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This paper examines the effect of managerial interlocking networks (MINs) on firm risk spillover by using a sample of Chinese A-share listed firms.

Applying the complex network approach, we build managerial interlocking networks (MINs) and leverage degree centrality to quantify a manager’s network position. To gauge firm risk spillover, we utilize the conditional autoregressive value at risk (CAViaR) model to compute the value-at-risk. Subsequently, we employ ordinary least squares to investigate the influence of MINs on firm risk spillover.

Our research uncovers a direct correlation between a firm risk spillover and the status of network positions within managerial interlocking networks; namely, the more central the position, the greater the risk spillover. This increase is believed to be due to central firms in MINs having greater connectedness and influence. This fosters a similarity in decision-making across different firms through interfirm managerial communication, thus amplifying the risk spillover. Economic policy uncertainty (EPU) and Guanxi culture furtherly intensify the effects of MINs. Additional analysis reveals that the impact of MINs on the firm risk spillover is significantly noticeable in non-state-owned enterprises, while good corporate governance diminishes the risk spillover prompted by MINs.

Our findings offer fresh insights into the interfirm risk outcome associated with MINs and extend practical guidelines for attenuating firm risk spillover with a view toward mitigating systemic risk.

The combination of improved PSO (IPSO) algorithm and artificial neural network (ANN) model for intelligent monitoring of the bearing performance of the hydrostatic turntable.

This paper proposes an artificial neural network model based on IPSO algorithm for intelligent monitoring of hydrostatic turntables.

The theoretical model proposed in this paper improves the accuracy of the working performance of the static pressure turntable and provides a new direction for intelligent monitoring of the static pressure turntable. Therefore, the theoretical research in this paper is novel.

Theoretical novelties: an ANN model based on the IPSO algorithm is designed to monitor the load-bearing performance of a static pressure turntable intelligently; this study show that the convergence accuracy and convergence speed of the IPSO-NN model have been improved by 52.55% and 10%, respectively, compared to traditional training models; and the proposed model could be used to solve the multidimensional nonlinear problem in the intelligent monitoring of hydrostatic turntables.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2024-0081/

With increasing complexity of construction projects and new construction processes and methods are adopted, more safety hazards are emerging at construction sites, requiring the application of the modern risk management methods. As an emerging technology, digital twin has already made valuable contributions to safety risk management in many fields. Therefore, exploring the application of digital twin technology in construction safety risk management is of great significance. The purpose of this study is to explore the current research status and application potential of digital twin technology in construction safety risk management.

This study followed a four-stage literature processing approach as outlined in the systematic literature review procedure guidelines. It then combined the quantitative analysis tools and qualitative analysis methods to organize and summarize the current research status of digital twin technology in the field of construction safety risk management, analyze the application of digital twin technology in construction safety risk management and identify future research trends.

The research findings indicate that the application of digital twin technology in the field of construction safety risk management is still in its early stages. Based on the results of the literature analysis, this paper summarizes five aspects of digital twin technology's application in construction safety risk management: real-time monitoring and early warning, safety risk prediction and assessment, accident simulation and emergency response, safety risk management decision support and safety training and education. It also proposes future research trends based on the current research challenges.

This study provides valuable references for the extended application of digital twin technology and offers a new perspective and approach for modern construction safety risk management. It contributes to the enhancement of the theoretical framework for construction safety risk management and the improvement of on-site construction safety.

Although the literature recognizes that coopetition plays a significant role in the success of international construction joint ventures (ICJVs), the impacts of coopetition on the performance outcomes of ICJVs remain largely unknown. This study extends this line of research by theorizing coopetition from three dimensions, i.e. coopetition intensity, coopetition balance and coopetition structure, and examining the relationships between coopetition and ICJV performance outcomes from both the contingency and configuration perspectives.

The hypotheses were tested using survey data from a sample of 188 ICJVs. Structural equation modelling was employed for the contingency approach to estimate the relationships between the three dimensions of coopetition and performance. For the configuration approach, cluster analysis was utilized to identify coopetition patterns. Subsequently, an analysis of variance was employed to analyse the relationships between these coopetition patterns and performance.

The contingency results indicate that while coopetition intensity is positively related to all types of performance, coopetition balance is only positively related to project performance and partner performance. Moreover, coopetition structure is only related to partner performance and socioenvironmental performance. The configuration approach identifies six patterns of coopetition, manifesting different levels of project, partner and socioenvironmental performance.

These findings, therefore, contribute to the ICJV literature by extending the understanding of how coopetition dimensions individually and jointly influence ICJV performance.

The purpose of this study is to investigate the impact of digital agricultural insurance on farmers’ fertilizer reduction technology adoption and explain its main mechanisms, as well as to reveal the heterogeneity of the impact with regard to the production scale and crop type.

Using the dataset of CHFS-SCAU2021, this study empirically examines the impact of digital agricultural insurance on farmers’ fertilizer reduction technology adoption by Probit model and employ instrumental variables and treatment effect model to address the potential endogeneity bias.

(1) Digital agricultural insurance can significantly improve farmers’ fertilizer reduction technology adoption and (2) it has a greater promoting effect on the adoption of fertilizer reduction technology compared to traditional agricultural insurance, which still holds after correction of endogeneity bias. (3) Digital agricultural insurance can help promote farmers’ fertilizer reduction technology adoption through decreasing risk aversion, information asymmetry and alleviating financial constraint, while (4) it can only promote the fertilizer reduction technology adoption among large-scale and grain-crop farmers currently.

(1) This study is the first to empirically examine the causal impact of digital agricultural insurance on farmers fertilizer reduction technology adoption. (2) This study construct a comprehensive framework to explain the main mechanisms through which digital agricultural insurance influences farmers fertilizer reduction technology adoption both theoretically and empirically. (3) It also compares the disparities between traditional agricultural insurance and digital agricultural insurance in terms of influence on farmers’ fertilizer reduction technology adoption and proposes the relative recommendations on digital agricultural insurance to help improve farmers’ willingness and behavior of fertilizer reduction technology adoption to promote extension efficiency.

This study aims to investigate the impact of corporate social responsibility (CSR) on green innovation by considering the three dimensions of green innovation cognition, behavior and outcomes and to explore the role of situational and measurement factors in this relationship.

This study adopts a meta-analysis method to integrate 208,997 observations from 48 independent empirical studies on CSR and green innovation.

CSR positively affects green innovation cognition, behavior and outcomes. Additionally, the relationship between CSR and green innovation is stronger in Western cultural background than in Eastern ones. The impact of CSR on green innovation is also more significant in small and medium-sized enterprises (SMEs). Moreover, this study shows that the correlation between CSR and green innovation is stronger when the source of data is primary data and when green innovation is measured by non-patent methodologies.

This study elucidates the impact of CSR on green innovation and further clarifies the potential reasons for the divergent findings in existing related studies. The article enriches the theoretical results related to CSR and green innovation and provides valuable insights and references for corporate decision-makers.

We aim to provide a systematic literature review of the determinants and consequences of labor investment efficiency in an international context. First, we offer a theoretical discussion of labor investment efficiency, followed by an examination of its measurement. Next, we review the determinants of labor investment efficiency, categorizing them into firm fundamentals including financial reporting quality, governance and controls, corporate social responsibility/environmental regulation and macroeconomic determinants. Finally, we review the limited empirical literature on the consequences of labor investment efficiency. We also provide some suggestions for future research.

We perform a systematic literature review using the Preferred Reporting Items for a Systematic Review of Meta-Analysis (PRISMA) guidelines to examine archival studies investigating the determinants and consequences of labor investment efficiency. Using a Boolean search strategy on the Scopus and PRISMA selection criteria, we review 86 published archival research articles from 2014 to the end of August 2024.

Our review highlights that firm-level fundamental factors including financial reporting quality have profound implications for labor investment efficiency. Effective governance mechanisms also help mitigate agency conflicts and information asymmetries and alleviate labor investment inefficiencies. Furthermore, the influence of regulations including ESG-related regulations and macroeconomic factors play a crucial role in shaping labor investment decisions. We find very little research on the consequence of labor investment efficiency.

Our review has highlighted that well-functioning corporate governance tools are effective in mitigating inefficient labor investments. Stakeholders, therefore, should ensure that firms have effective internal governance mechanisms in place and that external governance regulations complement and where necessary act as substitutes for internal governance mechanisms to optimize labor investments.

To the best of our knowledge, this study represents the first systematic review of extant research on labor investment efficiency. Our review highlights some research gaps, particularly about the consequences of labor investment efficiency and offers some suggestions for future research.

Damage to the pipe structure and increased bolt stress in operating tunnels will significantly affect the long-term stability of shield tunnels. However, due to the large number of segments and complex bolt installation methods, it is difficult to directly obtain the conditions of segments and bolts. Convergence deformation, as an important indicator for the health assessment of operating tunnels, is easy to collect and can directly reflect the structural state of tunnel segments and bolts.

Taking the typical sections of Hangzhou Metro Line 1 and Line 3 as an example, the current structural damage is simulated by monitoring tunnel convergence deformation. First, based on the disease data, the relationship between convergence deformation and segment leakage, segment misalignment as well as the longitudinal joint opening between two segments is analyzed statistically. The stress of bolts, steel bars and segments under different convergence deformations is simulated by Midas. Then a reinforcement measure of circumferential internal tension steel rings is proposed.

It is found that when the segment convergence exceeds 85 mm, although the overall force on the segment has not reached the material limit, there are certain safety risks in the structure. After comparison, the reinforcement measure has a relatively significant effect on controlling the lateral deformation of segments.

The results have important guiding significance for the evaluation of structural diseases, early warning and control of structural diseases at different convergence deformations.

During the COVID-19 pandemic, an infodemic erupted on social media, leading to a surge in negative disclosure behaviors such as expressing dissatisfaction and releasing negative emotions. By extending the elaboration likelihood model and the Big Five personality theory to the domain of online self-disclosure, we aimed to identify the factors that influence negative disclosure behavior.

We investigated how the features of negative information content, information sources and recipients’ social perceptions influence how social media users disclose negative information. We also examined the moderating roles of personality traits in this process. To validate the model and test our hypotheses, we collected cross-sectional data from 456 social media users.

Empirical results reveal that (1) information overload, topic relevance, attractiveness of information sources, peer approval of negative disclosure and social influence on negative information strengthen the intention to disclose negative information. (2) The perception of social risk weakens the intention to disclose negative information. (3) Openness to experience, extraversion and neuroticism strengthen the relationship between the intention to disclose negative information and actual disclosure behavior.

Our results not only provide new perspectives on the decision-making mechanisms behind negative disclosure behavior but also extend personality research within the context of the dissemination of negative information. Furthermore, it offers insights into negative information dissemination on social media platforms, with significant implications for various stakeholders.

This study aims to investigate the relationship between individual-level psychological resources and team resilience in the context of expatriate project management teams. It seeks to understand how personal psychological resources contribute to team resilience and explore the dynamic evolution mechanism of team resilience. The goal is to enhance team resilience among expatriates in a BANI (Brittle, Anxious, Nonlinear, and Incomprehensible) world, where organizations face volatile and uncertain conditions.

An online survey was applied for data collection, and 315 valid samples from Chinese expatriates in international construction projects were utilized for data analysis. A structural equation model (SEM) examines the relationships between personal psychological resources and team resilience. The study identifies five psychological factors influencing team resilience: Employee Resilience, Cross-cultural Adjustment, Self-efficacy, Social Support, and Team Climate. The hypothesized relationships are validated through the SEM analysis. Additionally, a fuzzy cognitive map (FCM) is constructed to explore the dynamic mechanism of team resilience formation based on the results of the SEM.

The SEM analysis confirms that employee resilience, cross-cultural adjustment, and team climate positively impact team resilience. Social support and self-efficacy also have positive effects on team climate. Moreover, team climate is found to fully mediate the relationship between self-efficacy and team resilience, as well as between social support and team resilience. The FCM model provides further insights into the dynamic evolution of team resilience, highlighting the varying impact effects of antecedents during the team resilience development process and the effectiveness of different combinations of intervention strategies.

This study contributes to understanding team resilience by identifying the psychological factors influencing team resilience in expatriate project management teams. The findings emphasize the importance of social support and team climate in promoting team resilience. Interventions targeting team climate are found to facilitate the rapid development of team resilience. In contrast, interventions for social support are necessary for sustainable, long-term high levels of team resilience. Based on the dynamic simulation results, strategies for cultivating team resilience through external intervention and internal adjustment are proposed, focusing on social support and team climate. Implementing these strategies can enhance project management team resilience and improve the core competitiveness of contractors in the BANI era.