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In the context of Industry 4.0, intelligent construction technologies (ICT) represented by information technology and networking will undoubtedly provide new impetus to the development of the prefabricated building supply chain (PBSC), but they will also bring various potential risks. So far, there is a large lack of research on the comprehensive consideration of the risks associated with the intelligent transformation of PBSC based on the information sharing perspective, and the critical risks and interactions are still unclear, making it difficult to identify efficient risk mitigation strategies. Therefore, this paper aims to reveal the interactions between stakeholders and clarify the critical risk nodes and interactions in information sharing of PBSC (IS-PBSC), and propose targeted risk mitigation strategies.

Firstly, this paper creatively delineates the risks and critical stakeholders of IS-PBSC. Secondly, Data is collected through questionnaires to understand the degree of risks impact. Thirdly, with the help of NetMiner 4 software, social network analysis is conducted and IS-PBSC risk network is established to reveal critical risk nodes and interactions. Finally, further targeted discussion of critical risk nodes, the effectiveness and reasonableness of the risk mitigation strategies are proposed and verified through NetMiner 4 software simulation.

The results show that the critical risks cover the entire process of information sharing, with the lack of information management norms and other information assurance-related risks accounting for the largest proportion. In addition, the government dominates in risk control, followed by other stakeholders. The implementation of risk mitigation strategies is effective, with the overall network density reduced by 41.15% and network cohesion reduced by 24%.

In the context of Industry 4.0, ICT represented by information technology and networking will undoubtedly provide new impetus to the development of the PBSC, but they will also bring various potential risks. So far, there is a large lack of research on the comprehensive consideration of the risks associated with the intelligent transformation of PBSC based on the information sharing perspective, and the critical risks and interactions are still unclear, making it difficult to identify efficient risk mitigation strategies.

Based on the results of risk network visualization analysis, this paper proposes an ICT-based IS-PBSC mechanism that promotes the development of the integration of ICT and PBSC while safeguarding the benefits of various stakeholders.

Polyaniline (PANI) has garnered attention for its potential applications in anticorrosion fields because of its unique properties. Satisfactory outcomes have been achieved when using PANI as a functional filler in organic coatings. More recently, research has extensively explored PANI-based organic coatings with self-healing properties. The purpose of this paper is to provide a summary of the active agents, methods and mechanisms involved in the self-healing of organic coatings.

This study uses specific doped acids and metal corrosion inhibitors as active and self-healing agents to modify PANI using the methods of oxidation polymerization, template synthesis, nanosheet carrier and nanocontainer loading methods. The anticorrosion performance of the coatings is evaluated using EIS, LEIS and salt spray tests.

Specific doped acids and metal corrosion inhibitors are used as active agents to modify PANI and confer self-healing properties to the coatings. The coatings’ active protection mechanism encompasses PANI’s own passivation ability, the adsorption of active agents and the creation of insoluble compounds or complexes.

This paper summarizes the active agents used to modify PANI, the procedures used for modification and the self-healing mechanism of the composite coatings. It also proposes future directions for developing PANI organic coatings with self-healing capabilities. The summaries and proposals presented may facilitate large-scale production of the PANI organic coatings, which exhibit outstanding anticorrosion competence and self-healing properties.

Many studies have investigated dynamic positions and their importance, but there is less attention paid to how to enter more central positions. Interorganizational relationships are an important factor in network structural change. In Chinese society, firms allocate significant human, financial and material resources towards cultivating guanxi. The purpose of this study is to explore whether and how the three aspects of guanxi, namely renqing, ganqing and xinyong, can make firms more central, and to examine the mediating role of interaction.

The study used a mixed method to collect data from 256 Chinese Cops (complex product systems) firms. And, hypotheses were tested using SPSS 25.0 and AMOS 26.0.

The results indicate that renqing, ganqing and xinyong have significant positive effects on the increase in centrality, but with varying magnitudes. Additionally, the interaction was found to mediate the relationship between the three aspects of guanxi (renqing, ganqing and xinyong) and the increase in centrality.

The study provides new insights to help firms become more central by combining guanxi (renqing, ganqing and xinyong) with change in centrality, enriching the literature on network dynamics and guanxi-related research. Moreover, the study provides managers with a clear understanding of how to use guanxi to make the firm more central in situations with limited resources.

This paper aims to find the best method to predict the friction coefficient of textured 45# steel by comparing different machine learning algorithms and analytical calculations.

Five machine learning algorithms, including K-nearest neighbor, random forest, support vector machine (SVM), gradient boosting decision tree (GBDT) and artificial neural network (ANN), are applied to predict friction coefficient of textured 45# steel surface under oil lubrication. The superiority of machine learning is verified by comparing it with analytical calculations and experimental results.

The results show that machine learning methods can accurately predict friction coefficient between interfaces compared to analytical calculations, in which SVM, GBDT and ANN methods show close prediction performance. When texture and working parameters both change, sliding speed plays the most important role, indicating that working parameters have more significant influence on friction coefficient than texture parameters.

This study can reduce the experimental cost and time of textured 45# steel, and provide a reference for the widespread application of machine learning in the friction field in the future.

The purpose of this study is to use the corrected stress field theory to derive the shear capacity of geopolymer concrete beams (GPC) and consider the shear-span ratio as a major factor affecting the shear capacity. This research aims to provide guidance for studying the shear capacity of GPC and to observe how the failure modes of beams change with the variation of the shear-span ratio, thereby discovering underlying patterns.

Three test beams with shear span ratios of 1.5, 2.0 and 2.5 are investigated in this paper. For GPC beams with shear-span ratios of 1.5, 2.0 and 2.5, ultimate capacities are 337kN, 235kN and 195kN, respectively. Transitioning from 1.5 to 2.0 results in a 30% decrease in capacity, a reduction of 102kN. Moving from 2.0 to 2.5 sees a 17% decrease, with a loss of 40KN in capacity. A shear capacity formula, derived from modified compression field theory and considering concrete shear strength, stirrups and aggregate interlocking force, was validated through finite element modeling. Additionally, models with shear ratios of 1 and 3 were created to observe crack propagation patterns.

For GPC beams with shear-span ratios of 1.5, 2.0 and 2.5, ultimate capacities of 337KN, 235KN and 195KN are achieved, respectively. A reduction in capacity of 102KN occurs when transitioning from 1.5 to 2.0 and a decrease of 40KN is observed when moving from 2.0 to 2.5. The average test-to-theory ratio, at 1.015 with a variance of 0.001, demonstrates strong agreement. ABAQUS models beams with ratios ranging from 1.0 to 3.0, revealing crack trends indicative of reduced crack angles with higher ratios. The failure mode observed in the models aligns with experimental results.

This article provides a reference for the shear bearing capacity formula of geopolymer reinforced concrete (GRC) beams, addressing the limited research in this area. Additionally, an exponential model incorporating the shear-span ratio as a variable was employed to calculate the shear capacity, based on previous studies. Moreover, the analysis of shear capacity results integrated literature from prior research. By fitting previous experimental data to the proposed formula, the accuracy of this study's derived formula was further validated, with theoretical values aligning well with experimental results. Additionally, guidance is offered for utilizing ABAQUS in simulating the failure process of GRC beams.

Excessive borrowing significantly contributes to pushing businesses towards default and their transition into zombie enterprises. Despite government efforts to implement deleveraging policies and guide bank credit flows, it’s essential to delve into the internal dynamics that steer the borrowing behavior of these zombie enterprises at a micro level. To gain a comprehensive understanding of the issue, this study focuses on examining the incentives that drive corporate executives of zombie enterprises to consistently engage in large-scale borrowing from banks.

In this study, panel data analysis is utilized, incorporating firm-, industry- and year-fixed effects. Drawing from data pertaining to listed companies in China spanning from 2007 to 2020, we employ a one-by-one identification method to pinpoint zombie enterprises. Ultimately, a total of 2,533 samples of zombie enterprises were obtained.

The results indicate that as bank loans to zombie enterprises increase, executive monetary compensation decreases, while on-the-job consumption by executives increases, and they are less likely to be forced into rotation. Mechanism testing reveals that corporate performance partially mediates the relationship between bank loans and executive monetary compensation, but this mediation is ineffective for on-the-job consumption and job rotation. Further investigation suggests that the property rights nature of central enterprises and modified audit opinions can exacerbate the adverse impact of bank loans on the monetary compensation of zombie corporate executives, without significantly affecting on-the-job consumption or job rotation. Conversely, executive power does not enhance the positive effects of bank loans on monetary compensation or on-the-job consumption, but it diminishes the negative impact of bank loans on the forced rotation of zombie executives.

These results indicate that while bank loans may have a negative impact on corporate value, they function as safeguards for the positions and interests of executives. As a result, bank loans serve as incentives for executives of zombie enterprises.

This study holds theoretical significance as it explores the motivations behind non-performing loans in high-borrowing enterprises, sheds light on corporate governance challenges encountered by zombie enterprises and provides policy insights aimed at addressing the underlying causes of persistent non-performing loans in high-borrowing enterprises, including zombie enterprises.

Face is the most intuitive and representative feature at the individual level. Many studies show that beautiful faces help individuals and enterprises obtain economic benefits and form a high economic premium, but the discussion of their potential social value is insufficient. This study aims to focus on the impact of the personal characteristics of executives. It mainly analyzes the impact mechanism of CEO facial attractiveness on corporate social responsibility (CSR) decision-making, clarifying the social value of beauty from the perspective of CSR.

The authors use the regression model to analyze the panel data set, which was conducted by a sample of Chinese publicly listed firms from 2016 to 2018.

The study found that CEOs with high facial attractiveness are more active in fulfilling CSR, which can usually bring higher social benefits. CEOs with beautiful faces are prone to overconfidence, are optimistic about their ability and the future development of the enterprise and are more willing to increase their investment in CSR. CEO duality can positively regulate the positive correlation between a CEO’s facial attractiveness and CSR.

Based on the perspective of upper echelons theory, this paper explores the mechanism of CEO facial attractiveness on CSR. This study enriches the perspective of the upper echelon’s theoretical research and has essential enlightenment for CEO selection and training practice.

This study aims to test the effect of individual audit quality on career advancement the audit labour market.

This paper uses data on auditors from two collapsed audit firms in China, namely, Ruihua and Zhengzhong Zhujiang, and tests the effect of individual audit quality on career advancement in the audit labour market.

The baseline results show that high-quality audits promote auditors’ career advancement. Our results hold after a battery of robustness tests. Further analyses support our hypothesis, indicating that client retention and audit fees are positively related to auditors’ prior audit quality. The effect of audit quality on career advancement does not hold for auditors from sanctioned branch offices or for auditors with prior culpable clients, as shared reputation damage can weaken the effect of high audit quality. Furthermore, this paper investigates whether the reputation enhancement effect of high audit quality can be strengthened by auditor experience, the title of “senior auditor” and IPO auditing experience. We also show that clients and audit firms place more weight on the quality of audits conducted by auditors in competitive markets and auditors with engagements matched with industries.

Together, these findings indicate the vital role of individual audit quality in auditors’ career development in the audit labour market, consistent with the reputation rationale for audit quality.

This study investigates the relationship between CEO leadership, gender homophily and corporate environmental, social and governance (ESG) performance. We also investigate whether it is essential to have a critical mass of women directors on the board to create a significant power of gender diversity in leadership positions.

Our study is based on firms listed on the London Stock Exchange (FTSE-All-Share) from 2011 to 2019. CEO characteristics and other board variables were collected from BoardEx, and ESG data, and other related variables were collected from Eikon database.

We find a critical mass of female directors contributes to ESG performance suggesting that token representation of female directors on boards limits their effectiveness. We do not find support for the gender homophily perspective, our findings suggest that the effectiveness of female CEOs does not depend on the existence of a critical mass of female directors. Female directors and female CEOs are less likely to be associated with ESG activities when firms experience poor financial performance. We also find that younger female CEOs have a positive impact on ESG performance. Furthermore, we find female CEOs with shorter tenure are more likely to improve ESG performance. Overall, our findings suggest a substitutional effect between having female CEOs and gender diverse boards.

This study contributes to the debate on gender homophily in the boardroom and how that may affect ESG practices. It also complements existing academic research on female leadership and ESG performance and has important implications for senior management and policymakers.