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The purpose of this paper is to construct an index for systemic risk in China.

This paper develops a systemic risk index for China (SRIC) using textual information from 26 leading newspapers in China. Our index measures the systematic risk from 21 topics relating to China’s economy and provides narratives of the sources of systemic risk.

SRIC effectively predicts changes in GDP, aggregate financing to the real economy and the purchasing managers’ index. Moreover, SRIC explains several other commonly used macroeconomic indicators. Our risk measure provides a helpful monitoring tool for policymakers to manage systemic risk.

The paper construct an index of systemic risk based on the information extracted from newspaper articles. This approach is new to the literature.

Nature provides a wide range of structures with different functions, which can serve as a source of research concepts. Based on the bionics principle, a bionic structure was applied to drill pipe specimens to compare the bond strength of paint coatings with and without a bionic ring groove pattern machined on the substrate.

Using the Revetest Xpress Plus scratch tester, the bond strengths of the coatings on the drill pipe with and without the bionic structure were measured and the difference in bond strength was observed.

The critical scratch loads of the surface coatings were 12.77 and 5.4 N. Furthermore, the scratch curve from the plain sample had a larger fluctuation compared to the curve of the samples with bionic ring grooves.

This indicated that the application of a bionic pattern to the surface of the substrate could enhance the bond strength and the degree of mechanical adhesion between the coating and the surface of the drill pipe, which is beneficial for the anti-corrosion performance of the drill pipe.

The purpose of this paper is to obtain some strong deviation theorems for arbitrary continuous random variable sequences under suitable restrict Chung‐Teicher type conditions.

The crucial part of the proof is to construct a.s. convergence super‐martingale by means of the notion of limit logarithmic likelihood ratio of random variable sequences and then applying the martingale convergence theorem.

The upper and lower bounds of the deviations from the sums of arbitrary continuous random sequence to their marginals are obtained.

The rigorous bounds are the main limitations which are difficult to obtain.

A useful method to study the property of dependent random sequence.

The paper presents the new approach of proof strong limit theorems.

China is not only the biggest mutton consumer, but also the top mutton importer in the world. China’s urban households are becoming the key driving force behind a surge in mutton consumption. Therefore, the purpose of this paper is to investigate the determinants of mutton demand in urban China.

Based on a sample of 32,910 urban households across six provinces and autonomous regions, an inverse hyperbolic sine (IHS) double-hurdle model is estimated, by maximum likelihood estimation, to reveal the determinants of mutton consumption-at-home.

The empirical results indicate that, first, household income has a positive effect on mutton consumption, and higher income households have a higher income elasticity; second, wet weather increases probability, but reduces conditional level and unconditional level; finally, minority group households consume more mutton than Han group households.

It is necessary for policymakers to develop a long-term outlook in relation to the increase of China’s mutton appetite and to shift from a domestic perspective to a global one and develop diversified import strategies. Furthermore, policymakers require to make a practicable emergency preplan for tackling short-term agglomeration of demand for mutton, attributed to festivals, and religious events of a minority ethnic group.

This is a major work based on a large sample of 32,910 urban households conducted by the National Bureau of Statistics of China. This paper uses an IHS double-hurdle model to quantify the determinants of mutton consumption; it sheds light on the climatic, regional, and ethnic characteristics of mutton consumption in urban China.

Weather affects consumer decision-making. However, academic research on how weather factors affect specific takeaway foods is limited. This paper aims to fill in the gap and therefore to contribute to online marketing and operation.

Web crawler techniques were first exploited to collect takeaway food ordering data from Meituan, the world’s largest GMV platform. Then statistics models and a time series regression model were selected to study the weather impact on online orders.

The findings highlight that certain weather factors, such as temperature, air quality and rainfall have clear effects on most category takeaway orders.

Quantitative analysis of weather impacts on the takeaway ordering business will help to guide the online service platforms for marketing promotion and the settled businesses to make reasonable arrangements for inventory and marketing tactics.

The purpose of this paper is to propose an availability modeling method of complex multiple units system (CMUS) based on the multi-agent technique.

Based on the multi-agent technique, this paper describes the availability model structure for CMUS and develops agent-based models of components, maintenance policies, maintenance tools, maintenance fields, and maintenance staff, as well as the communication method among the different agents. On the basis of the agent-based availability modeling theory, the availability simulation scheme of CMUS is given using MATLAB. Thus, the availability modeling theory of CMUS and its simulation method are developed. To demonstrate the applicability of the proposed availability modeling method, a numerical example is given.

The proposed agent-based modeling method is applicable to availability modeling of CMUS, including the modeling of component failure, maintenance tools/fields/staff, maintenance policy, and structural/economic dependence among components.

As a bottom-top, modular, expandable, and reusable modeling theory, the agent-based modeling method might be useful for availability modeling of different CMUSs in reality.

The multi-agent technique is introduced into availability modeling of multi-component systems in this paper. Thus, it is possible to model failure of many components, maintenance policies, maintenance tools, maintenance fields, and maintenance staff together for availability analysis of complex systems of equipment.

The authors investigated how and when work connectivity behavior after-hours (WCBA) spilled over to cyberloafing, considering ego depletion as a mediator and motivations and workaholism as moderators. This paper aims to discuss the aforementioned objective.

In Study 1, 380 employees participated in a scenario experiment with a 2 × 2 between-subjects design. Studies 2 and 3 involved 483 and 406 employees, respectively in two two-wave surveys.

WCBA was indirectly linked to cyberloafing via ego depletion. However, when WCBA was driven by high autonomous and low controlled motivation, it exerted less influence on ego depletion, thus weakening the mediating effect of ego depletion. Moreover, the association between WCBA and ego depletion was not significant among employees accustomed to excessive work. The indirect effect of ego depletion also operated contingently on the level of excessive work.

The findings shed light on the spillover effects of WCBA, suggesting that WCBA may lead to cyberloafing by depleting resources. However, the influence of WCBA on ego depletion is concealed when employees engage in WCBA autonomously or are habituated to excessive work.

Based on upper echelons theory and social contagion theory, we investigate how environmental leadership affects GIC via green human resource management (GHRM) and examine the moderating role of environmental climate.

We conduct hierarchical regression and use the bootstrap method to analyze the two-waved data from 317 Chinese manufacturers in order to verify the hypotheses.

The results indicate that GHRM mediates the impacts of environmental leadership on green human capital, structural capital and relational capital. In addition, environmental climate strengthens the positive impact of environmental leadership on GHRM.

Our study enriches the literature on GIC by uncovering the “black box” between environmental leadership and GIC, providing a logical framework opposite to mainstream GIC research, and expanding the boundary condition for GIC accumulation. This study provides more logical paths for enterprises and governments to increase the accumulation of GIC and promote green intellectual economy development.

This study aims to identify the key factors that influence household pro-environmental behaviors (HPEBs) and explore the differences caused by the same influencing factors between household waste management behavior (HWM) and household energy-saving behavior (HES).

A meta-analysis was conducted on 90 articles about HPEBs published between 2009 and 2023 to find the key factors. HPEBs were further categorized into HWM and HES to investigate the difference influenced by the above factors on two behaviors. The correlation coefficient was used as the unified effect size, and the random-effect model was adopted to conduct both main effect and moderating effect tests.

The results showed that attitude, subjective norms, and perceived behavioral control all positively influenced intention and HPEBs, but their effects were stronger on intention than on HPEBs. Intention was found to be the strongest predictor of HPEBs. Subjective norms were found to have a more positive effect on HES compared to HWM, while habits had a more positive effect on HWM. Furthermore, household size was negatively correlated with HWM but positively correlated with HES.

The same variables have different influences on HWM and HES. These results can help develop targeted incentives to increase the adoption of HPEBs, ultimately reducing household energy consumption and greenhouse gas emissions and contributing to the mitigation of global warming.

Using the behavioural perspective as a theoretical complement of rational models, this paper examines factors that influence the decision of producing organic wines.

Based on a quantitative analysis of 687 wineries belonging to Denomination of Origin in Spain, the authors empirically examine the sequential relationships between manager's personality and winery and institutional level factors, on organic wine production activity and winery export performance.

This paper investigates the direct and indirect sequential relationships between wineries' factors including an organic production activity and two dimensions of export performance, namely: volume-based and value-based performance. The results of a sequential model provide evidence that openness to experience, a manager's personality trait, has a positive causal relationship with organic wine production.

This paper offers richer insights into the factors leading wine production managers to change from conventional to organic production methods. Specifically, the study shows that wine production managers are susceptible to make decisions to whether produce organic wine or not that may not be consistent with the current theoretical models based on economic efficiency (i.e. comparing costs and benefits). Instead, these decisions are, in part, based on their personality traits. Future research could study how the functional attribute affects the willingness to produce organic wines.

This study contributes to a new strategic implication of organic wine production activity and export performance linkage in behavioural and traditional theoretical perspectives. These findings are valuable for policy makers in the wine sector, as they can better inform and guide policies directed to identify organic production support programs.