Search Results (163)

Supply chains are increasingly exposed to sudden disruptive events (SDEs) such as natural disasters and trade wars. We develop a multi-stage game-theoretical model to investigate a novel coping mechanism: when a firm is forced to exit the market because of SDEs, the firm can regain profits by licensing its proprietary production tech to a competitor. We find that, compared with the scenario before SDEs, such events can even increase the profit of each manufacturer under certain conditions. Under certain conditions, the cooperative strategy (i.e., supply chain reshaping) yields a higher supply chain system profit than the non-cooperative strategy. After SDEs, the common manufacturer may either accept or reject cooperation, depending on the customer transfer rate and the cooperation cost. Notably, under the cooperation strategy, the high-tech manufacturer extracts part of the common manufacturer’s profit through patent licensing, and the existence of cooperation cost further contributes to a misalignment between the common manufacturer’s optimal decision and the supply chain system optimum. These findings contribute to the literature by identifying a novel supply chain reshaping mechanism driven by patent licensing and offer strategic guidance for firms and policymakers navigating SDE-induced market exits. Full article

To evaluate the efficiency of innovation development in China’s high-tech manufacturing industry, this paper constructs a two-stage dynamic network cross-efficiency model. This model divides innovation activities into two stages: technology research and development and achievement transformation and introduces a 2-year lag period in the technology research and development stage and a 1-year lag period in the achievement transformation stage. It proposes the overall efficiency and efficiency models for each stage. The model was applied to 30 provinces in China, and the results showed that most provinces have achieved relatively ideal results in the overall efficiency and achievement transformation stage of high-tech manufacturing, while the efficiency in the technology research and development stage is generally lower than that in the achievement transformation stage. It is recommended that enterprises increase their R&D investments, break through technological barriers, and optimize the innovation chain. Full article

The global trend toward Industry 4.0 has intensified the demand for intelligent, adaptive, and energy-efficient manufacturing systems. Machine learning (ML) has emerged as a crucial enabler of this transformation, particularly in high-mix, high-precision environments. This review examines the integration of machine learning techniques, such as convolutional neural networks (CNNs), reinforcement learning (RL), and federated learning (FL), within Taiwan’s advanced manufacturing sectors, including semiconductor fabrication, smart assembly, and industrial energy optimization. The present study draws on patent data and industrial case studies from leading firms, such as TSMC, Foxconn, and Delta Electronics, to trace the evolution from classical optimization to hybrid, data-driven frameworks. A critical analysis of key challenges is provided, including data heterogeneity, limited model interpretability, and integration with legacy systems. A comprehensive framework is proposed to address these issues, incorporating data-centric learning, explainable artificial intelligence (XAI), and cyber–physical architectures. These components align with industrial standards, including the Reference Architecture Model Industrie 4.0 (RAMI 4.0) and the Industrial Internet Reference Architecture (IIRA). The paper concludes by outlining prospective research directions, with a focus on cross-factory learning, causal inference, and scalable industrial AI deployment. This work provides an in-depth examination of the potential of machine learning to transform manufacturing into a more transparent, resilient, and responsive ecosystem. Additionally, this review highlights Taiwan’s distinctive position in the global high-tech manufacturing landscape and provides an in-depth analysis of patent trends from 2015 to 2025. Notably, this study adopts a patent-centered perspective to capture practical innovation trends and technological maturity specific to Taiwan’s globally competitive high-tech sector. Full article

The advancement of high-tech industries, notably in semiconductor manufacturing, pharmaceuticals, and precision instrumentation, has imposed stringent requirements on cleanroom environments, where strict control of airborne particulates, microbial presence, temperature, and humidity is essential. However, these controlled environments incur significant energy consumption, with air conditioning systems accounting for 40–60% of total usage due to high air circulation rates, intensive treatment demands, and system resistance. In light of global carbon reduction goals and escalating energy costs, improving the energy efficiency of cleanroom heating, ventilation, and air conditioning (HVAC) systems has become a critical research priority. Recent efforts have focused on optimizing airflow distribution, integrating heat recovery technologies, and adopting low-resistance filtration to reduce energy demand while maintaining stringent environmental standards. Concurrently, artificial intelligence (AI) methods, such as machine learning, deep learning, and adaptive control, are being employed to enable intelligent, energy-efficient system operations. This review systematically examines current energy-saving technologies and strategies in cleanroom HVAC systems, assesses their real-world performance, and highlights emerging trends. The objective is to provide a scientific basis for the green design, operation, and retrofit of cleanrooms, thereby supporting the industry’s transition toward low-carbon, sustainable development. Full article

The middle reaches of the Yangtze River are important bases for high-tech, advanced manufacturing, and modern service industries in China, as well as a demonstration area for the coordination of economic and ecological construction, which plays an important role in the ecosystem carbon cycle. With the steady progress of social and economic development and urbanization, the supply capacity of ecosystem services has sharply decreased, and the carbon cycle mechanism has changed, further reducing the sustainability of regional ecosystem services. In this study, carbon storage in the middle reaches of the Yangtze River was estimated from 2000 to 2020 based on the InVEST model, and the temporal and spatial evolution characteristics of carbon storage in the middle reaches of the Yangtze River were summarized using the coefficient of variation and spatial autocorrelation. The coupled InVEST-PLUS model was used to simulate the carbon storage characteristics of the middle reaches of the Yangtze River under natural development, ecological protection, cultivated land protection, and urban development scenarios in 2035. The results show the following: (1) The main land-use types in the middle reaches of the Yangtze River are cultivated and forest land, and the land-use types in the study area show the characteristics of “two increases and four decreases” in the past 20 years. (2) The carbon storage level in the middle reaches of the Yangtze River has decreased by 83.65 × 10⁶ t in the past 20 years (approximately 1.16%). The coefficient of variation showed that the carbon storage level in the middle reaches of the Yangtze River was high, with the fluctuating area accounting for 8.79% of the total area. The results of local spatial autocorrelation show that the high-value areas of carbon storage are mainly distributed in the west and southeast of the study area, and the low-value areas are mainly distributed in the middle of the study area, exhibiting characteristics of “high values surrounding low values” in space. (3) The simulation results of carbon storage in the middle reaches of the Yangtze River in 2035 showed that the ecological protection scenario was better than the other scenarios in terms of the mean level, functional performance, and patch presentation. Full article

Innovation has become a pivotal factor in driving economic growth for cities and regions. Urban innovation spaces are urban spaces where innovative economic and industrial activities, such as research, teaching, and high-tech manufacturing, are clustered. They have become hot research topics in recent years. Evaluating the performance of urban innovation spaces to promote rational resource allocation and enhance land development potential has become a critical task in urban planning. However, existing studies suffer from insufficient depth of research scales and a lack of quantitative indicators and data analysis. In response to the above gaps, this study constructed a framework for evaluating the performance of urban innovation spaces from 25 indicators of five major types, including core elements of innovation, entrepreneurship support institutions, service facilities, external environments, and diversities, aiming to quantify the performance heterogeneity of innovation spaces at the micro scale. This study took Harbin as an example and employed the entropy, kernel density estimation, and entropy-weighted TOPSIS methods, identifying four high-scoring areas of innovation spaces—the Science and Technology Innovation City area, the High-tech Industrial Development area, the core area of the old city, and the Harbin Veterinary Research Institute area—which were divided into three types: the Entrepreneurial leading area, Environmental Support area, and Balanced Development area. Finally, this study analyzed the interaction between each indicator. It was found that the correlation between the core elements of innovation and the indicators of entrepreneurship support institutions was strong and had a high degree of importance. The correlation of different types of service facility indicators is quite different, and the external environment indicators and diversity indicators are mainly affected by other indicators, especially the core elements of innovation and entrepreneurship support institutions. This paper provides a valuable tool for the performance evaluation of urban innovation spaces for researchers and urban planning decision makers. Full article

The digital transformation of enterprises constitutes a crucial element of modernization processes in the countries of the European Union, supporting the achievement of sustainable development goals through increased innovation, economic efficiency and the development of high-tech sectors and knowledge-intensive services. In empirical analyses, multidimensional statistical analysis methods were applied, with particular emphasis on linear ordering, classification methods and regression analysis. Ten monitoring indicators adopted by the European Union constitute the basis for assessing the digital transformation advancement of enterprises. The study classified EU countries into three groups according to the level of digital transformation: low, medium and high. Based on the employment structure in high-tech manufacturing, medium–high-tech manufacturing and knowledge-intensive services, four distinct types of employment structures were identified. A positive relationship was found between the level of digital transformation and the share of employment in knowledge-intensive services, while no significant relationship was observed for the other sectors. The study shows that the EU countries are clearly differentiated both in terms of the level of digital transformation of enterprises and the structure of employment in high-tech manufacturing, medium–high-tech manufacturing and knowledge-intensive services. A higher level of digital transformation supports the growth of employment in knowledge-intensive services, while its impact on high-tech and medium–high-tech manufacturing remains limited. Full article

The Free Trade Area (FTA) strategy and the participation of enterprises in global value chains (GVCs) are important aspects of China’s high-quality economic development stage. This study matches trade data from the China Customs Import and Export database with information from listed firms in the CSMAR database, calculating the firms’ GVC embeddedness and the depth of trade agreements at the firm level. On this basis, this research employs a gravity model with fixed effects to empirically analyze the impact and mechanism of the FTA strategy on the embedding of Chinese listed firms in GVCs, utilizing data from 2000 to 2006. The results demonstrate that the FTA strategy substantially enhances the embeddedness of Chinese listed enterprises in GVCs. The heterogeneity analysis indicates that state-owned enterprises, those located in the central and western regions, manufacturing firms, and high-tech industry enterprises derive greater advantages from the FTA strategy in terms of their embeddedness in GVCs. Moreover, the mechanism analysis indicates that the FTA strategy enhances the embeddedness of enterprises in GVCs by increasing their technological innovation levels. Additionally, the internal control costs of enterprises negatively moderate the impact of the FTA strategy on their embedding in GVCs, and a “substitution effect” exists between asset operating efficiency and the FTA strategy in promoting the GVC embedding of listed firms. These findings provide empirical evidence and policy recommendations for the Chinese government to enhance the FTA strategy and sustainably improve the embeddedness of Chinese listed enterprises in GVCs. Full article

This study investigates how small and medium-sized enterprises (SMEs) can successfully transform into high-tech, high-value-added companies within the aviation industry, considering the latest manufacturing, certification, and quality technologies. We identified critical factors through a comprehensive literature review and expert interviews, then analyzed the relationships between these factors using two complementary methodologies: grey DEMATEL (Decision Making and Trial Evaluation Laboratory) and ISM (Interpretive Structural Modeling). Our approach employed grey numbers to address individual uncertainty and utilized the Aczel–Alsina function to integrate expert opinions while accounting for inter-expert disagreements. The research focused on traditional machinery manufacturers in Taiwan transitioning to aviation manufacturing, the findings being applicable to enterprises in other countries with similar environments where small and medium-sized enterprises are the main players. The results revealed three critical factors determining successful transformation: organizational culture and workforce quality, aviation certification protocols, and original equipment manufacturer (OEM) outsourcing policies and requirements. Based on these findings, the study provides strategic recommendations for government policymakers and business executives to facilitate the successful entry of traditional industrial enterprises into the aviation manufacturing sector. Full article

This study aims to investigate the impact of board size on environmental, social, and governance (ESG) controversies using data from Chinese-listed companies during 2007–2022. In addition, we explore the moderating effects of female participation on corporate boards, board age, financing constraints, and internal control. ESG controversies are measured by an ESG controversies score from the LSEG Workspace, and fixed effects models are used to perform the analysis. The results show that larger boards can lead to more ESG controversies in China. This impact is greater in non-manufacturing, heavily polluted, and non-high-tech industries, in state-owned enterprises, eastern regions, and non-foreign-funded companies. Additionally, women on boards and internal control weaken the impact of board size on ESG controversies, while financing constraints strengthen this impact. The moderating effect of board age is not significant. The findings can help Chinese-listed companies improve their ESG performance and achieve sustainable development through strengthening corporate governance. Full article

In line with the principles of the circular economy, this study aimed to develop a pyrolysis-activation regeneration process capable of producing highly porous carbon materials from spent granular activated carbon (GAC), which was generated by a high-tech electronics manufacturing company in Taiwan. Thermogravimetric analysis (TGA) and other thermochemical analyses were first conducted to investigate the thermal decomposition behavior of the spent GAC. Subsequently, the thermal regeneration system was employed to perform the N₂ pyrolysis and CO₂ activation experiments under various process conditions (i.e., 800, 850, and 900 °C for holding 0, 30, and 60 min, respectively). Analytical instruments included a surface area and porosimeter for pore property analysis, scanning electron microscopy (SEM) for porous texture observation, and energy dispersive X-ray spectroscopy (EDS) for surface elemental distribution analysis. The results revealed that the pore properties of thermally regenerated GAC were significantly improved compared to the spent GAC, indicating the effective removal or decomposition of adsorbed organics and deposited substances under the process conditions. Additionally, thermal regeneration via physical activation with CO₂ led to enhanced pore properties compared to simple pyrolysis. The maximum BET surface area achieved exceeded 720 m²/g, which was greater than those of spent GAC (approximately 425 m²/g) and N₂-pyrolyzed GAC (approximately 570 m²/g) under the same regeneration conditions (i.e., 900 °C with a 30 min holding time). Full article

In the era of new productive forces, the efficient utilization of industrial land in high-tech zones is critical for fostering technological innovation, intelligent manufacturing, and green development. However, constrained by limited land reserves, inefficient stock utilization, and sluggish industrial upgrading, high-tech zones must establish a scientific early warning mechanism for industrial land redevelopment. This study constructs a four-tier early warning system (normal, alert, warning, and response) based on three key dimensions: enterprise life cycle, enterprise–park compatibility, and industrial land use efficiency. Using the Jinan High-Tech Zone as a case study, this study conducts an empirical analysis of 360 industrial land parcels from 2020 to 2022, employing DEA, fixed effects models, GIS visualization, and MCDA methods. The results indicate a strong correlation between enterprise life cycle and land use efficiency, with significant spatial differentiation in enterprise–park compatibility. Efficient land use is concentrated in areas with well-defined functions and high industrial agglomeration. This study identifies 360 land use scenarios, with 12% classified as normal, 28% requiring monitoring, 52% requiring optimization, and 8% necessitating redevelopment. Based on these findings, a “warning–monitoring–regulation” closed-loop management model is proposed, providing decision-making support for dynamic land optimization and sustainable development in high-tech zones. Full article

The global and domestic divisions of labor have had a great influence on the economy and environment in China during the last decade. With the refinement of production processes, national value chains (NVCs) coexist with global value chains (GVCs), enabling regions to participate in dual value chains (DVCs) simultaneously. This study calculates the NVCs and GVCs participation of manufacturing sectors in China’s provinces. On this basis, this research adopts a fixed effects model to analyze the impact of GVCs and NVCs participation and their interaction effect on manufacturing upgrades and green development. The results show, first, that significant regional differences in GVCs participation exist among provinces in China. In comparison, provincial NVCs participation demonstrates fewer regional differences. Second, there are significant sectoral differences of GVCs participation in China’s manufacturing industry—high-tech manufacturing is more embedded than other manufacturing industries. The sectoral differences in NVCs participation are relatively small. Third, GVCs and NVCs participation and their interaction effect have significantly promoted the upgrading and green development of manufacturing sectors in provinces of China, and this impact exhibits significant heterogeneity across regions, industries, and NVCs participation modes. The conclusions of this study provide empirical evidence and policy recommendations for the upgrading and green development of China’s manufacturing industry. Full article

Background: Influenza is a serious contagious disease caused by influenza virus. It is particularly dangerous for children, potentially leading to severe and even fatal complications. The aim of this study was to evaluate the safety and immunogenicity of two candidate quadrivalent influenza subunit vaccines in children aged 6–35 months. Methods: The subjects were randomly divided into three groups at a 1:1:1 ratio and received the corresponding vaccines: QIV-Sub-HD (Quadrivalent Influenza Subunit Vaccine, High Dose), QIV-Sub-LD (Quadrivalent Influenza Subunit Vaccine, Low Dose) and QIV-Split-LD (Quadrivalent Influenza Split-Virion Vaccine, Low Dose). Adverse events were recorded at 30 min, 0–7 days and 8–28 and 30 days after each dose of immunization. Serious adverse events (SAEs) were collected and reported within 6 months after the full vaccination. Blood samples were collected before the first dose and on 28 days, 3 months and 6 months after full vaccination for antibody detection to evaluate the immunogenicity and duration of immune responses. Results: The results showed that the relative and absolute criteria met the goals set by the clinical trial protocol, indicating that both vaccines are immunogenic. From the first dose to 30 days after full vaccination, the total incidence of adverse reactions in the QIV-Sub-HD, QIV-Sub-LD and QIV-Split-LD groups was 29.64%, 33.33% and 29.64%, respectively. The main symptoms were fever, cough, diarrhea and vomiting. No new safety concerns were identified. Conclusions: The quadrivalent influenza subunit vaccines candidate, manufactured by Ab&B Bio-tech Co., Ltd. JS., are safe and immunogenic in children aged 6–35 months. Full article

This study analyzes the impact of digital transformation on the international economic integration of ASEAN-6 countries during the period of 2000–2023 using the Generalized Least Squares (GLS) estimation method. The findings indicate that factors such as fixed broadband subscriptions (FixB), fixed telephone subscriptions (FixT), and the value added from medium- and high-tech manufacturing (MHT) have a positive and statistically significant effect on trade openness (TO). Conversely, mobile cellular subscriptions (MB) and the percentage of individuals using the Internet (IU) exhibit a negative impact on economic integration, reflecting the uneven development of digital infrastructure across countries. Based on these results, the study suggests policy implications, including substantial investment in digital infrastructure, technological advancement in production, and improved accessibility to digital services to foster more effective economic integration. ASEAN-6 countries should adopt tailored development strategies that emphasize innovation and the development of a skilled digital workforce to enhance their competitiveness both regionally and globally. Full article