Amidst the global digital wave reshaping international trade patterns, cross-border e-commerce is undergoing a paradigm shift from factor-driven to innovation-driven development. This study employs Chinese cross-border e-commerce enterprises as research subjects, constructing a dynamic threshold evolution model grounded in self-organized criticality (SOC) theory to systematically unravel the nonlinear mechanisms through which industrial chain innovation element agglomeration enhances corporate competitiveness. Empirical findings reveal: (1) Cross-dimensional synergy of innovation elements within industrial chains significantly amplifies corporate competitiveness, demonstrating multiplier effects from deep integration of innovation chains and industrial chains; (2) Increased international network density as a moderating variable elevates marginal effects
of innovation element agglomeration, confirming globalization embeddedness as a catalyst for innovation diffusion; (3) Market access demonstrates significant dual threshold effects. When institutional barriers transcend the critical threshold, self-organized criticality evolution is triggered, resulting in exponential leaps in the impact of industrial chain innovation levels on corporate competitiveness. This research provides theoretical insights for cross-border e-commerce enterprises to overcome developmental bottlenecks.

This study takes the typical intelligence research products of well-known foreign think tanks as research cases, and analyzes several aspects such as the information sources, release time, and utilization characteristics of the open source information they adopt. It summarizes the methods and processes of developing and utilizing open source information, and based on current needs and the characteristics of open source information, it proposes a process for the development and utilization of foreign open source information in China’s intelligence work, with the aim of providing certain references for the research of open source intelligence in China.

The copyright compliance of training data for generative artificial intelligence represents a common challenge in global industrial governance. This paper takes the U.S. court rulings in the 2025 cases of Bartz v. Anthropic and Kadrey v. Meta as its starting point, employs a combination of case analysis and comparative legal research to systematically deconstruct the judicial application logic of the fair use doctrine in the context of generative artificial intelligence training data. The study finds that although the U.S. judicial practice acknowledges the rationality of using AI training data in individual cases, its adjudication highly depends on specific case facts, exhibiting significant characteristics of case-by-case discretion. Notably, judges have universally expressed profound concerns about potential market impacts in their rulings and have reserved room for adjustment in future jurisprudence at the legal theoretical level. This judicial model, characterized by the coexistence of limited exemptions and systematic uncertainties, provides an important reference for the governance of artificial intelligence data.

Mr. Rob van Kranenburg is a speaker at the “2025 Shanghai Competitive Intelligence Forum”. With his authorization, this article is written based on his speech and the content of his new book Statecraft and Policymaking in the Age of Digital Twins: Digital Democracy and the Internet of Things. Against the backdrop of the convergence of technologies such as the Internet of Things, artificial intelligence, and 6G communications, this article explores the profound transformation of contemporary urban governance from the “smart city” to the “wise city”. The article first analyzes how cities, in an environment where objects, machines, and artificial intelligence are deeply interconnected, can upgrade governance models by leveraging data perception and systemic decision-making. It then examines the dilemmas and challenges faced by social governance in today’s digitalization process—particularly the limitations of the Western “entrepreneurial government” model and its intrinsic association with the rise of populism. Finally, the article proposes a pathway for the evolution from an “entrepreneurial government” toward a “co-creative ecosystem”, emphasizing a new governance paradigm centered on “event identity”, key value indicators (KVI) , and a polycentric governance architecture. The article argues that the future of urban governance is not merely a matter of technological integration but also a deep fusion of cognitive frameworks, institutional designs, and humanistic values. At its core is the construction of a systemic decision-making mechanism that is both responsive to real-time data and grounded in public rationality. This governance mindset offers new insights and reference points for research and practice in urban competitive intelligence: as cities and industries operate in increasingly technological and real-time modes, competitive intelligence must not only capture surface-level innovation trends but also penetrate the underlying logic of systemic transformation. It must not only analyze data but also understand the governance structures and social risks behind the data. Such systemic thinking will empower intelligence analysts to grasp the coupling relationship among information, power, and value in the technology driven city of the future, providing deeper cognitive support for strategic decision-making. It must be noted that the discussions in this article are based on the European context, and the relevant conclusions or viewpionts may have certain contextual limitations.

With the development of green economy, China has formulated a number of policies on the promotion and application of new energy vehicles. The market share of new energy vehicles is increasing, and it is very important to identify their competitors and competitive products referred to as “competitiors”. The purpose of this study is to construct a competitive product identification model for new energy vehicles by using multi-source reviews with complementary advantages. The co-occurrence analysis method and the sentiment analysis method are used to construct a new energy vehicle competitive product identification model consisting of four modules: data collection and processing, preliminary screening of competitive products, identification of competitive products and analysis of competitive products. The Xiaomi SU7 new energy vehicle is taken as an example for empirical analysis. Using this model to analyze the competitive products of Xiaomi SU7, on the one hand, the advantages and disadvantages of Xiaomi SU7 are identified, and on the other hand, the core competitive products of Xiaomi SU7 are identified, and the effectiveness of the model is verified.

Since the China-US friction, trademark litigation has become a significant factor restricting the overseas development of Chinese enterprises. During the period from 2019 to 2023, the number of trademark litigation cases involving China has been on the rise, with Chinese enterprises often being defendants and the rate of default judgments remaining high. This predicament stems from both internal and external factors: externally, there are challenges such as targeted policies from the US government, judicial environment bias, and differences in legal systems; internally, there are shortcomings like lagging strategic awareness, incomplete management systems, and weak litigation response capabilities. Addressing these issues requires a systematic solution, including optimizing trademark layout and enhancing litigation response capabilities at the enterprise level, and at the national level, building a multi-level rights protection service system for cross-border cases.

在推进中国式现代化的征程中，科技是开路先锋，上海作为“先头部队的尖兵部队”，肩负着抢占全球创新制高点的重任。面对技术变革风起云涌、机遇窗口转瞬即逝的复杂局面，战略敏捷性成为上海加快建设全球科创中心的核心能力。而开源科技情报，正为锻造这一能力提供了关键支点。

From October 21 to 23, 2025, the 2025 Shanghai Competitive Intelligence Forum (SCIF 2025) was successfully held in Shanghai. The forum, themed “Intelligence for Future Cities” brought together experts and scholars from various fields such as international organizations, research institutions, and industry to jointly explore the cutting-edge trends in urban governance and development in the new era. The event not only showcased applications of technologies such as artificial intelligence in city management but also focused on systematic enhancement of urban cognitive capabilities, emphasizing the profound value brought about by the integration of technology and decision-making mechanisms. Building an urban cognition system centered on technology and intelligence is becoming a key pathway to strengthen strategic capacities and sustainable competitiveness of cities. This article reviews the forum’s core topics and insights, offering an intelligence-driven
perspective to interpret the logic and trends of future urban development, providing useful ideas and references for city policymakers, researchers, and practitioners in related industries.

Cities serve as crucial strategic spaces for modern intelligence work. This study on programmable urban intelligence empowerment aims to deepen the understanding of intelligence service models and operational mechanisms within the context of emerging urban spatial forms, and offer theoretical support and practical insights for intelligence practices in the era of digital and intelligent urban governance and development. First, by integrating the programmable characteristics of cities with the digital development trends of intelligence work, the study systematically analyzes their coupling relationship and mutual needs. Second, it explores the highlights and leverage points, key areas and challenges of programmable urban intelligence empowerment, clarifying the underlying logic and strategic levers of such empowerment. Finally, it proposes practical paths from three dimensions of anchoring empowerment tasks, strengthening empowerment support, and cultivating empowerment ecosystem. The findings reveal that the practice of intelligence empowerment in programmable
cities can be advanced through multiple synchronous and asynchronous pathways “synch ronous + asynchronous” to anchor empowerment tasks; through combined technological and data-driven approaches “technology + data” to consolidate empowerment support; and through adaptive and reform-oriented measures “adaptation + reform” to nurture the empowerment ecosystem.

In an era marked by global intensifying competition and rapid advances in digital and artificial intelligence technologies, provincial science technology information institutions must explore new development strategies. This research undertakes a comprehensive investigation of 30 provincial-level science and technology information institutions, systematically evaluates their data resource management, platform infrastructure development, and service implementation practices to diagnose existing barriers in the innovation and development process of provincial science and technology intelligence institutions. Drawing upon Qian Xuesen’s systematic science philosophy, the study formulates a “six-dimensional integrated” developmental architecture: multi-sourced data aggregation, intelligent service platform construction, diversified service content, personalized service provision, adaptive service modeling, and ecosystem-oriented system development, thereby establishes a holistic roadmap for institutional advancement in the digital and intelligent age.

In the evolving judicial landscape where the logic of “information as evidence” is increasingly emphasized, library and information institutions are gradually transforming from traditional information intermediaries into litigation support actors in intellectual property (IP) disputes. Using three representative cases involving the Shanghai Library, this paper examines how such institutions contribute to evidentiary construction in trademark infringement through generic term validation, in design patent infringement through image-to-text retrieval, and in utility patent infringement through specialized data acquisition. It systematically analyzes the practices by which information is effectively transformed into admissible evidence and distills four operational principles: Timeliness of Retrieval Boundaries, Priority of Source Credibility in Literature Acceptance, Precise Semantic Translation, and Optimization of Collaborative Interfacing. The study offers a practical paradigm for expanding the judicial support functions of library and information institutions, and provides a strategic reference for professionals seeking to maintain technical relevance and institutional value amid the growing prevalence of AI in the digital era.

在市场经济中，科技情报既是事业也是产业，科技情报服务既有公共产品、准公共产品，也有为市场主体提供的私产品。科技情报产业是科技服务业的重要组成部分之一。科技服务业是运用现代科学知识和技术手段。围绕科技创新全链条发展、科技成果高效率转化，向社会提供智力服务的新兴产业，是现代服务业的重要组成。国家高度重视科技服务业的发展问题。

As market competition intensifies and corporate intelligence activities proliferate, enterprises have placed greater emphasis on the protection of intelligence assets, leading to heightened intelligence games among them. This paper aims to explore the evolutionary process and influencing factors of competitive intelligence game strategies among enterprises based on evolutionary game theory. By analyzing the evolutionary stable strategies of the game system and the influence degree of different parameters, and validating the results through numerical simulations, the research findings indicate that the initial state of strategic choices made by two competing parties and the changing trends of key parameters values have significant impacts on the evolutionary stable state. Specifically, an increase in the benefits of providing truthful information has a notable positive effect on achieving strategic equilibrium, whereas an increase in the benefits derived from providing false intelligence has a negative impact. Finally, relevant suggestions are proposed to facilitate cooperation in competitive intelligence among enterprises.

The rapid diffusion of digital technologies is profoundly transforming urban governance. Digital governments and smart cities have become central policy paradigms for improving administrative efficiency, rationalizing public service provision, and enhancing citizens’ quality of life. Digital government deploys big data, artificial intelligence (AI) and related tools to strengthen the efficiency and transparency of public services and promote the intelligent and evidence base of government decision-making, while smart cities integrate the Internet of Things (IoT), cloud computing and other advanced technologies to elevate the intelligent level in multiple fields, including urban infrastructure construction, traffic management and environment protection. To explore in depth how these technologies drive future urban governance, taking advantage of the opportunity of the 2025 Shanghai Competitive Intelligence Forum held in Shanghai in October, our magazine conducted an interview with Lee Sungho, the director of the AI and Big Data Laboratory at the Seoul Institute in South Korea, who was a guest at the forum. This interview systematically analyzes his assessment of digital government and smart city development in Seoul, and explores how AI and big data play a key role in enhancing urban governance capacities, optimizing public services and improving the quality of life for citizens, aiming to provide references for the digital transformation of governments in China and other countries. The edited interview transcript is presented below, with annotations added by the editors.

The Australian Center on China in the World (CIW) is a world-renowned university affiliated think tank with China as its research object. It has its own characteristics in organizational structure, personnel composition,operation mode, research purpose, research field, research method, achievement transformation, talent training,influence building and other aspects. This also makes CIW an excellent think tank with world influence. The construction and development of CIW has certain reference and enlightenment significance for the construction of the university affiliated think tanks in China, which is conductive to the optimization of the university affiliated think tanks in China in the aspects of target positioning, team optimization, financial support, brand building,and so on, and then enhance the world influence of China’s university think tanks.

After World War II, the focus of international competition gradually shifted from the military sphere to the economic and technological domains, prompting many countries to construct economic and technological intelligence systems suited to their own needs. The Soviet Union, France, and Japan each pursued distinct explorations in this regard. In Europe during the 1970s, a relatively unique school of economic and technological intelligence emerged. Represented by Stevan Dedijer, this school advanced the concept of “social intelligence”, which exerted a profound influence on the economic and technological intelligence practices of developing countries. The academic recognition and dissemination of this idea owed much to the efforts of information scientist Blaise Cronin. This “thinker–communicator” mode of collaboration reveals a core theme in the development of economic and technological intelligence: how to construct bridges between scholarship and practice. Although Dedijer’s ideas lacked systematic writings, his advocating, training, and consulting services influenced other schools of thought, including those in French economic intelligence and American competitive intelligence, and highlighted the urgency of developing economic and technological intelligence in developing countries. Cronin, by contrast, ensured the preservation, circulation, and integration of these ideas into the academic literature system through academic research and documentation. This intersection of the two not only aligns with the principle that theory originates from practice but also holds unique significance. In the process of knowledge production and retention, the importance of systematic articulation and dissemination mechanisms is often no less significant than originality itself. Today, the development of economic and technological intelligence in China faces new challenges brought by the impact of artificial intelligence and the risks of geopolitics, while the division between theory and practice has become increasingly prominent. Against this backdrop, revisiting this episode of intelligence history and reflecting on how to reconstruct a system of “theories of economic and technological intelligence in practice” is of critical contemporary relevance.

Digital natives are a group with high information literacy and are more likely to engage in online health information seeking behavior. In order to meet the health needs of “information disadvantaged groups”such as the elderly and indirectly contribute to the development of the Healthy China strategy, this study investigates the impact of information framework on digital natives in different states of surrogate seeking intention and behavioral decision-making, aiming to explore what kind of information can promote frequent and scientific surrogate seeking. Using experimental methods, we conduct positive and negative information framework interventions on digital natives to explore whether the framing effect can promote their surrogate seeking intention and generate behavioral change decisions. The research results show that information framework can enhance the surrogate seeking intention of digital natives for health information; the gain frame is more effective than the loss frame in promoting the surrogate seeking intention of digital natives; information acceptance plays a mediating role in the impact of information framework on the surrogate seeking intention of digital natives; the surrogate seeking intention of digital natives can significantly promote the generation of their behavioral change decisions.

To systematically analyze the current research landscape of open science practice, this study employs a bibliometric analysis base on the Web of Science and core databases of China National Knowledge Infrastructure (CNKI), quantitatively revealing the differences between domestic and international research. It further integrates the innovation diffusion theory and the Technology-Organization-Environment (TOE) framework to construct a “dynamic-static combination” analytical model. Key findings include:（1）Technology Dimension: The adoption of technology in research exhibits a dual characteristic of demand-oriented compatibility principle (gradual integration of existing technologies) and pragmatism (emphasis on immediate effectiveness), driven by both “top-down” (government governance) and “bottom-up” (public participation) forces.（2）Organization Dimension: The analysis primarily centers on three key entities. The state/government assumes the core role in governance and policy implementation; research institutions/personnel serve as the main actors fostering practice and culture cultivation; society/the public act as deep participants, promoting scientific democratization through mutual empowerment.（3）Environment Dimension: Risks involved in the research are systematically distributed across the physical layer (technological ethics, infrastructures and talents), network layer (international competition, resource allocation), application layer (incentive-evaluation contradictions, personal concerns), and policy layer (lack of top-level design). The environmental representation manifests as the evolution of the research paradigm towards open innovation research (emphasizing transparency, sharing, and collaboration), and the reshaping of collaborative models towards an open innovation ecosystem (characterized by co-opetition and symbiosis among multi-dimensional actors).

Strategic emerging industries serve as a critical carrier for accelerating the development of new-quality productive forces, and large-scale industrial classification of enterprises constitutes a fundamental task for formulating industrial policies. To address the issues of high cost and low efficiency in conventional manual screening, an industrial classification method based on bidirectional enhancement of text data and label semantics is proposed. First, to deal with the limited training samples and unbalanced categories, we augment the textual corpus through a suite of data-enhancement strategies to increase data diversity and rectify categories imbalance. Secondly, according to the industrial definitions formulated by industry authorities, we enrich label semantics by introducing external domain knowledge, thereby expanding the semantic coverage of the labels and improving their semantic
expression capabilities. Finally, Cross-Attention mechanism is employed to achieve deep semantic interactions between text and labels which helps better capture key semantic features in text data and strengthen the intrinsic semantic alignment between text and labels, thus improving model performance. Experimental results show that the proposed new method achieves a performance improvement of more than 3.5% compared with traditional baseline models in the application of industrial classification task of three leading industries in Shanghai.

The legalization of inducement prize mechanisms for science and technology in China remains at a preliminary stage of exploration. This paper examines the origins of the inducement prize system in the United Kingdom, with a particular focus on the “Longitude Act” as an institutionalized legal framework, its development and transformation during its validity, the role of the Board of Longitude, and the establishment and eventual abolition of the Longitude Prize. In the 21st century, the UK reintroduced inducement prizes, reflecting both the expansion of contemporary technology inducement prize and innovation competitions—extending from scientific challenges to broader societal issues—and the indispensable role of third-party organizations in their implementation. A comparative analysis of the system’s historical and contemporary development suggests that the diminishing direct role of government, the enhanced functions of specialized institutions, the establishment of evaluation committees, the use of media for project dissemination, and the clarification of assessment criteria have all served as key drivers in the evolution of the inducement prize system.

Policy comparison research has widely adopted a range of intelligence analysis methods. However, existing studies often separate macro-level textual similarity analysis from micro-level analyses of policy tool and thematic structures. This separation overlooks the interconnections between analytical levels and, to some extent, limits the overall effectiveness of policy intelligence analysis. From the perspective of intelligence studies, this paper proposes an integrated methodological framework that leverages large language models (LLMs) to enable coordinated macro–micro comparative analysis. Taking China’s new energy vehicle (NEV) policy as an empirical case, the study examines the feasibility and validity of the proposed approach. The results indicate that the policy comparative texts generated by LLMs perform well in terms of readability, informational richness, and content completeness, although a certain degree of score convergence is observed in similarity assessments. The proposed method provides empirical evidence for the application of large language models in policy comparative research while offering new analytical perspectives and methodological tools to support systematic policy analysis by intelligence researchers and policymakers.

“十五五”时期是我国基本实现社会主义现代化夯实基础、全面发力的关键时期，也是实现高水平科技自立自强、建成科技强国、以科技现代化支撑引领中国式现代化的关键时期。党的二十届四中全会审议通过的《中共中央关于制定国民经济和社会发展第十五个五年规划的建议》对“加快高水平科技自立自强，引领发展新质生产力”作出了专章部署。这对“十五五”时期我国科技情报行业的高质量发展提出了要求，即必须实现从“支撑服务”到“前瞻引领”的根本性转变，其核心路径可以概括为——构建一个以“开源智慧、自主协同”为特征的新型国家科技情报体系。

Against the backdrop of escalating China-U.S. technological competition and the deepening strategic contest within the global semiconductor industry, the boundaries and risks associated with technical intelligence activities have become highly concerned issues by international community. In 2025, China’s Ministry of Commerce included the Canadian company Tech Insights and its related entities in the “Unreliable Entity List”, marking a significant shift in China’s countermeasures in the semiconductor sector—from primary restrictions focused on hardware and equipment level to broader controls over technical intelligence and information flows. This move has triggered extensive discussion across both industry and academia. Taking the sanctions against Tech Insights as a point of departure, this article outlines the company’s business model and development trajectory, and examines how its practices in chip reverse engineering and technical intelligence services diverged from internationally recognized commercial norms and professional ethics. The article further analyzes the underlying drivers of these practices and their adverse impacts on global semiconductor innovation ecosystems as well as industrial and supply chain security. It argues that amid intensifying great-power rivalry and the rise of techno-nationalism, technical intelligence activities—traditionally regarded as commercially neutral—are increasingly being toolized and embedded within strategic competition frameworks. Under such conditions, reliance on market mechanisms solely is insufficient to reconcile the growing tension between security and development. Focusing on the question of how technical intelligence can be used legally and in compliance with regulations in an environment of heightened international competition, the article advances targeted policy recommendations. It emphasizes the importance of accelerating the establishment of a national-level international regulatory framework for competitive intelligence that is compatible with globalization and grounded in the principle of mutual benefit. Such a framework would provide critical support for maintaining fair competition and promoting international technological cooperation, and thus holds significant practical relevance and policy value.

Recognized as a core driver for enhancing scientific and technological productivity, artificial intelligence (AI) has been incorporated into China’s major national strategies. Both central and local governments have rolled out supporting policies, propelling the “AI+” initiative to integrate AI across diverse fields. This study analyzes a sample of 450 central and local AI policies from the PKULAW database and official releases (2017-2024). By employing the BERTopic model and the policy modeling consistency (PMC) index model, it comprehensively evaluates the characteristics, thematic focus, and efficacy of these policies across three dimensions: textometrics, content mining, and policy evaluation, thereby quantifying their coordination degrees. Findings indicate regional differences and imbalances, yet reveal high consistency and effective coordination between central and local policies, with joint priorities on the research and development and application of next-generation AI technologies, education promotion, medical devices, and talent cultivation. Central policies demonstrate the highest efficacy, with the eastern regions outperforming the central and western regions. This research clarifies the degree of central-local policy coordination, provides a reference framework for other domains, and holds pivotal significance for advancing AI industrial development and supporting national strategic objectives.

In order to improve the quality and competitiveness of professional talent cultivation in biological breeding in China, and to better support the national seed industry security strategy and the construction of a strong agricultural modernization country, this study, from the perspective of competitive intelligence, utilizes methods such as literature review, interviews, and comparative research to analyze the differences in organizational models, curriculum design, and teaching approaches of biological breeding disciplines among A5 alliance universities. Additionally, it investigates the underlying issues in the construction of biological breeding disciplines in Chinese higher education institutions. Based on these findings, the study offers the following recommendations for the construction of biological breeding disciplines in agricultural universities: Initiate interdisciplinary talent training programs and reinforce the ethos of collaborative research between teachers and students; refine the curriculum of advanced interdisciplinary courses and heighten awareness of ethical considerations and intellectual property rights in science and technology; establish a seamless integration of industry, academia, research, and application in the talent cultivation process, and enhance the mechanisms for collaborative training between universities and enterprises.

Taking the Shanghai special exhibition industry as a research sample, this study explores the evolutionary process and ecological landscape of the industry from both diachronic and synchronic perspectives, under the framework of “co-opetition.” The Shanghai special exhibition industry, which first emerged in the early 2010s, has experienced rapid expansion and differentiation before the COVID-19 pandemic, and is now entering a new stage characterized by both phenomenal explosion and structural adjustments coexist. A diverse ecological structure, built by authoritative leaders, innovative disruptors, professional operators, and ecosystem co-builders, constitutes the complex competitive and cooperative landscape of the Shanghai special exhibition industry. The study suggests that future development paths for the special exhibition industry require abandoning zero-sum thinking and shifting towards win-win cooperation, with differentiated positioning among different entities to achieve an upgraded “multi-party co-construction” model.

情报的本质是消除或建构信息不对称，其最终目的是影响决策者的认知与选择。不过，情报对决策者的影响，可能并非简单的“情报输入—决策输出”的线性过程，而是决策者将获得的情报与其已有的信息知识结构和自有的认知框架叠加之后的结果，所以本质上，情报是通过潜移默化地重塑决策者的认知框架来影响决策的。