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In the last few years, environmental issues have become a matter of survival. In this sense, e-waste management is among the major problems since it may be a way of mitigating mineral depletion. In this context, the literature lacks e-waste supply chain studies that systematically map supply chain challenges and risks concerning material recovery.

Given this context, the authors' paper conducted a systematic literature review (SLR) to build a framework to identify the constructs of e-waste supply chain risk management.

The paper revealed the theoretical relationship between important variables to achieve e-waste supply chain risk management via a circular economy (CE) framework. These variables include reverse logistics (RL), closed-loop supply chains (CLSC), supply chain risk management, supply chain resilience and smart cities.

The literature contributions of this paper are as follows: (1) a complete list of the risks of the e-waste supply chains, (2) the techniques being used to identify, assess and mitigate e-waste supply chain risks and (3) the constructs that form the theoretical framework of e-waste supply chain risk management. In addition, the authors' results address important literature gaps identified by researchers and serve as a guide to implementation.

This paper aims to investigate the following issues: the mechanisms through which different types of top management team’s social capital influence the innovation quality of high-tech firms, and the moderating effect of organizational knowledge utilization on the relationship between top management team’s social capital and innovation quality in high-tech firms.

This study categorizes top management team’s social capital into political, business and academic dimensions, investigating their impact on innovation quality in high-tech firms. Furthermore, a research model is developed with organizational knowledge utilization as the moderating variable. Data from Chinese high-tech firms between 2010 and 2019 are collected as samples for analysis.

The innovation quality of high-tech firms shows an inverted U-shaped trend as the top management team’s political capital and business capital increase. The top management team’s academic capital has a significantly positive correlation with the innovation quality of high-tech firms. Moreover, organizational knowledge utilization plays a significant moderating role in the relationship between the top management team’s social capital and innovation quality in high-tech firms.

This study explores the relationship among different dimensions of top management team’s social capital, innovation quality and organizational knowledge utilization. It holds significant theoretical value in enriching and refining the interactions between top management team’s social capital, knowledge management theory and innovation management theory. In addition, it offers important practical implications for firms to rationally approach top management team’s social capital, emphasize top management team configuration management and establish a comprehensive and efficient organizational knowledge utilization mechanism.

In the era of the digital economy, higher demands are placed on versatile talents, and the cultivation of students with innovative and entrepreneurial abilities has become an important issue for the further development of higher education, thus leading to extensive and in-depth research by many scholars. The study summarizes the characteristics and patterns of dual-innovation education at different stages of development, hoping to provide a systematic model for the development of dual-innovation education in China and make up for the shortcomings.

This paper uses Citespace software to visualize and analyze the relevant literature in CNKI and Web of Science databases from a bibliometric perspective, focusing on quantitative analysis in terms of article trends, topic clustering, keyword co-linear networks and topic time evolution, etc., to summarize and sort out the development of innovation and entrepreneurship education research at home and abroad.

The study found that the external characteristics of the literature published in the field of bi-innovation education in China and abroad are slightly different, mainly in that foreign publishers are more closely connected and have formed a more stable ecosystem. In terms of research hotspots, China is still in a critical period of reforming its curriculum and teaching model, and research on the integration of specialization and creative education is in full swing, while foreign countries focus more on the cultivation of students' entrepreneurial awareness and the enhancement of individual effectiveness. In terms of cutting-edge analysis, the main research directions in China are “creative education”, “new engineering”, “integration of industry and education” and “rural revitalization”.

Innovation and entrepreneurship education in China is still in its infancy, and most of the studies lack an overall overview and comparison of foreign studies. Based on the econometric analysis of domestic and foreign literature, this paper proposes a path for domestic innovation and entrepreneurship education reform that can make China's future education reform more effective.

This study aims to examine the impact of board characteristics on firm performance while also exploring the influential mechanisms that help Chinese listed companies establish effective boards of directors and strengthen their corporate governance mechanisms.

This paper uses machine learning methods to investigate the predictive ability of the board of directors' characteristics on firm performance based on the data from Chinese A-share listed companies on the Shanghai and Shenzhen stock exchanges in China during 2008–2021. This study further analyzes board characteristics with relatively strong predictive ability and their predictive models on firm performance.

The results show that nonlinear machine learning methods are more effective than traditional linear models in analyzing the impact of board characteristics on Chinese firm performance. Among the series characteristics of the board of directors, the contribution ratio in prediction from directors compensation, director shareholding ratio, the average age of directors and directors' educational level are significant, and these characteristics have a roughly nonlinear correlation to the prediction of firm performance; the improvement of the predictive ability of board characteristics on firm performance in state-owned enterprises in China performs better than that in private enterprises.

The findings of this study provide valuable suggestions for enriching the theory of board governance, strengthening board construction and optimizing the effectiveness of board governance. Furthermore, these impacts can serve as a valuable reference for board construction and selection, aiding in the rational selection of boards to establish an efficient and high-performing board of directors.

The study findings unequivocally demonstrate the superiority of nonlinear machine learning approaches over traditional linear models in examining the relationship between board characteristics and firm performance in China. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. The study reveals that the predictive performance of board attributes is generally more robust for state-owned enterprises in China in comparison to their counterparts in the private sector.

In this study, solid formaldehyde, benzoguanamine and butanol were used to synthesize butylated benzo-amino resin by one-step-two-stage method.

This research first examined the influence of solid formaldehyde content on the hydroxymethylation phase. Subsequently, the effects of butanol content, etherification time and hydrochloric acid content on the formation of benzo-amino resin during the etherification stage were studied in detail. In addition, the reaction process was further analyzed through interval sampling withdrawing during the hydroxymethylation and etherification stages. Finally, the synthesized benzo-amino resins were used in the production of high solid content polyester and acrylic coatings and the properties of that were also evaluated.

Based on the experimental findings, the authors have successfully determined the optimal process conditions for the one-step-two-stage method in this study. The hydroxymethylation stage demonstrated the most favorable outcomes at a reaction temperature of 60°C and a pH of 8.5. Similarly, for the etherification stage, the optimal conditions were achieved at a temperature of 45°C and a pH of 4.5. Furthermore, the investigation revealed that a ratio of benzoguanamine to solid formaldehyde to n-butanol, specifically at 1:5.2:15, produced the best results. The performance of the resulting etherified benzo-amino resin was thoroughly evaluated in high solid content coatings, and it exhibited promising characteristics. Notably, there was a significant enhancement in the water resistance, solvent resistance and glossiness of canned iron printing varnish coatings.

Amino resin, a versatile chemical compound widely used in various industries, presents challenges in terms of sustainability and operational efficiency when synthesized using conventional methods, primarily relying on a 37% formaldehyde solution. To address these challenges, the authors propose a novel approach in this study that combines the advantages of the solid formaldehyde with a two-stage catalytic one-step synthesis process. The primary objective of this research is to minimize the environmental impact associated with amino resin synthesis, optimize resource utilization and enhance the economic feasibility for its industrial implementation. By adopting this alternative approach, the authors aim to contribute toward a more sustainable and efficient production of amino resin.

Prefabricated construction (PC) is increasingly recognized for its sustainability and is being vigorously promoted worldwide. However, its adoption in developing countries remains suboptimal, with existing studies predominantly focusing on policy frameworks or the impact of a single policy instrument. This study addresses this research gap by optimizing the path of PC promotion from the perspective of policy mixes.

The study employs fuzzy-set qualitative comparative analysis (fsQCA) in conjunction with necessary condition analysis, to explore effective policy configurations for PC promotion. A comprehensive collection of 171 PC-related policies issued by the Chinese government was analyzed using text mining to identify antecedent conditions of configuration. Data were further obtained through a questionnaire survey involving 263 valid responses, with fsQCA used to derive the optimal policy configurations.

The analysis identified six distinct combination paths for effective policy configurations. Land supply and governmental procurement were found to be core conditions, while fiscal and taxation financial measures emerged as marginal conditions prevalent across all paths. These findings suggest that land supply policies are particularly suitable for regions with limited land resources, such as Shanghai, while government procurement is more effective in regions like Xinjiang, where PC awareness is still developing.

In practice, the conclusions enable policymakers to clearly understand policy instruments, thereby finding differentiated pathways for promoting PC with comparable effects. The proposed recommendations help advance PC development effectively while reducing financial burden and minimizing resource waste. This provides important guidance for PC development across different regions or stages, helps address regional imbalances in PC development, and ultimately contributes to the broader goal of sustainable urban development.

This study significantly enriches the research on PC policy combinations by utilizing more comprehensive and robust data, thereby enhancing the universal applicability of the findings. The results provide valuable references for policymakers in different regions, helping to address regional imbalances in PC development and facilitating the construction industry’s transition towards greater intelligence and sustainability.

We investigate the joint impacts of three trust cues – content, sentiment and helpfulness votes – of online product reviews on the trust of reviews and attitude toward the product/service reviewed.

We performed three studies to test our research model, presenting participants with scenarios involving product reviews and prior users' helpful and unhelpful votes across experimental settings.

A high helpfulness ratio boosts users’ trust and influences behaviors in both positive and negative reviews. This effect is more pronounced in attribute-based reviews than emotion-based ones. Unlike the ratio effect, helpfulness magnitude significantly impacts only negative attribute-based reviews.

Future research should investigate voting systems in various online contexts, such as Facebook post likes, Twitter microblog thumb-ups and up-votes for article comments on platforms like The New York Times.

Our findings have significant implications for voting system-providers implementing information techniques on third-party review platforms, participatory sites emphasizing user-generated content and online retailers prioritizing product awareness and reputation.

This study addresses an identified need; that is, the helpfulness votes as an additional trust cue and the joint effects of three trust cues – content, sentiment and helpfulness votes – of online product reviews on the trust of customers in reviews and their consequential attitude toward the product/service reviewed.

Companies increasingly leverage artificial intelligence (AI) to enhance human performance, particularly in e-commerce. However, the effectiveness of AI augmentation remains controversial. This study investigates whether, how and why AI enhances human agents’ sales through a randomized field experiment.

This study conducts a two-by-two factorial randomized field experiment (N = 1,090) to investigate the effects of AI augmentation on sales. The experiment compares sales outcomes handled solely by human agents with those augmented by AI, while also examining the moderating effect of agents’ experience levels and the underlying mechanisms behind agents’ responses.

The results reveal that AI augmentation leads to a significant 5.46% increase in sales. Notably, the impact of AI augmentation varies based on agents’ experience levels, with inexperienced agents benefiting nearly six times more than their experienced counterparts. Mediation analysis shows that AI augmentation improves response timeliness, accuracy and sentiment, thereby boosting sales.

This study highlights the role of AI augmentation in human–AI collaboration, demonstrates the varying impacts of AI augmentation based on agents’ experience levels and offers insights for organizations on how to regulate AI augmentation to enhance agent responses and drive sales.

Mental health issues negatively affect employees’ quality of life and employers’ bottom line. Consequently, ensuring well-being in the workplace is becoming a high priority from a strategic human resource management perspective. Drawing on basic psychological needs theory, we propose that proactive personality will be related to mental well-being through satisfaction of basic psychological needs. In addition, drawing on the trait-by-trait interactions perspective, we expect the mediated relationship to be moderated by conscientiousness.

We tested our research model using data collected from 185 employees using a three-wave time-lagged design.

Proactive personality related to mental well-being indirectly, via psychological need satisfaction, and this indirect relationship was stronger at higher levels of conscientiousness.

Ensuring mental well-being of employees is critical to achieving a competitive advantage. Support for the mediating role of need satisfaction suggests that organizations can tailor interventions aimed at influencing the more malleable mediating variable, psychological need satisfaction, compared to relatively stable personality traits.

We contribute to theory by testing a theoretical explanation for how and why personality affects mental well-being. Another theoretical contribution is demonstrating that mental well-being results from a combination of personality traits, with a trait-by-trait perspective fitting the data better than an unconditional trait model.

Safety management is a key point and poses a challenge in joint testing. To detect and address potential accidents' hidden dangers early, this paper conducts research on the safety control technology for high-speed railway joint tests by incorporating the concept of hazardous events.

Aiming at ensuring the safety of high-speed railway combined inspections and trials, this paper starts from the dual prevention mechanism. It introduces the concept of threatening events, defines them and analyzes the differences between threatening events and railway accidents. The paper also proposes a cause model for threatening events in high-speed railway combined inspections and trials, based on three types of hazard sources. Furthermore, it conducts research on the control strategies for these threatening events.

The research on safety control technology for high-speed railway combined operation and testing, based on the analysis of threatened events, offers a new perspective for safety management in these operations. It also provides theoretical and practical support for the transition from passive prevention to active risk pre-control, which holds significant theoretical and practical value.

The innovation mainly includes the following three aspects: (1) Building on the traditional dual prevention mechanism, which includes risk hierarchical management and control as well as hidden danger investigation and management, a triple prevention mechanism is proposed. This new mechanism adds the management of threatening events as the third line of defense. The aim is to more comprehensively identify and address potential security risks, thereby enhancing the efficiency and effectiveness of security management. (2) In this paper, the definition of a railway threatening event is clarified, and the causative model of a high-speed railway threatening event based on three kinds of danger sources is proposed. (3) This paper puts forward the control strategy of the high-speed railway combined operation and trial, which includes five key links: identification, reporting, analysis, rectification and feedback, which provides a new perspective for the safety management of the high-speed railway combined operation and trial and has important theoretical and application value.