method to obtain the reference points based on regret theory and expert weighting method is proposed. Second, a consensus reaching method based on preference-approval structure is proposed. Then, an adjustment mechanism to further improve the consensus level between individuals is designed. Finally, an example of the assessment of elderly care institutions is used to illustrate the feasibility and effectiveness of the proposed method.

The feasibility and validity of the proposed method are verified by comparing with the advanced two-stage minimum adjustment method. The compared results show that the proposed method is more consistent with the actual situation.

This paper presents a consensus reaching method for MAGDM based on preference-approval structure, which considers the avoidance behaviors of individuals and reference points. Decision makers (DMs) can use this approach to rank and categorize alternatives while further increasing the level of consensus among them. This can further help determine the optimal alternative more efficiently.

A new MAGDM problem based on the combination of regret theory and individual reference points is proposed. Besides, a new method of obtaining experts' weights and a consensus reaching method for MAGDM based on preference-approval structure are designed.

This study examines the impact of China’s mixed-ownership reform on the innovation of non-state-owned acquirers, with a particular focus on the impact on firms with high financing constraints, low-quality accounting information or less tangible assets.

We use a proprietary dataset of firms listed on the Shanghai and Shenzhen Stock Exchanges to investigate the impact of mixed ownership reform on non-state-owned enterprise (non-SOE) innovation. We employ regression analysis to examine the association between mixed ownership reform and firm innovation.

The study finds that non-state-owned firms can improve innovation by acquiring equity in state-owned enterprises (SOEs) under the reform. Eased financing constraints, lowered financing costs, better access to tax incentives or government subsidies, lowered agency costs, better accounting information quality and more credit loans are underlying the impact. Additionally, cross-ownership connections amongst non-SOE executives and government intervention strengthen the impact, whilst regional marketisation weakens it.

This study adds to the literature on the association between mixed ownership reform and firm innovation by focussing on the conditions under which this impact is stronger. It also sheds light on the policy implications for SOE reforms in emerging economies.

This study investigates the impact of human capital (managers' capital, employees' capital) and orientation (market orientation, entrepreneurial orientation) for accelerating the digitalization process and improving the firm performance. It also studies the role of supply chains as both direct and indirect mediators of the correlation between digitalization and business performance.

This article aims to develop an empirical study using a random sampling technique and survey data collected from 368 managers and owners of different food enterprises in Vietnam. The study adopted a methodological approach quantitatively. Analysis of the relationships and confirmatory factors was performed using structural equation modeling (SEM), a technique to evaluate the proposed relationships.

In line with expectations, the findings emphasize the impact of human capital (managers' capital, employees' capital) and orientation (market orientation, entrepreneurial orientation) for accelerating the digitalization process and the role of supply chains as both direct and indirect mediators of the correlation between digitalization and improving the firm performance, in the context of emerging markets.

This is an important investigation, according to the authors' knowledge, regarding the role of developing human capital (managers' capital, employees' capital) and orientation (market orientation, entrepreneurial orientation) as a key strategy for accelerating the digitalization process and improving the firm performance. Further, the study's novelty reinforces the role of supply chains as both direct and indirect mediators of the correlation between digitalization and business performance in the Vietnamese food companies, where a market economy is emerging.

This study aims to propose a consensus model that considers dynamic trust and the hesitation degree of the expert's evaluation, and the model can provide personalized adjustment advice to inconsistent experts.

The trust degree between experts will be affected by the decision-making environment or the behavior of other experts. Therefore, based on the psychological “similarity-attraction paradigm”, an adjustment method for the trust degree between experts is proposed. In addition, we proposed a method to measure the hesitation degree of the expert's evaluation under the multi-granular probabilistic linguistic environment. Based on the hesitation degree of evaluation and trust degree, a method for determining the importance degree of experts is proposed. In the feedback mechanism, we presented a personalized adjustment mechanism that can provide the personalized adjustment advice for inconsistent experts. The personalized adjustment advice is accepted readily by inconsistent experts and ensures that the collective consensus degree will increase after the adjustment.

The results show that the consensus model in this paper can solve the social network group decision-making problem, in which the trust degree among experts is dynamic changing. An illustrative example demonstrates the feasibility of the proposed model in this paper. Simulation experiments have confirmed the effectiveness of the model in promoting consensus.

The authors presented a novel dynamic trust consensus model based on the expert's hesitation degree and a personalized adjustment mechanism under the multi-granular probabilistic linguistic environment. The model can solve a variety of social network group decision-making problems.