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The rapid development of information technology, epitomized by AIGC and the metaverse, presents unprecedented challenges to techno-ethics, exposing society to significant risks and uncertainties. A systematic investigation and discussion of the construction of techno-ethical order become crucial under the paradigm of risk society theory. The selection of conditions and pathways for constructing a techno-ethical order under the risk society theory paradigm becomes an unavoidable and vital issue.

Drawing on risk society theory, this study employs scientometrics and qualitative comparative analysis (QCA) to empirically analyze the key factors and conditional pathways in the construction of techno-ethical order. Initially, a quantitative analysis is conducted on 1,490 thematic literature retrieved from CNKI and WoS to identify the hot topics and core concepts in techno-ethical research. Subsequently, QCA configuration analysis is applied to calculate eight evaluation indicators and their weights from the perspectives of government, society and individuals. Finally, the study explores the mechanisms of the impact of these indicators’ weights on the construction of techno-ethical order.

The analysis of factor weights and pathways indicates that the selection of pathways for constructing techno-ethical order is influenced both by the inherent development patterns of technology and societal systems and cultural values. Literature metrics analysis reveals an overall trend of sustained growth in techno-ethical research, indicating an unprecedented prosperity in this field. Alongside technological advancements, keywords related to “artificial intelligence” play a crucial role in current techno-ethical research. Configuration analysis demonstrates that conditional variables from the dimensions of government, society and individuals form a configuration pathway, influencing and synergistically impacting the overall level of techno-ethical order construction. Attention should be given to the mutual constraints and synergistic effects of factors related to technological development, societal systems and cultural values.

This study, grounded in the risk society theory paradigm, quantitatively explores the key factors and pathways of techno-ethical order construction in academic texts, expanding new perspectives, providing novel insights, establishing innovative methodologies and extending new boundaries in the field. Further enrichment of the dataset and in-depth discussions are warranted for continued advancement.

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 paper aims to investigate the interconnectedness of redenomination risk premiums across the four main European sovereign bond markets (France, Germany, Italy and the Netherlands).

The authors used the time-varying parameter vector autoregressions method to achieve the objectives.

This study reveals that the redenomination risk connectedness throughout the Euro area sovereign bond markets is dynamic and exhibits remarkable variations across various crisis episodes, such as the COVID-19 pandemic and Russia–Ukraine tensions. In addition, the analysis uncovers significant bilateral connections between countries. Furthermore, the research finds that spillovers from the US dollar redenomination premium (USDRP) are greater than those from the euro redenomination premium (ERP) and currency redenomination premium (CRP). However, during the Ukraine–Russia tensions, the connectedness between the USDRP is stronger than that between the ERP and CRP. On the other hand, the connectedness between CRP is higher than the USDRP and ERP during the COVID-19 pandemic. Importantly, this study demonstrates that the four countries play a role as both shock transmitters and receivers, switching alternatively.

This study contributes to the related literature by exploring the redenomination risk connectedness throughout the Euro area sovereign bond markets. Specifically, we rely on the USDRP, the ERP and CRP. These findings have serious implications for both portfolio risk management.

Previous research has predominantly concentrated on examining risk spillovers through single-layer networks, neglecting the multi-related and multilayer network characteristics of the economic system. This study constructs multilayer connectedness networks, including return, volatility and extreme risk layers, to systematically analyze the risk spillovers across Chinese industries at the system and industry levels.

Previous studies have constructed multilayer networks using Diebold and Yilmaz’s (2012) approach or the time-varying parameter vector autoregressive (TVP-VAR) connectedness model. In this study, we employ the TVP-VAR-extended joint connectedness approach, which improves these methods and captures risk spillovers more accurately.

At the system level, the risk spillover across industries exhibits distinct network structures and dynamic evolution behaviors across different layers. During extreme events, the intensity, scope and speed of risk spillovers increase markedly across all layers, with volatility and extreme risk layers demonstrating greater sensitivity to crises. At the industry level, industrial and optional consumption typically serve as risk transmitters, while medicine and health, as well as financial real estate, tend to be risk receivers across three layers. Moreover, industrial, optional consumption and materials exhibit significant systemic importance.

To the best of our knowledge, this is the first study to apply multilayer networks with return, volatility and extreme risk layers to systematically examine risk spillovers between Chinese industries.

The purpose of this paper is to identify the historical trends and status of the national development of artificial intelligence (AI) from a nationwide perspective and to enable governments at different administrative levels to promote AI development through policymaking.

This paper analyzed 248 Chinese AI policies (36 issued by the state agencies and 212 by the regional agencies). Policy bibliometrics, policy instruments and network analysis were used to reveal the AI policy patterns. Three aspects were analyzed: the spatiotemporal distribution of issued policies, the policy foci and instruments of policy contents and the cooperation and citation among policy-issuing agencies.

Results indicate that Chinese AI development is still in the initial phase. During the policymaking processes, the state and regional policy foci have strong consistency; however, the coordination among state and regional agencies is supposed to be strengthened. According to the issuing time of AI policies, Chinese AI development is in accordance with the global situation and has witnessed unprecedented growth in the last five years. And the coastal provinces have issued more targeted policies than the middle and western provinces. Governments at the state and regional levels have emphasized familiar policy foci and played the role of policymakers, along with regional governments that also functioned as policy executors as well. According to the three-dimension instruments coding, the authors found an uneven structure of policy instruments at both levels. Furthermore, weak cooperation appears at the state level, while little cooperation is found among regional agencies. Regional governments cite state policies, thus leading to the formation of top-down diffusion, lacking bottom-up diffusion.

The paper contributes to the literature by characterizing policy patterns from both external attributes and semantic contents, thus revealing features of policy distribution, contents and agencies. What is more, this research analyzes Chinese AI policies from a nationwide perspective, which contributes to clarifying the overall status and multi-level relationships of policies. The findings also benefit the coordinated development of governments during further policymaking processes.

This study aims to investigate the effects of thermal buoyancy and flow incidence angles on mixed convection heat transfer and vortex-induced vibration (VIV) of an elastically mounted circular cylinder. The focus is on understanding how varying these parameters influences the vibration amplitudes in both the x and y directions and the overall heat transfer performance.

The research involves a numerical simulation of thermal fluid-structure interactions by integrating rigid-body motion equations with heat and fluid flow solvers. The cylinder operates at a lower temperature than the mainstream flow, and flow incidence angles range from 0° (opposing gravity) to 90° (perpendicular to gravity). The methodology is validated by comparing the results with established data on VIV for a cylinder vibrating in one direction under thermal buoyancy effects.

The study reveals that, without buoyancy (Ri = 0), increasing the flow angle from 0° to 90° decreases the vibration amplitude along the x-direction (A_x) while increasing it along the y-direction (A_y) across various reduced velocities (U_r). When buoyancy effects are introduced (Ri = −1), A_x peaks at specific U_r values depending on the flow angle, with significant variations observed. The maximum increase in A_x at Ri = −1 is over 15 times at U_r = 9 for a 0° angle, and A_y shows a more than 10-fold increase at U_r = 8 for a 30° angle. Additionally, adjusting the flow angle results in up to an 8% increase in the mean Nusselt number at Ri = −1.

This research provides novel insights into the combined effects of flow incidence angles and thermal buoyancy on VIV and heat transfer in an elastically mounted cylinder.

The purpose of this study is to theoretically hypothesise and empirically explore the relationships between operations and supply chain management (O&SCM) and marketing/sales (OMS) collaboration, social media (SM) usage, organisational resilience and performance. This paper considers how collaboration through SM can enhance organisational resilience capability and performance.

A survey was conducted among 395 organisations in the UK. Structural equation modelling was applied to test the research hypotheses.

The empirical findings of this study support the significant mediating role of O&SCM–OMS collaborative activities through internal and external SM for better organisational resilience, capability, cost efficiency, customer-focused and business performance. This also extends to exploring differences based on product versus service industries.

Through empirical research, the findings contribute to the theoretical development and managerial guidance on O&SCM–OMS collaboration and resilience capability by emphasising the strategic deployment of SM across functions through the lens of contingency theory and resource-based view.

This study aims to evaluate and synthesize literature on exoskeleton implementation in the construction industry to understand their current applications, evaluate existing research approaches and identify critical areas for future investigation. Through a comprehensive analysis of empirical studies, the research seeks to establish a clear roadmap for advancing exoskeleton adoption in construction work.

This study conducts a systematic literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. By searching relevant databases and applying predefined inclusion criteria, the review focused on empirical studies that evaluate the effectiveness and acceptance of exoskeletons in construction. Both objective parameters (EMG data, Kinematic analysis, heart rate) and subjective parameters (user comfort, perceived exertion, usability surveys) were analyzed to assess how impactful are exoskeletons among construction workers.

The review identified 236 publications, of which 36 were included, revealing several critical insights: (1) A significant reliance on studies conducted in controlled environments, accounting for 77.78% of studies. (2) A limited representation of actual construction workers, mainly non-construction worker volunteers, which may affect the practical relevance of the findings. (3) A significant gap exists in standardized evaluation protocols, with researchers using varying assessment methods that hinder cross-study comparisons. (4) Predominantly short-term nature of existing studies. These findings highlight the need for more real-world testing, standardized evaluation frameworks and longitudinal studies.

This review contributes original insights into the deployment of exoskeletons in the construction sector, particularly highlighting the industry's gap in direct, in situ engagement with construction workers. It suggests that future research should prioritize long-term, onsite studies to achieve a more comprehensive understanding of exoskeletons’ impacts, thus supporting the development of targeted intervention strategies for reducing work-related musculoskeletal disorders (WMSDs) among construction workers.

Previous research mainly uses graph neural networks on syntactic dependency graphs, often neglecting emotional cues in sarcasm detection and failing to integrate image features for multimodal information effectively. To address these limitations, this study proposes a novel multimodal sarcasm detection model based on the directed graph isomorphism network with sentiment enhancement and multimodal fusion (DGIN-SE-MF).

The approach extracts image and text features through vision transformer and BERT, respectively. To deeply integrate the extracted features, the author develops a text-guided multi-head attention fusion mechanism module. Subsequently, a directed graph is constructed through SE and the multimodal factorized bilinear pooling method to integrate image features into the graph. The DGIN then fuses the image and text features, using a weighted attention mechanism to generate the final representation.

The model is validated on three datasets: English, Chinese and an Indonesian–English dataset. The results demonstrate that the proposed model consistently outperforms other baseline models, particularly on the Chinese and English sarcasm datasets, achieving F1 scores of 88.75 % and 83.10 %, respectively.

The proposed model addresses the inadequacies of previous methods by effectively integrating emotional cues and image features into sarcasm detection. To the best of the authors’ knowledge, this is the first work to leverage a DGIN-SE-MF for this task, leading to significant improvements in detection performance across different languages.