For a long time, problems such as information lag and cumbersome processes have been widespread under the traditional supply chain management mode. The phenomenon of information silos among enterprises has become the primary obstacle to information connection and efficiency improvement in the supply chain. With the emergence of the digital era, the application of big data, artificial intelligence, the Internet of Things, cloud computing and blockchain technology has successively empowered supply chain management, injecting new vitality into the innovation and efficiency improvement of modern supply chain management models. There are very few studies in the existing literature that examine the employment spillover effects of digital technology application in supply chains. From the perspective of supply chain network construction, This paper intends to explore the impact of supply chain digital technology application on the scale of labor employment of enterprises, and further analysis the impact of the collaborative application of supply chain digital technology of other enterprises in the industrial chain on the scale of labor employment of enterprises in the chain. Compared with the existing literature, the potential contributions of this paper are as follows: Firstly, different from traditional literature that focuses on the analysis of the substitution effect and creation effect of digital transformation on labor employment of enterprises, this paper takes the application of digital technology in supply chain network as an entry point to discuss the spillover effect of supply chain network construction on labor employment of enterprises in the chain. Specifically, this paper clarifies two paths of the employment spillover effect of supply chain digitization from the aspects of commercial credit spillover along the supply chain and smoothing enterprise production, which enriching the existing research on the factors affecting employment in the labor market. Secondly, this paper focuses on the analysis of the synergy between the upstream and downstream of the supply chain network, emphasizing the win-win cooperation of multiple subjects from the perspective of the supply chain, providing theoretical support and empirical evidence for the subsequent promotion and construction of industrial chain digitization. Based on the supply chain research data of listed companies and the perspective of supply and demand network construction, this paper discusses the employment effect of supply chain digitization. The difference-in-differences results show that the enterprise's digitization has a substitution effect on labor employment, while the supply chain digitization within industrial chain can effectively improves the enterprises’ employment scale by smoothing production and reducing the downstream enterprises’ occupation of commercial credit funds, which helps to ease the liquidity constraints of enterprises. In addition, industrial supply chain digitization can effectively cushion the impact of supply chain risks on the labor market, which helps to achieve "the employment-stabilizing". Heterogeneity analysis shows that the employment-stabilizing effect of industrial supply chain digitization is limited by the financing constraints, state-owned enterprises and the enterprises with concentrated purchasing and marketing business show greater spillover effect on employment.The research conclusions of this article are of great significance for the subsequent development of digitized supply chain construction, the maintenance of supply chain security and stability.

Addressing climate change has become a global consensus, and the energy sector, as the primary "contributor" to global carbon emissions, has become an important reform area for countries to promote carbon neutrality. In recent years, with the rapid development of clean energy technology, the proportion of renewable energy such as wind and solar energy in the energy system continues to increase, and a new generation of global energy system with electrification, high efficiency, low carbon and interconnection is taking shape. Scientific and technological innovation will once again promote the evolution of human energy system and become the first driving force to support and lead the realization of the "double carbon" goal. This paper expounds the necessity, urgency and importance of relying on scientific and technological innovation to promote the development of China's clean energy industry from three aspects: the development of clean energy science and technology, the scientific and technological competition between China and the United States, and the development of China's traditional manufacturing-green superior industry. This paper systematically expounds the development status of clean energy industry in China from four aspects: the level of clean energy technology, the utilization rate of clean energy resources, the empowerment of digital intelligence technology and the construction of talent team, and clarifies the five major challenges facing the development of clean energy industry in China. First, China's energy system is confronted with the challenges of total demand growth and suboptimal structure in the short and medium term. Secondly, there is a spatial dislocation between energy supply and demand in China. Thirdly, the rapid development of clean energy industry forces China to speed up the construction of a new power system. Fourthly, there is still a certain gap between China's clean energy technology level and that of developed countries. Fifthly, China's strategic mineral resources supply chain is facing greater risks. To this end, the practical path of scientific and technological innovation to support the development of China's clean energy industry lies in: coordinating the national energy strategic deployment, eliminating the spatial differences between energy supply and demand; focusing on the world's leading edge of energy science and technology, speeding up the tackling of key core technologies; relying on major projects to reduce costs and increase efficiency, promoting advanced technologies to try first; promoting the construction of energy integration systems, improving the efficiency of cross-border energy utilization. We should extensively expand international scientific and technological cooperation, fully learn from the successful experience of the United States and Europe, implement the strategy of guaranteeing the supply of mineral resources, and build a safe and resilient supply system. The key policy recommendations are as follows: First, vigorously promote the development of new energy storage industry and support the transformation of energy supply from "trans-regional energy transmission" to "local energy supply". The second is to build a scientific and technological innovation consortium in the field of energy and give full play to the role of leading enterprises in science and technology. Third, we should create an innovative ecosystem for technology sharing, accelerate the cross-industry and cross-domain flow of advanced technology, and stimulate innovation vitality. Fourthly, the State Key Laboratory of Energy System Integration should be established to tackle key problems in the form of major engineering projects. Fifth, we should actively build a more proactive mechanism for international scientific and technological cooperation.

This study explores the application of complex networks and computational science of science paradigms in the field of Science of Science, focusing on uncovering universal laws behind scientific activities while addressing the challenges of avoiding the “numerical game.” In the era of big data, large-scale data has provided new perspectives for science studies, where complex networks help reveal hidden patterns in scientific research by analyzing collaboration networks and knowledge dissemination pathways. Computational science of science, powered by advanced algorithms and models, has further enabled intelligent analysis in science studies. However, this data-driven approach also poses potential risks of falling into the “numerical game,” where over-reliance on quantitative analysis may overlook the complexities and contextual factors inherent in scientific activities. This study not only examines the strengths of complex networks and computational science of science in related studies but also delves into how to balance data-driven methods with domain knowledge to avoid the limitations of excessive data dependence. Ultimately, this paper aims to offer new perspectives for the future development of science studies and calls for more cautious and integrative approaches to address the challenges of modern science.

The contemporary life science research paradigm is undergoing a major transformation. Along with the continuous integration between biotechnology and information technology, the evolution of research beliefs, methods, and cultures have jointly promoted the paradigm shift of life science research: research beliefs have shifted from reductionism to holism, and the dialectical integration of the two has been realized with the help of network thinking; the rise of deep learning has led to the realization of double leaps in efficiency and precision of computational simulation and modeling methods under the strong coupling of data, algorithms, and computing power; and the organization and management modes have gradually become data-centric, platform-based, and ecological, awakening the advocacy and support of an open scientific culture. The new paradigm of data-driven life science research has accelerated the process of scientific discovery and expanded the scope of scientific discovery, and at the same time brought about many biotechnological and ethical challenges.

As the primary resource, talents, especially the strategic talent force, play an increasingly prominent supporting role in enterprise innovation activities. However, despite the remarkable progress made in the construction of talent teams across various industries, the cultivation and utilization of the strategic talent force are still in the long - term exploratory stage. A large number of enterprises still have no understanding of the overall picture of the strategic talent force and lack systematic theoretical guidance on how to cultivate relevant talents. Regrettably, the current theoretical research on the competency structure and development laws of the strategic talent force is still in its infancy. Existing studies have carried out some exploratory work on deconstructing the competency structure of the strategic talent force, but their focus has been on describing the morphological characteristics of talent competency elements. Questions such as what differences exist in the competency structures of different types of strategic talent forces and what development trajectories the elements in a specific competency structure follow still remain to be answered. Therefore, this study, on the basis of clarifying the competency configurations of two types of strategic talents, strategic scientists and outstanding engineers, maps the evolution of their competencies with individual growth, thus providing new insights for cultivating competencies required for strategic talents.

We conducted semi-structured interviews with 34 top experts from a central state-owned enterprise. These interviews required respondents to recall 1-3 behavioral events of themselves or high-level talents around them in the process of achieving significant accomplishments, solving major problems, leading major projects, as well as 1-3 typical experiences of their own growth and participation in talent cultivation. Subsequently, adopting the programmatic grounded theory, we refined the typical competencies of strategic scientists and outstanding engineers, and the processes and mechanisms of the competencies’ formation.

The study finds that: (1) Strategic scientists possess competencies such as a commitment to scientific truth, a noble scientific mission, a strategic scientist identity, advanced theoretical insights, and exceptional exploration abilities; outstanding engineers possess competencies such as practical engineering qualities, ambitious engineering goals, an outstanding engineer identity, forward-looking engineering insights, and excellent practical skills. The competency configurations of strategic scientists and outstanding engineers exhibit heterogeneity, with the former serving scientific discovery and theoretical innovation, while the latter serves engineering practice and industrial development; (2) The evolution of the competency configurations of strategic scientists and outstanding engineers includes five core stages: enlightenment, education, career initiation, career development, and career emergence. (3) The differences in the competency configurations lead to varying key factors and pathways in their corresponding evolutionary contexts. Moreover, the development of competencies demonstrates dynamic characteristics of sequential integration and presents an evolutionary form of multiple parallel pathways.

The theoretical contributions of this study can be summarized in three aspects: First, unlike previous studies that focused on depicting the profile of a single type of strategic talents, this study deconstructs and contrasts the competency configurations of scientists and engineers, by considering the context distinction of talents. Second, differing from studies on talent development, this study goes beyond merely observing the individual development of strategic talents and, by considering the dynamic characteristics of competencies, delves deeply into the underlying trajectory of competency evolution. Third, in terms of theory, this paper combines the longitudinal perspective of career theory with the lateral perspective of competency theory, fostering dialogue between these two talent-focused theories.

Provincial strategic emerging industry development planning is a major measure to implement the national innovation strategy and promote local economic development. In order to implement the national strategic requirements of developing new quality productivity in accordance with local conditions and promoting the healthy and orderly development of strategic emerging industries, in view of the current problems of convergence, greed for perfection and forcing the growth of local strategic emerging industries, a provincial strategic emerging industry evaluation methodology based on comparative advantage theory and overcoming the "comparative advantage trap" was constructed on the basis of reviewing existing research results, so as to serve the scientific decision-making of local governments and support local governments in selecting characteristic industries with comparative advantages. This evaluation methodology introduces sustainable development theory and innovation theory, establishes two dimensions of resource endowment and comprehensive output, and innovatively constructs an indicator system that highlights scientific and technological innovation, ecological friendliness, social welfare and economic efficiency, breaking through the limitation of existing research focusing on the singleness of economic indicators. The Shanxi Province, which once faced the challenge of the "comparative advantage trap", was used as an example for verification and analysis. The results show that the evaluation method is practical, feasible and scientific. Based on the experience of empirical research, practical and policy recommendations are put forward.

Accelerating the construction of independent innovation capabilities in core technologies is an imperative requirement in the new context of international scientific and technological competition. Against this backdrop, China's innovation policy planning must transcend the traditional logic of follower catch-up and shift towards a technological strategic perspective of beyond catch-up. It is essential to balance the breakthrough of bottleneck technologies and the forward-looking layout of killer technologies, focusing not only on the autonomy and control of current key industries but also on shaping future technological competitive advantages.

Focusing on the strategic layout of national innovation policy, this study defining and discussing the scientific connotations and development patterns of killer technologies from the perspective of beyond catch-up, and emphasizes the strategic significance of killer technologies in international competition, which compensates for the bias of existing research that predominantly emphasize bottleneck technologies. Killer technologies refer to "asymmetrical technologies" mastered by technological entities at the high end of the innovation chain, which are difficult for other entities to imitate and surpass. Killer technologies are primary innovation outcomes formed within an endogenous innovation chain, fundamentally different from bottleneck technologies that rely on external sources of innovation. In the process of breaking through bottleneck technologies, latecomers who improve and expand within existing technological paradigms and tracks are prone to falling into the "catch-up trap" of continuous catching up and continuous falling behind.

This study provides a comprehensive analysis of the "valley of death" phenomenon in key core technology innovation. On the basis of summarizing and sorting out the patterns of innovation transformation chains for two types of key core technology, the study analyzes the three major innovation breakpoints and constraints of innovation achievement transformation from basic research to application development, to productization, and then to scaling up, which supplements the previous research's insufficient attention to the breakpoints of upstream technology acquisition and downstream technology promotion. The main challenges faced by killer technologies at the stages of technology acquisition, transformation, and promotion are the insufficiency of continuous basic research, goal divergence among multiple entities, and the failure of business model innovation. Bottleneck technologies face the "cold start" paradox of latecomers, the lack of "know-how" in application transformation, and the difficulty of scaling up development at three stages.

Breakthroughs in key core technologies typically require multiple entities to collaborate in complex innovation networks. Focusing on the three types of "valley of death" faced by the two categories of key core technologies, this study systematically elaborates the breakthrough path mechanisms for killer technologies and bottleneck technologies based on the "capability enhancement - resource allocation - institutional environment" logical framework, aiming to provide new theoretical perspectives and practical guidance for China's innovation policy layout. Capacity building of entities is key to breakthroughs in key core technologies, the optimization of resource allocation aims to enhance the entity capabilities, and reasonable and effective institutional arrangements support and safeguard the effective allocation of resources. These three types of innovation breakthrough elements interact and collaborate effectively in the process of breaking through key core technologies.

The intensified competition amidst the new round of technological changes and industrial revolutions has led to substantial advancements in the manufacturing industry. However, there is a notable dependency on imports in key core technology areas, such as next-generation information technology and biomedical industry, posing significant challenges. In response, the report of the 20th National Congress of the Communist Party of China in 2022 made important strategic deployments, proposing to resolutely win the battle for mastering key core technologies. The unique and in-depth professional technology accumulated by enterprises in specific knowledge fields for a long time is the key driving force to promote the breakthrough of key core technologies. In this context, SRID enterprises, leveraging their professional expertise and deep cultivation in specific segments of the industrial chain, are crucial for breaking through key core technologies.

There is a consensus in literature on the importance of knowledge resources in driving breakthroughs in key core technologies. However, existing research primarily focus on exploring this through collaboration networks, lacking literature that examines the impact mechanism of a firm's internal knowledge base on key core technology breakthrough, especially empirical research on the degree of technological specialization among SRDI enterprises.

This study takes the new generation of information technology industry in the first five batches of listed small giant enterprises in China as the research object, and deeply explores the effect of technological specialization on the breakthrough of key core technologies, the mediating role played by knowledge search in this process, and the moderating role of knowledge integration capabilities. The results show that there is an inverted U-shaped relationship between technology specialization, knowledge search and key core technology breakthroughs. A firm's specialized knowledge base and externally searched heterogeneous knowledge provide a direct resource base for breakthrough innovations in key core technology fields. The moderating effect analysis shows that the inverted “U” shaped relationship between technology specialization and key core technology breakthroughs is mediated by knowledge search. Enterprises will conduct knowledge searches based on their own knowledge characteristics and, through continuous cooperation and exchanges with the outside world, provide more extensive or in-depth heterogeneous knowledge resources for breakthrough innovations in key core technology fields, thereby freeing enterprises from resource constraints. In addition, knowledge integration ability moderates the role of technology specialization and knowledge search on key core technology breakthroughs, respectively. High knowledge integration ability will alleviate the negative impact of over-specialization and over-search, and when it breaks through a certain threshold, it can completely offset the negative impact and further promote key core technology breakthroughs.

These findings hold significant importance for enterprises to facilitate knowledge search by deepening their own specialized knowledge, thereby promoting breakthroughs in key core technologies: (1) SRDI enterprises should deepen core technology research while exploring diversified technologies, forming dedicated teams and building a knowledge base to avoid the specialization trap. (2) SRDI enterprises should integrate internal and external resources by collaborating across sectors and deeply mining existing knowledge, utilizing advanced tools for systematic analysis and integration. (3) Constructing a knowledge sharing platform and nurturing a multidisciplinary team will enhance resource integration, facilitating efficient knowledge conversion and application.

This study emphasizes the complementary synergy between knowledge search and technology specialization, expands the research scope of key core technology breakthroughs at the micro level, and provides theoretical guidance and decision-making reference for enterprises to promote key core technology breakthroughs.

Chip lithography technology is a pivotal component in the semiconductor manufacturing domain and exemplifies the “root-trunk-branch” characteristics of a complex technology cluster. Its relevance extends beyond individual processes, influencing a country’s comprehensive technological capabilities and industrial competitiveness. However, existing research has offered only limited insight into how these multifaceted core technologies evolve in clusters over time. In an effort to address this knowledge gap, researchers introduced the concept of “root technology,” employing both explicit and implicit relationships derived from patent data to explore the dynamic evolution of key core technologies. By incorporating terminology extraction, clustering analysis, and related methods, they developed an analytical model that delineates the way crucial lithography innovations emerge and transform.

The findings of this study highlight four principal root technologies within the broader chip lithography system—projection exposure technology, direct-write lithography technology, photoresist materials, and photomask manufacturing. Together, they form the backbone of chip lithography’s evolution and diverge into distinct pathways of development. While projection exposure technology tends to merge features from various domains (reflecting a fusion-oriented path), direct-write lithography gradually contracts into more specialized niches, signaling a pattern of consolidation. Photoresist materials expand and diversify to accommodate evolving demands and technical frontiers, illustrating a path of sustained growth. By contrast, photomask manufacturing branches out into multiple subfields, capturing a split-type trajectory that underscores the complexity and range of potential innovations in that area.

This comparative perspective on distinct evolutionary paths accentuates the defining traits of root technologies: they provide a fundamental foundation for subsequent developments; they exhibit high levels of complexity and intricate integration with complementary domains; and they impose significant barriers to entry, owing to their specialized expertise, substantial R&D requirements, and stringent quality standards. Such insights contribute to a deeper understanding of the unique nature of root technologies, advance theoretical frameworks on complex innovation clustering, and add practical value for policymakers and industry leaders.

In particular, these outcomes offer concrete guidance for China’s chip lithography sector, which faces urgent demands for technological breakthroughs. By pinpointing the specific root technologies and clarifying how each one evolves, researchers and practitioners can formulate strategies to distribute resources more effectively, foster targeted collaborations, and stimulate ongoing innovation in lithography manufacturing. Ultimately, appreciating the interconnected yet distinct evolution paths of projection exposure, direct-write lithography, photoresist materials, and photomask manufacturing helps lay the groundwork for robust policy decisions and industrial strategies that will shape the future of semiconductor fabrication.

Regional science and technology innovation capacity is an important starting point for leading high-quality development. Building regional science and technology innovation centers is conducive to gathering innovation elements and resources and promoting the improvement of the capabilities of various innovation entities. At the same time, in order to accelerate the strategic deployment of big data and create an innovation landscape led by big data, as a data element distribution center and a big data industry gathering place, the big data comprehensive pilot zone can provide data sharing dividends and industries for regional technological innovation development. It supports the engine and contributes to continuous practice and sums up big data industry development experience that can be promoted and replicated across the country. Based on the quasi-natural experiment established in the big data comprehensive pilot zone, this study adopted a multi-period double difference (DID) model to conduct statistical analysis on panel data of 30 provinces (including municipalities and autonomous regions) from 2011 to 2021, in order to explore the impact of the big data comprehensive pilot zone on regional science and technology innovation capacity and the implementation effects of different pilot policies. Research results show that the establishment of a national big data comprehensive pilot zone has significantly improved regional science and technology innovation capacity. This conclusion still holds true after passing the placebo test, lag one-period model and robustness test excluding first-tier cities. In order to further explore the effect of different pilots in the national big data comprehensive pilot zone on the science and technology innovation capacity of surrounding areas, this article also conducted a heterogeneity analysis on the eight pilot areas. The results show that, firstly, the policy effects of the eight major pilots are different, that is, different pilots in the national big data comprehensive pilot zone have different effects on the science and technology innovation capacity of surrounding areas, with spatial and regional differences. Second, the heterogeneity analysis results of the national big data comprehensive pilot zones in Guizhou, Beijing-Tianjin-Hebei, Henan, Inner Mongolia, and Shenyang are significantly positive, indicating that the big data comprehensive pilot zone policy has a significant effect on the regional science and technology innovation capacity of these pilots. Third, the heterogeneity analysis results of the national big data comprehensive pilot zones in Shanghai, the Pearl River Delta, and Chongqing are not significant, indicating that the policy effect of the big data comprehensive pilot zones is not obvious in these areas. This article further explores the reasons for this result, which are attributed to differences in local economic development foundations, policy implementation goals, and innovation distribution structures. Based on this, corresponding policy suggestions are put forward. On the one hand, it is recommended to strengthen inter-regional policy coordination and promote the exchange, sharing and integration of innovative resources between regions. On the other hand, for the Pearl River Delta, Shanghai, and Chongqing pilot areas, policy implementation should consider based on the actual development of local science and technology innovation, we will further optimize the adaptability of big data pilot zone policies, ensure the precise implementation of policies, and promote the coordinated development of regional science and technology innovation capacity.