• Restructuring of regional innovation system driven by provincial laboratories: A case study from the Multi-level Perspective
• 2026 Vol. 44 (8): 1569-1580.
• Abstract ( )
• Against the backdrop of China’s evolving science and technology governance, provincial laboratories are established across the country as pivots to bridge central strategies and local implementation, and as important platforms to promote the restructuring of regional innovation systems. Currently, the research regarding the establishment, development paths, and the role of provincial laboratories in driving the restructuring of regional innovation systems have been still relatively under-investigated. To address this research gap, this paper employs the Multi-level Perspective and the Regional Innovation System theory to build an integrated analytical framework. Unlike traditional approaches that view innovation systems as static, this framework particularly focuses on the dynamic interplay and interweaving among multi-level factors, namely, the Macro-level Landscape (national strategy), the Meso-level Regime (regional institutional frameworks), and the Micro-level Niche (technological innovation activities). This framework aims to decode how the institutional construction of provincial laboratories can serve as a process of socio-technical transition and finally lead to the reform of regional innovation systems. To verify this framework, this paper presents a single case study of the Liaoning HH Laboratory, a representative entity situated in a traditional industrial base facing urgent transformation pressures – Liaoning Province. By utilizing triangulated data from semi-structured interviews, participant observations, and internal documents, the study conducts a deep investigation into the case laboratory’s evolution in the area of high-end equipment manufacturing and machine tools. The case analysis reveals that provincial laboratories can act as critical adapters in the regional innovation system. Specifically, the study identifies three distinct paths in the HH Laboratory’s establishment and evolution: (1) Top-down institutional translation: responding to the landscape directives of national strategies, the laboratory was empowered to build a relatively autonomous management structure, which enables the laboratory to effectively convert abstract national strategies into localized exercises, thereby overcoming the previous disconnection between central policies and local implementation. (2) Meso-level demand alignment: by anchoring itself in the regional regime, the laboratory identifies and addresses specific local industrial demand, such as some technological barriers in machine tools, thereby helping tackle the historical misalignment that hindered local university research from supporting regional industrial upgrading. (3) Bottom-up consolidation of innovation activities: focusing on the niche level, the laboratory provides pre-investment and specialized support to consolidate fragmented innovation resources, which facilitates the commercialization of technologies that individual enterprises cannot handle, thereby feeding successful innovation experiences back into the provincial institution to reshape regional policies for technological innovation. With these findings, the case study reveals that provincial laboratories, as important vehicles for exploring new R&D mechanisms at the provincial level, have undertaken multiple functions in responding to national strategies, aligning regional industry-academia needs, and enhancing the efficiency of technology transfer. In this way, the provincial laboratory has effectively transformed the past innovation institution featured with insufficient central-local coordination, weak innovation foundation, and loose organization of innovation entities into a new institution. The analysis of this study indicates that provincial laboratories are not merely local executors of national projects but have become an active hub for multi-level policy coordination. In this sense, they perform an important force for promoting the transformation of regional innovation systems by aligning vertical strategic goals with horizontal industrial needs. The operational mechanisms of provincial laboratories provided an empirical basis and theoretical insights for understanding the on-going changes in China’s science and technology governance system.

• "Building Nests for Phoenixes":Digital Industrial Cluster Building and Enterprises' New Quality Productivity
• 2026 Vol. 44 (8): 1581-1592.
• Abstract ( )
• In the era of rapid global industrial transformation driven by the digital economy, there is an urgent need to cultivate spatial carriers that align with the development requirements of new quality productivity. This paper treats the gradual implementation of China's digital industry cluster pilot policy as a quasi-natural experiment and employs a staggered difference-in-differences (DID) approach to empirically examine the impact of digital industry cluster development on enterprises' new-quality productivity, using data from A-share listed companies between 2011 and 2023. The study finds that: (1) the construction of digital industry clusters significantly enhances enterprises' new quality productivity; (2) mechanism analysis reveals three primary pathways through which digital industry clusters promote productivity improvements: by improving the efficiency of credit and labor allocation to optimize the factor chain, reducing customer and supplier concentration to restructure the supply chain, and fostering integrated innovation to upgrade the innovation chain; (3) heterogeneity analysis shows that the productivity-enhancing effect is more pronounced for enterprises located in the eastern region, those in intellectual property-intensive industries, strategic emerging industries, state-owned enterprises, and smaller-scale enterprises; (4) analysis of spillover effects indicates that the digital industry cluster policy also boosts the new-quality productivity of enterprises in neighboring districts and counties. These findings offer valuable insights for policymakers seeking to promote the development of new quality productivity through the lens of digital industry cluster construction.

• Does Scientific Literacy Influence Individual Climate Change Perception?——An Empirical Study Based on the 2023 Science, Technology and Society Barometer Survey
• 2026 Vol. 44 (8): 1593-1602.
• Abstract ( )
• The scientific literacy of citizens significantly influences individual perceptions of climate change. This paper conducts an empirical study on the relationship between these two variables based on data from the 2023 Science, Technology and Society Barometer Survey. The findings reveal that scientific literacy has a notable positive impact on individuals' perceptions of climate change. Mechanism analysis indicates that improvements in scientific literacy affect climate change perception through increased scientific interest, trust in science, and trust in scientists, thereby exerting a positive influence. Heterogeneity analysis shows that, at the individual level, the positive impact of scientific literacy on climate change perception is greater for males, individuals with a bachelor's degree or higher, and younger individuals compared to females, those with less than a bachelor's degree, and older age groups. At the regional level, scientific literacy positively influences climate change perception in the eastern, central, and western regions, with the degree of influence being strongest in the eastern region, followed by the western and central regions, while the positive impact in the northeastern region lacks statistical significance. Enhancing citizens' scientific literacy and trust in science, thereby guiding behavioral changes to address the global issue of climate change, can be achieved through strengthening climate change education, promoting the practice of low-carbon lifestyles, and building professional scientific communities.

• Risks Intellectual Property Risks and Compliance Strategies on the User Side of Open-Source Foundation Models: A Legal Perspective on License Breach under Open Source Agreements
• 2026 Vol. 44 (8): 1603-1612.
• Abstract ( )
• Current research on the construction and governance of open-source large model ecosystems primarily focuses on macro-level top-level design, with a notable lack of micro-level risk identification and compliance strategies. In the open-source AI ecosystem, diverse actors increasingly participate in model deployment, creating an urgent need for theoretical guidance to support industry compliance practices.This study systematically reviews representative open-source licenses in the global large model domain, identifies intellectual property risks potentially triggered by license breaches, and employs an interdisciplinary "Law-Technology-Intelligence" analytical framework to propose countermeasures.The primary causes of license breach risks include insufficient clearance of rights-related information during the data preprocessing stage, lack of typological understanding of open-source license provisions during application management, misaligned risk recognition, and inadequate control over derivative outputs.At the data preprocessing (upstream) stage, enterprises should implement a full-cycle rights information clearance mechanism integrating technical filtering, responsibility clarification, and data compliance.At the model management (midstream) stage, organizations must account for the typological traits and risk profiles of permissive licenses,restrictive-permissive licenses, and copyleft licenses, and accordingly establish differentiated compliance governance systems.At the content output (downstream) stage, compliance management should encompass four dimensions: data handling, model training, generation control, and user supervision.

• The Operational Logic of Internal Governance in new types of R&D Institutions: An Analysis Based on Complex Adaptive Systems Theory
• 2026 Vol. 44 (8): 1613-1623.
• Abstract ( )
• Abstract: With the deepening implementation of the innovation-driven development strategy, new types of research and development (R&D) institutions, serving as pivotal platforms for the full integration of Industry-University-Research (IUR), play a central role in facilitating the efficient flow of innovation resources, accelerating the commercialization of scientific and technological achievements, and driving industrial transformation and upgrading. Their internal governance directly influences the rational allocation of research resources, the innovative vitality of researchers, and the market-oriented application of research outputs, thereby profoundly influencing the overall effectiveness, resilience, and competitiveness of the national innovation system. However, these institutions are confronted with complex governance challenges, including multi-stakeholder participation, ambiguous organizational boundaries, and dynamically evolving objectives that linear and static governance theories cannot adequately address. While prior studies have examined macro-level issues, such as organizational model innovation and policy support systems, as well as micro-level concerns, including governance structure optimization and incentive design, they have not adequately captured the dynamic interactions among internal governance elements or the underlying mechanisms by which organizations adapt to environmental changes. To tackle these challenges, this study proposes an analytical framework based on the theory of Complex Adaptive Systems (CAS) to investigate the internal governance logic of new types of R&D institutions. We selected six representative domestic and international cases and applied grounded theory methodology to systematically examine their governance practices and optimization pathways. The findings reveal that the internal governance of new types of R&D institutions aligns with a dynamic framework under CAS, characterized by "system identification → stakeholder interactions → resource flows → adaptation mechanisms." This framework elucidates how these institutions attain effective governance and sustainable development in complex environments. In terms of system identification, these institutions implement a multi-tiered framework encompassing institutions, departments, and individual actors, which underpins effective collaboration and enables the strategic allocation of resources. Regarding stakeholder interactions, the internal governance of these institutions operates as a complex adaptive system involving multiple stakeholders, whose effective functioning relies on dynamic interactions both among internal actors and between the organization and its external environment, exhibiting characteristics of complexity and nonlinearity. With respect to resource flows, the sustainability of internal governance depends on the circulation of diverse elements—financial, informational, material, knowledge-based, and human resources—among governance actors and between the institution and its environment. This process ultimately establishes a self-reinforcing cycle in which resource flow drives innovation, which in turn promotes further flow. Finally, concerning adaptive mechanisms, these new types of R&D institutions demonstrate a dynamic capacity to respond to changes in internal and external conditions, which can be conceptualized as a closed-loop process of perception, decision-making, implementation, and feedback. Based on these findings, the study offers the following policy recommendations:(1) Strengthen the construction of system identification to clarify the collaborative orientation among multiple stakeholders; (2) Optimize resource allocation and flow mechanisms to streamline multidimensional interaction channels; (3) Enhance mechanisms for resource circulation to ensure efficient allocation of key elements, (4) Establish a closed-loop adaptive mechanism to improve dynamic responsiveness. These recommendations provide comprehensive and actionable guidance for enhancing the internal governance, innovation efficiency, and long-term strategic development of new types of R&D institutions.

• Identification and Verification of Influencing Factors on the Level of Innovation Consortium Construction in China
• 2026 Vol. 44 (8): 1635-1646.
• Abstract ( )
• Innovation consortia are increasingly recognized as pivotal instruments for advancing research and development activities, fostering collaborative innovation, and sustaining competitive advantages in today’s rapidly evolving technological landscape. In the context of China’s dynamic innovation system, this study investigates the multifaceted determinants that influence the construction level of innovation consortia. By developing and empirically validating an integrated framework, the research endeavors to bridge the gap between theoretical constructs and practical insights, thereby providing valuable guidance. The primary objective of this study is to identify and validate the key factors that underpin the effectiveness and sustainability of innovation consortia in China. Recognizing that innovation is a complex interplay of technical, organizational, and environmental factors, the research emphasizes the significance of strategic alliances, resource integration, governmental support, and inter-organizational dynamics. This investigation holds considerable academic value as it enriches the current literature on innovation management by offering a multidimensional perspective on consortium construction. Furthermore, from a practical standpoint, the study aims to inform decision-makers regarding the optimal allocation of resources and the formulation of policies that can stimulate robust consortium development, ultimately contributing to the enhancement of national innovation capabilities. A mixed-methods approach is adopted to ensure a comprehensive analysis of the influencing factors. This study takes China's innovation consortium as the research object, and comprehensively collects the published data of 1734 innovation consortions. Firstly, the construction situation of China's innovation consortium from 2029 to 2024 is statistically analyzed, and the basic laws of the construction quantity, fields and related policies of innovation consortium are obtained. Secondly, through the three-level coding step of rooted theory, the influencing factors of innovation consortium construction are extracted from the original data. In this process, the three-dimensional theoretical framework of "strategic triangle view" is used for reference to better integrate macro and micro perspectives; Then, taking 356 innovation consortia with listed enterprise members as research samples, random forest algorithm was used to quantitatively verify and rank the importance of factors identified by the rooted theory, and a variety of machine learning algorithms were introduced to test the model. The empirical findings of the study reveal several critical insights. First of all, science and technology human resources have been proved to be the most critical factor to improve the level of innovation consortium construction, and the relatively important factors are the advantages of industrial clusters, market-oriented resources and innovation resources. The second most important is the system of achievement sharing and protection, the upgrading demand of the industry, the basic situation of the industrial chain and the support and incentive system. The importance of institutional factors within innovation consortia is relatively low. In summary, this research offers a timely and comprehensive examination of the influencing factors that determine the construction level of innovation consortia in China. By integrating theoretical perspectives with empirical validation, the study not only enriches the academic discourse on collaborative innovation but also provides actionable recommendations for enhancing the performance and sustainability of innovation networks. The insights derived from this analysis are expected to serve as a valuable resource for both scholars and practitioners seeking to navigate the challenges and opportunities in the contemporary innovation landscape.

• Information Exposure and Threat Situation: An Exploratory Analysis of the Causes of Public Cognitive Polarization
• 2026 Vol. 44 (8): 1647-1657.
• Abstract ( )
• The rapid development of intelligent technologies is propelling humanity toward an intelligent society, bringing about profound changes in production, lifestyle, organizational structures, and social order. These transformations have given rise to numerous new challenges, making the governance of intelligent society an urgent research agenda. While existing studies have addressed key risks associated with intelligent technologies—including algorithmic abuse, the digital divide, and issues of trust and fatigue—relatively less attention has been paid to the transformative impact of intelligent recommendation systems on public information exposure, cognitive patterns, and behavioral preferences. The widespread use of personalized recommendations often results in individuals being repeatedly exposed to homogeneous content, leading to the formation of information cocoons, exacerbating cognitive polarization, and increasing the risk of societal fragmentation. This presents a significant challenge for intelligent social governance. Traditional analyses of public cognition and attitude formation are often based on the rational actor model, assuming that individuals make decisions through cost-benefit calculations. However, such perspectives tend to overlook the psychological and emotional mechanisms involved in information processing. Recent studies from the fields of psychology and behavioral science have begun to explore how emotional preferences, identity, ideology, and personality traits influence the relationship between information exposure and cognitive polarization. Nevertheless, little attention has been given to the role of perceived external social environments, especially perceptions of societal threats. Psychological research indicates that perceived threats in the social environment significantly shape individual cognition and attitudes. In today’s digital landscape, where intelligent technologies dominate, threat-inducing and emotionally charged content is more likely to attract attention and be widely disseminated. This can amplify public anxiety and perceptions of insecurity, thereby intensifying cognitive polarization. Accordingly, this study seeks to bridge the gap by examining how threat perceptions and information exposure interact to influence public cognitive polarization. This paper introduces the perspective of external threat situations and explores how they, together with information exposure, jointly influence public cognitive polarization. Using the application of facial recognition technology in “pedestrian red-light violation exposure” as a case study, this research constructs a 2 (no threat situation vs. threat situation)×2 (homogeneous information vs. heterogeneous information) between-subjects experiment. A total of 1,281 participants were recruited online for the experiment. The results indicate that exposure to homogeneous information strengthens the public’s original views, thereby intensifying cognitive polarization, while exposure to heterogeneous information weakens the public’s original views, reducing cognitive polarization. Compared to the absence of external threat situations, threat situations significantly weaken the depolarization effect brought about by exposure to heterogeneous information. Additionally, for individuals of different genders and average annual incomes, threat situations play varying roles in the process by which information exposure influences polarization. The findings demonstrate that the external environment in which the public is situated, including threat perceptions caused by social unrest, economic crises, crime, disease risks, and unexpected events, may have a significant impact on changes in cognitive polarization during information exposure. This deserves further attention and research. Moreover, when the government addresses viewpoint polarization in cyberspace, it should not only promote the public’s exposure to more heterogeneous information that challenges their original views and encourages diverse thinking, but also pay attention to the external environment the public faces. This can help reduce public anxiety and threat perception, thereby enhancing the role of heterogeneous information in mitigating viewpoint polarization.

• Richard Nelson's Innovation and Development Thoughts and Policy Implications
• 2026 Vol. 44 (8): 1658-1669.
• Abstract ( )
• Richard R. Nelson is founder of modern evolutionary economics and a leading figure in innovation economics. Starting from a critical re-evaluation of neoclassical economics, Nelson pioneered the development of evolutionary theories of innovation, driving a significant paradigm shift in innovation studies. His research spans areas such as corporate innovation, industrial innovation, national innovation systems, and long-term economic growth. Notably, he profoundly elucidated the crucial role of the co-evolution of technology and institutions in long-term economic development from an evolutionary perspective, establishing a vital cornerstone for contemporary theories of innovation and development and policy-making research. To commemorate Nelson's outstanding contributions to innovation studies, this paper systematically reviews his thoughts on innovation development and, based on this, discusses the significant insights they offer for research on innovation and development theory and policy-making in China.

• Information Consumption and Digital Technology Innovation--Evidence from National Information Consumption Pilot Cities
• 2026 Vol. 44 (8): 1670-1680.
• Abstract ( )
• Information consumption, which accelerates the integration of consumption chains with supply chains, industrial chains, and value chains through digital technology, has become a defining feature of digital economic development and a key engine driving high-quality economic growth. To promote information consumption, the State Council issued the “Guiding Opinions on Further Expanding and Upgrading Information Consumption to Continuously Unleash the Potential of Domestic Demand” in 2017. This document emphasized deepening the integration of information consumption with innovation, entrepreneurship, and the “Internet Plus” initiative, while encouraging core technology R&D and service model innovation. The 2021 “Outline of the 14th Five-Year Plan for National Economic and Social Development and the Long-Range Objectives Through the Year 2035” highlighted the need to cultivate new forms of consumption, including information consumption, digital consumption, and green consumption. The 2024 State Council Opinions on Promoting High-Quality Development of Service Consumption called for accelerating the construction and upgrading of information consumption experience centers and launching a series of new information consumption projects. Consequently, advancing information consumption has become a key component of the national innovation strategy. The Ministry of Industry and Information Technology approved 104 national information consumption pilot cities in 2014 and 2015, respectively, deploying pilot initiatives in infrastructure, consumption models, and core technologies to support information consumption development. How, then, do information consumption-driven policies at all government levels simultaneously advance information consumption development and digital technology accumulation while elevating urban digital technology innovation levels? What are their underlying mechanisms? Addressing these questions not only provides a theoretical framework and empirical evidence for evaluating the policy implications of information consumption pilot city development but also offers valuable insights into leveraging demand-driven innovation to enhance urban digital technology innovation capabilities. Drawing upon demand-driven innovation theory, this paper constructs an analytical framework encompassing foundational elements, core entities, and ecosystem effects. It elucidates the potential mechanisms through which information consumption-driven policies empower urban digital technological innovation. Empirical validation employs a multi-period difference in differences model, utilising multiple datasets including urban datasets, patent databases, national tax survey databases, and listed company databases, alongside information consumption pilot policies. Findings reveal that information consumption-driven policies significantly elevate urban digital technology innovation levels. Mechanism analysis indicates these policies drive innovation through multiple pathways: attracting talent clusters, fostering enterprises as innovation agents, and strengthening governmental external ecosystem safeguards. Heterogeneity analysis demonstrates that such policies primarily enhance digital innovation in regions with high marketisation levels, cities below tier-two status, and areas possessing robust digital industrial foundations. Synergy analysis indicates that digital finance, digital economy policies, and information infrastructure support can generate significant synergistic effects with information consumption-driven policies through financial empowerment, policy guidance, and facility support. The findings of this study provide novel and viable pathways for technological innovation in the digital era, offering important insights for unleashing urban digital technology innovation vitality under information consumption-driven frameworks. Based on the above conclusions, this paper proposes the following policy implications: First, refine top-level institutional design and resource support systems to establish standardized policy closed-loop mechanisms. Second, build collaborative innovation mechanisms among talent, enterprises, and government to stimulate endogenous motivation among micro-level entities. Third, implement tailored, tiered advancement strategies based on the distinct resource endowments of different cities.

• Digital intelligence and the solution of the dilemma of "low quality and low efficiency" in enterprise green innovation
• 2026 Vol. 44 (8): 1695-1709.
• Abstract ( )
• It has become an important issue in theory and reality to promote the deep integration of enterprise digitalization, intelligence and greening, and solve the dilemma of green innovation. Based on the listed companies in Shanghai and Shenzhen A-shares from 2014 to 2023, this study explores the impact and mechanism of digital intelligence on enterprise green innovation from the dual perspective of "improving quality and expanding quantity" as well as "enhancing efficiency". The results show that: (1) Digital intelligence can not only promote the quantity and quality, but also improve efficiency, and the conclusion still holds after testing for robustness. (2) The mechanism testing shows that digital intelligence breaks through the green innovation dilemma by optimizing the allocation of innovation resources and reducing information asymmetry and other means. (3) Heterogeneity analysis shows that high environmental regulation areas, high-tech industries, state-owned and large enterprises, digital intelligence plays a more significant effect on the improvement of the green innovation. (4) The effect consequences study shows that the promotion of enterprise green innovation by digital intelligence can further improve the economic, environmental, and social responsibility performance of the enterprise. The conclusion of this study provides useful insights for leveraging digital intelligence to drive enterprise green innovation, achieving the dual-carbon goals and boosting the overall performance of China's innovation system, and shaping new driving forces and advantages for high-quality development of enterprises.

• Research on the influence of AI technology integration on sustainable product innovation
• 2026 Vol. 44 (8): 1710-1720.
• Abstract ( )
• Abstract: Based on the resource orchestration theory, this study examines the mechanisms through which AI technology integration influences different types of sustainable product innovation (SPI) using a sample of 298 firms. It further explores the mediating role of digital platform capabilities. The findings reveal that AI technology integration positively affects both functional and systems SPI, with a stronger impact on systems SPI. AI technology integration also positively influences both consumer and customer digital platform capabilities. Consumer digital platform capability positively affects both functional and systems SPI, with a stronger impact on functional SPI. Customer digital platform capability positively affects both functional and systems SPI, with a stronger impact on systems SPI. Furthermore, consumer digital platform capability mediates the relationship between AI technology integration and functional SPI, while customer digital platform capability mediates the relationship between AI technology integration and systems SPI.

• Pasteur-type scientists, institutional incentives, and industry-academic cooperative R&D
• 2026 Vol. 44 (8): 1721-1733.
• Abstract ( )
• This paper undertakes a systematic review and theoretical synthesis of the mechanisms through which Pasteur-type scientists engage in and catalyze industry-university collaboration (IUC). Moving beyond theoretical exposition, the research is empirically grounded in the practical model of Industry-University Collaborative R&D Centers, a policy-driven initiative prominently adopted by small and medium-sized enterprises (SMEs) within Hubei Province, China. The methodological approach combines a review of extant literature with rich, qualitative data derived from semi-structured interviews conducted with administrators and principal investigators at twelve distinct such centers. This robust methodological foundation enables the construction of a novel, multi-level incentive theory that explicates the drivers of Pasteurian scientific engagement within the complex socio-economic framework of IUC. The theoretical model pivots on two central pillars: the indispensable, agency-like role of the Pasteur-type scientist as a bridge between fundamental inquiry and applied commercial development, and the critical importance of institutional incentive structures designed to augment the innovative output of these partnerships. Quantitative analysis conducted as part of this study yields a compelling finding: collaborative ventures that actively involve Pasteur-type scientists demonstrate a statistically significant enhancement in patent output, with an average increase of 3.512 patents compared to those that do not feature such pivotal figures. This finding underscores the scientist's role not merely as a participant but as a fundamental multiplier of innovation productivity. Delving deeper into the institutional enablers, the theory posits and validates several key moderating factors. Firstly, the organizational transformation of the academic institution itself is paramount. When the host university of a Pasteur-type scientist consciously evolves towards an "entrepreneurial university" model, it institutionalizes support structures that are critical for success. Crucially, this shift involves the implementation of equitable research assessment and evaluation systems that recognize and reward applied research, patent filings, and knowledge transfer activities on par with traditional academic publications. This institutional legitimacy removes a significant barrier to scientist participation and directly correlates with greater collaborative output. Secondly, the micro-level design of the collaboration contract is identified as a direct motivational lever. Agreements that stipulate transparent, equitable, and forward-looking clauses regarding intellectual property (IP) ownership and the sharing of long-term profits/revenues serve as powerful ex-ante incentives. By ensuring that Pasteur-type scientists are not merely compensated for their time but are also granted a stake in the future commercial success stemming from their ingenuity, these contracts align the interests of the individual researcher with the broader objectives of the collaboration, thereby fostering deeper commitment and yielding superior innovation performance. Finally, the macro-level role of government and external stakeholders is emphasized. The research finds that proactive support from local governments, manifested through higher direct subsidies for IUC projects, acts as a crucial risk-mitigating catalyst. Furthermore, government agencies can perform a vital brokerage function by facilitating introductions and attracting greater volumes of social capital and venture funding into these partnerships. This injection of financial and network resources expands the operational scale and ambition of the R&D centers, creating a more fertile environment for the generation of marketable technologies and thus leading to a higher volume of tangible outcomes.

• New Paradigm of User Innovation under Artificial Intelligence: Review and Prospect of Foreign Literature
• 2026 Vol. 44 (8): 1734-1744.
• Abstract ( )
• The paper employ literature review to address theoretical questions related to user innovation under the paradigm of artificial intelligence (AI). It begins by defining AI and user innovation and then conducts a literature search, using specific keywords and inclusion criteria to identify relevant studies. The search strategy is designed to be comprehensive yet accurate, focusing on peer-reviewed studies published in English from 1991 to 2023. The authors use the Gioia methodology for data analysis. This methodology involves three stages: first-order categories, second-order themes, and overall dimensions, moving from a strict focus on empirical data to developing theoretical insights. The purpose of this review is to bridge the gap between AI and user innovation research by identifying key themes and constructing an integrated framework that delineates the reciprocal impact of AI on user innovation and vice versa. The review aims to answer research questions such as "What impact does AI have on user innovation? Why and how can users improve or even innovate AI?" and to pave the way for future research focusing on the interplay of AI, enterprises, users, and multi-actor engagement. The study identifies eight key themes and constructs a comprehensive research framework that provides a systematic understanding of AI and user innovation. The study found that the paths through which AI acts on user innovation include: ①Enterprises identify user innovations through AI; ② AI-driven innovation toolkits; ③AI as a medium reshaping enterprise-user co-creation relationships; ④AI empowering innovation communities; ⑤AI directly participating in innovation as an actor. The paths through which user innovation acts on AI include: ①Consumer users through participatory design. ②Optimizing AI systems through the "human-in-the-loop" framework; ③Enterprise users driving AI innovation through data assets, scenario applications, and multiple roles. The paper enriches existing research results and promotes further research on the bidirectional impact of artificial intelligence and user innovation. It also identifies gaps in the literature and proposes a research agenda to advance innovation in AI users, contributing to the broader literature on user innovation management and providing a foundation for managing AI effectively in enterprises and user innovation processes. We synthesise these findings into an integrative framework that depicts AI and user innovation as a mutually constitutive system. Building on this synthesis, we propose a future research agenda that addresses five under-explored areas: At the firm level, future inquiry should shift from simply using machine learning to identify user insights toward investigating how retrieval-augmented generation and other generative-AI techniques can actively search for, synthesise and integrate user-generated knowledge and solutions. This includes clarifying the new boundaries and governance mechanisms that distinguish AI-native innovation communities from traditional digital ones, and critically examining data-acquisition M&A strategies—such as large firms buying hospitals to secure private health data—by unpacking their strategic motives and the attendant ethical risks of commodifying sensitive patient information. At the user level, in-depth case studies and experiments are needed to tease out the contextual contingencies of AI-driven innovation toolkits, moving AI from a passive “resource” to a co-evolving network actor. Particular attention should be paid to micro-level mechanisms through which (1) employees undergoing digital transformation tinker with or augment AI systems in situ, and (2) individual contributors in open AI communities iteratively refine algorithms via pull requests, issue tracking and human-in-the-loop feedback loops. At the multi-actor ecosystem level, research must go beyond marketing-oriented value co-creation to explore how AI infrastructures mobilise cross-domain collective intelligence in real time. Empirical studies should examine how heterogeneous actors dynamically orchestrate AI capabilities to sense, seize and scale transient digital opportunities within complex, rapidly changing environments.

• Research on the Impact of Local Fiscal Science and Technology Expenditure on Regional Innovation Capacity
• 2026 Vol. 44 (8): 1745-1755.
• Abstract ( )
• As the main participants in regional innovation capacity building, local governments' fiscal science and technology expenditures support basic research, major technological research and the transformation of innovation achievements, playing a role in reducing innovation risks, making up for market failures and enhancing regional innovation capabilities. This paper analyzes the current situation of central and local fiscal science and technology expenditures and the current situation of vertical fiscal imbalance in the three major regions, and then conducts an empirical study and empirical analysis on the impact of fiscal science and technology expenditures on regional innovation capabilities. The research finds that the promoting effect of local fiscal science and technology expenditure on the innovation capacity of the eastern and central regions is significantly greater than that of the western region. Basic research expenditure JCYJ and applied research expenditure YYYJ have a positive incentive effect on the improvement of regional innovation capacity, while technology research and development expenditure JSYJ has a negative effect on the improvement of regional innovation capacity. The vertical fiscal imbalance in the western region plays a significant negative moderating role in the improvement of regional innovation capacity by fiscal science and technology expenditure. Put forward policy opinions on optimizing the structure and scale of local fiscal science and technology expenditure, enhancing regional innovation capabilities, and optimizing the division of fiscal powers and expenditure responsibilities, as well as moderately reducing the level of vertical fiscal imbalance.

• Research on the impact of financial-industrial integration on the new quality productive forces of enterprises
• 2026 Vol. 44 (8): 1756-1768.
• Abstract ( )
• Adversity stimulates transformation, deficiency cultivates diligence, and affluence requires strategic foresight. The combination of production and financing is not only a power source for enterprises to promote new quality productive forces, but also a strategic fulcrum for accelerating the construction of a modernized industrial system and realizing innovation-driven and high-quality development. Existing research focuses primarily on the impact of financial-industrial integration on corporate operating performance, investment efficiency, business risk, and credit availability. However, studies examining the relationship between financial-industrial integration and corporate innovation are relatively scarce. As a crucial mode of financial-industrial integration, enterprise investment in banks reshapes the bank-firm relationship through capital nexus, injecting new impetus into the development of new quality productive forces. Based on the data of Chinese A-share listed companies from 2011 to 2023, this paper examines the impact and mechanisms of industry-finance integration on new quality productive forces of enterprises. It finds that financial-industrial integration significantly improves the new quality productive forces of enterprises, especially improving labor resources and realizing the leap of optimal combination. Mechanism analysis reveals that the combination of industry and finance mainly enhances new quality productive forces by alleviating financing constraints, curbing over-indebtedness and reducing agency costs. Heterogeneity analysis indicates that the effect of financial-industrial integration on firms’ new quality productive forces is more pronounced among firms in the central and western regions, where credit resources are scarce, as well as firms that receive fewer government subsidies, manufacturing firms and small-scale firms. The potential contributions of this paper include the following aspects. First, existing literature focuses on the impact of corporate transformation and development as well as the external market environment on new quality productive forces. However, few studies analyze how to enhance enterprises’ new quality productive forces from the perspective of financial-industrial integration. This paper examines the relationship between financial-industrial integration and new quality productive forces of enterprises, thereby enriching the field of new quality productive studies. Second, this paper investigates the mechanisms through which financial-industrial integration promotes the development of enterprises’ new quality productive forces from the perspectives of alleviating financing constraints, curbing over-indebtedness, and reducing agency costs. It provides a theoretical basis for accelerating the cultivation of enterprises’ new quality productive forces. Third, this paper analyzes the heterogeneous effects of financial-industrial integration on the development of enterprises’ new quality productive forces under varying regional and enterprise-specific characteristics. By considering these differences, it provides valuable insights for enterprise strategic decision-making and policy formulation. Based on the above findings, this study provides a theoretical foundation and policy implications to support enterprises in holding shares in non-listed banks and accelerate the development of new quality productive forces. The following recommendations are proposed in this paper. First, policy mechanisms should be optimized to actively promote financial-industrial integration among enterprises. This can be achieved through two key measures: gradually relaxing equity holding limits and developing differentiated policy frameworks. Second, industry supervision should be strengthened to regulate enterprise shareholding behaviors. Third, enterprises should optimize their strategic layout for financial-industrial integration to accelerate the cultivation of new quality productive forces.

• Research on Pathways for Enhancing the Effectiveness of the Science and Technology Talent Policy System: From the Perspective of "Individual-Organization" Interaction
• 2026 Vol. 44 (8): 1769-1782.
• Abstract ( )
• The orderly operation of the science and technology (S&T) talent policy system constitutes a fundamental guarantee for the construction and governance of high-level talent hubs. However, the intrinsic interaction mechanisms among the constituent elements within this system remain inadequately explored and require further revelation. To address this gap, this study leverages panel data from the Mainland Chinese city cluster within the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) spanning the period 2007–2021. Employing an integrated methodological approach that combines dynamic fuzzy-set Qualitative Comparative Analysis (fsQCA) and BERTopic machine learning, the research investigates the synergistic effects of key factors—namely innovation motivation, innovation capability, innovation emotion, and institutional environment—on enhancing the level of orderly operation within the S&T talent system. This investigation is grounded in an "individual-organizational" interaction perspective and systematically explores these dynamics across both temporal and spatial dimensions. The analysis yields several significant findings. Firstly, the orderly operation of the S&T talent policy system manifests through multiple pathways underpinned by complex mechanisms. Five distinct configurations were identified: a "motivation"-dominated synergy-driven type; an "emotion"-dominated regulation-driven type; a "motivation-emotion"-dominated synergy-driven type; a "motivation-capability"-dominated synergy-regulation-driven type; and a multi-factor synergy regulation-driven type. Crucially, within these five pathways, none of the individual or organizational factors alone constitutes a necessary condition for achieving a high degree of system orderliness. Instead, the research reveals the existence of equifinality—equivalent substitutability—between specific condition combinations. Notably, substitutable relationships exist between "motivation-driven" mechanisms and "regulatory intensity," between "emotion-driven" mechanisms and "interdepartmental coordination," and between the combination of "capability cultivation + interdepartmental coordination + regulatory intensity" and "emotion-driven" mechanisms. Among these, motivation-driven mechanisms consistently emerge as a core condition across multiple pathways, playing a pivotal role in achieving high system orderliness.Secondly, weak innovation motivation coupled with low regulatory intensity is identified as a primary constraint negatively impacting the orderly operation of the S&T talent policy system. Thirdly, the development trajectory of this system within the GBA's Mainland city cluster exhibits significant time effects, with 2013 and 2017 serving as critical inflection points. Heterogeneous pathways observed prior to these nodes consistently converged towards states characterized by high consistency and stability thereafter. Fourthly, distinct regions demonstrate differentiated realization pathways for achieving system orderliness, highlighting the significant influence of specific contextual conditions on the effective configuration of factors. From a theoretical perspective, this research offers novel contributions. By adopting the "individual-organizational" interaction lens, it focuses on micro-level elements influencing S&T talents—specifically individual innovation motivation, capability, and emotion—thereby revealing the synergistic mechanisms operating between conditions at the individual and organizational levels. Furthermore, grounded in the theory of policy attention allocation, the study clarifies the equifinal relationships among key elements, systematically delineating both the core conditions and the substitutable pathways essential for realizing the orderly operation of the S&T talent policy system.From a pactical perspective, the findings provide actionable insights for policymakers. Decision-makers should prioritize "motivation-driven" mechanisms while also flexibly utilizing the identified equivalent substitutability relationships to optimize the allocation of policy attention. Crucially, capability cultivation is not a universally applicable key mechanism, its effectiveness is contingent upon regional economic, social, and cultural environmental factors. During policy design and implementation, policymakers must simultaneously address individual talent needs and organizational synergy mechanisms to ensure the policy system operates sustainably and efficiently.Consequently, the conclusions provide robust theoretical support and concrete policy recommendations aimed at enhancing the operational effectiveness and governance of S&T talent policy systems.

• Science and Technology Backyard: History, Significance and Future Direction
• 2026 Vol. 44 (8): 1783-1792.
• Abstract ( )
• Abstract:The Science and Technology Backyard is a new exploration in the process of agricultural modernization with Chinese characteristics. The model of Science and Technology Backyard pioneered by universities in China recently has Reshaped the agricultural technology extension service system，providing effective assistance for small-scale farmers around the world to shake off poverty and increase income. The Science and Technology Backyard dates back to the rural construction movement during the Republic of China period. It originates from the establishment of the Quzhou Experimental Station of China Agricultural University and the construction of agricultural technology promotion network. Since its birth in 2009, the Science and Technology Backyard in China have gone through three stages, namely, exploration, growth, and development. In the new era, the Science and Technology Backyard has positive significance, becoming a new handle to promote comprehensive rural revitalization, a new tool to cultivate new agricultural productivity, a new practice to integrate education, science and technology, and talents as well as a new Platform to Implement key core technology research in agriculture. In the future, the development of Science and Technology Backyard will present five major trends, namely, diversified participation forces, clustered spatial layout, internationalized brand influence, professionalized service functions, and digitalized operation and management.