Jianjia He

Addressing China’s emergency industry challenges—supply–demand imbalances and insufficient long-term development under the “phased emergency” paradigm amidst frequent sudden disasters—this study innovatively constructed a scenario supply and demand network model driven by the Internet of Things technology, taking public health emergency events as a typical scenario to identify potential demand. The Internet of Things provides dynamic information support for the supply and demand network by collecting emergency materials, equipment, and personnel status data in real time, improving the network’s responsiveness and transparency. This model bridges emergency needs with industrial supply capabilities and incorporates complex network analysis to reveal structural patterns, facilitating the industry’s shift toward a “normalized and sustainable” model. Results demonstrate that the public health emergency-based supply–demand network exhibits characteristics of a resilient network, possessing certain risk resilience. Node-disruption simulations uniquely reveal the nonlinear dynamics of network resilience and pinpoint critical thresholds essential for maintaining systemreliability and recovery capacity. These findings emphasize the importance of preemptive intervention during critical periods and protecting key nodes in the emergency supply chain, and highlight the key role of Internet of Things technology in improving the resilience of the supply and demand network of the emergency industry.

As labour costs in China increase, labour-intensive industries are migrating to ASEAN countries, attracted by lower labour costs and market potential. This shift not only affects the economies of China and ASEAN but also reshapes the global manufacturing landscape. This paper investigates the correlation and spillover of supply chain risks using production exposure indicators derived from inter-country input-output data and the R-Vine Copula model. We assess the risk spillover of each country within the global supply chain. Our findings indicate that industrial relocation can significantly alter supply chain structures, thereby affecting the concentration and direction of risks. While China's role in the global textile supply chain has diminished, it remains significant, with notable increases in the roles of Vietnam and Thailand. This research reveals the supply chain risks between China and ASEAN in the context of industrial transfer, exploring the sustainable development of production linkages and sustainable economic cooperation among countries.

The 3D printing cloud platform (3DPCP) plays a pivotal role in breaking down the information silos between supply and demand, effectively reducing waste through information integration and intelligent production. However, due to the complexity of 3DPCP scheduling in green scenes and the multidynamic information perturbations, unveils problems in traditional task scheduling methods in 3DPCP. These issues manifest as incomplete considerations, subpar green performance, and weak adaptability to dynamic changes. There is an urgent need to design practical methods to realize the multidynamic information perturbations in green scenes within 3DPCP. Therefore, this article first defines the 3DPCP task scheduling problem for multidynamic information perturbation in green scenes. Second, the article proposes a task scheduling model and a heuristic task scheduling strategy to minimize both the average cost and carbon dioxide (CO2) emissions per unit of quality product. Finally, the article validates effectiveness and superiority of the proposed strategy through simulation experiments.

The uncertainties in current economic policies have increased, and Decisions about industrial convergence by businesses are impacted by uncertain macroeconomic policy. Using a fixed-effects model, the article selects annual data from A-share listed Chinese companies from 2010 to 2021 and empirically analyzes the relationship between economic policy uncertainty (EPU) and industrial convergence, as well as the mediating and moderating effects of diversification strategies and financial distress under this path of action. The findings are as follows: (1) EPU has a significant negative impact on industrial convergence, and this phenomenon is most obvious for non-state enterprises. (2) Enterprise diversification strategy mediate the relationship between industrial convergence and EPU (3) Corporate financial distress has a negative moderating effect on the relationship between EPU and industrial convergence. (4) The nature of firm property rights has a negative moderating effect on the relationship between EPU and industrial convergence. The aforementioned conclusions have implications for policy: the government should always ensure the long-term stability of economic policies and direct and encourage the development of cross-industry convergence of enterprises. Enterprises need to actively empower development with joint efforts to achieve win-win cooperation.

In the era of digital economy, Industrial Internet is promoting the deep integration of manufacturing industry and the Internet through the new generation of information technology, which has become a new driving force to encourage the development of digital transformation of manufacturing enterprises. In this paper, we use the China Industrial Internet Pilot Demonstration Project as a proposed natural experiment to assess the impact and mechanism of action of the Industrial Internet pilot on the digital transformation of manufacturing enterprises using score propensity matching and double-difference methods based on panel data of annual reports of manufacturing listed companies from 2012 to 2020. The empirical results show that the Industrial Internet has a significant empowering effect on the digital transformation of manufacturing enterprises and positively promotes the digital transformation of manufacturing enterprises through the mechanism of digitalization, technology absorption, talent introduction, and innovation integration of industry cohort enterprises; the heterogeneity analysis shows that the empowering effect of the Industrial Internet is more substantial for technology-intensive enterprises, diversified business enterprises, and enterprises in the eastern region. This study provides empirical evidence for understanding the digital transformation of manufacturing enterprises enabled by the Industrial Internet. It provides theoretical support for promoting the development of Industrial Internet projects and achieving sustainable development of the manufacturing industry.

Technology and innovation have promoted industry convergence and brought new opportunities for industrial development, and a degree of convergence exists in the emergency logistics industry. The purpose of this study is to explore the convergence of the emergency logistics industry and the change in convergence degree among related industries, so as to find a solution to the lack of robustness of the emergency logistics system. This study measures the technical relationship between industries and analyzes the overall trend of emergency logistics industry convergence using the consistency between patent co-classification analysis and patent categories and technical fields. The dominance index and relative strength index are used to assess the strength of industry nodes and the convergence of the emergency logistics industry. Social network analysis is used to investigate the industries and technical fields that are important in the convergence industry. The findings indicate that there is significant convergence between the technical fields of the emergency logistics industry. Twelve industries are actively involved in the emergency logistics industry convergence, and nine industry pairs have strong convergence relationships between them. The information industry is critical to the convergence of the emergency logistics industry. Industry convergence is assisting in the coordinated growth of the emergency logistics sector, lowering informational barriers between sectors, and boosting the system’s resilience. This study contributes theoretical significance to the development of the emergency logistics industry and enriches the emergency logistics industry’s research system.

Most previous works have studied the evolution of opinions based on the Hegselmann–Krause model, the Deffuant–Weisbuch model, and the Sznajd model. However, the influence of social influence on opinions is discussed less. Based on the social influence theory and the Hegselmann–Krause model of opinion dynamics, we introduce the affinity and social noise in the Hegselmann–Krause model of opinion dynamics and propose an affinity and social noise Hegselmann–Krause model (ASNHK). The influence of affinity degree, affinity threshold, social noise, and personnel heterogeneity on opinion evolution is discussed in experimental analysis. Experimental results show that the affinity between people can improve opinions to form a consensus positively, but the affinity threshold has a negative role contrarily. Moreover, when the social noise increases, the opinions will form a consensus. When it increases to a certain value, the opinion will be decentralized. Furthermore, personnel heterogeneity has different effects on opinion evolution. Open-minded individuals are more likely to form a unified opinion, while closed-minded individuals have difficulty unifying their opinions. Overall, this research provides a clearer explanation of the group opinion evolution from social influence.

Three-dimensional (3D) printing, also known as additive manufacturing, has unique advantages over traditional manufacturing technologies; thus, it has attracted widespread attention in the medical field. Especially in the context of the frequent occurrence of major public health events, where the medical industry’s demand for large-scale and customized production is increasing, traditional 3D printing production scheduling methods take a long time to handle large-scale customized medical 3D printing (M-3DP) production and have weak intelligent collaboration ability in the face of job-to-device matching under multimaterial printing. Given the problem caused by M-3DP large-scale customized production scheduling, an intelligent collaborative scheduling multiagent-based method is proposed in this study. First, a multiagent-based optimization model is established. On this basis, an improved genetic algorithm embedded with the product mix strategy and the intelligent matching mechanism is designed to optimize the completion time and load balance between devices. Finally, the effectiveness of the proposed method is evaluated using numerical simulation. The simulation results indicated that compared with the simple genetic algorithm, particle swarm optimization, and snake optimizer, the improved genetic algorithm could better reduce the M-3DP mass customization production scheduling time, optimize the load balance between devices, and promote the “intelligent manufacturing” process of M-3DP mass customization.

With the continuous cross-border cooperation among industries, the concept of an industrial interconnection supply and demand network is constantly mentioned. As industry interconnectivity continues to grow, collaboration models have changed as companies work more closely with each other, and the synergy model has changed. In order to improve the efficiency of collaboration and to promote the free allocation of resources in the trading process of the industry interconnection supply and demand network, an industry interconnection supply and demand network resource matching platform based on the Alliance blockchain was built, steps for resource trading on the platform were proposed. Using blockchain technology’s smart contract technology to simplify the transaction process, the triggering mechanism and algorithm rules of smart contracts in the trading process of the platform were designed, and the smart contract code was developed, deployed, and tested using Remix IDE, and the test results showed the transaction process between the supply and demand sides. Through blockchain technology, it achieves information security and transparency in the process of resource trading in the industry interconnection supply and demand network, establishes a trust mechanism on both sides of the transaction, reduces redundant steps in the transaction and improves the operational efficiency of the industry interconnection supply and demand network by increasing the efficiency of resource allocation.