Studies in Science of Science 科学学研究 is a comprehensive academic journal founded in 1983 and originally sponsored by the Chinese Society for Science of Science and S&T Policy Research. It is now jointly run by the Chinese Society for Science of Science and S&T Policy Research, the Institutes of Science and Development of the Chinese Academy of Sciences, and the Research Center for Science, Technology and Society of Tsinghua University. Studies in Science of Science is an interdisciplinary journal that examines science, technology, and innovation in close connection with economic, business, and management development. The Issues focuses on major national policies and widely debated events in science and technology innovation, especially their economic and industrial implications. It promptly presents academic viewpoints, the latest research progress, and policy recommendations including those related to industrial upgrading, innovation-driven growth, and science-and-technology governance that affects firms and markets. The “Theory and Methods” column takes science, technology, innovation activities and related economic and managerial phenomena as its core research objects. It highlights cutting-edge theoretical frameworks and methodological advances, encouraging contributions that integrate innovation studies with economics, management science, business strategy, industrial organization, and evaluation methods, thereby promoting theoretical and methodological innovation in these intersecting fields. The “Innovation Exploration” column is grounded in real-world practices of science and technology innovation at the levels of firms, industries, regions, and innovation systems. Using empirical research, it seeks to distill new insights from practice such as R&D management, entrepreneurship, digital transformation, technology transfer, and open innovation and to refine innovation theory with explicit attention to business models, organizational behavior, and performance outcomes. The “Frontiers and Perspectives” column takes global trends and frontiers in science and technology development as its background, examining new dynamics and their major impacts on economic structures, industrial competition, and business ecosystems. It focuses on strategies and policies for science, technology, and innovation development, and encourages authors to propose new ideas and forward-looking views whether at the level of national STI policy, regional innovation systems, or firm-level strategy as well as to engage in critique and debate that contribute to academic and practical progress. Studies in Science of Science is a monthly journal and can be subscribed to throughout China. International Standard Serial Number (ISSN): 1003-2053. Domestic Serial Number (CN): 11-1805/G3. Domestic postal distribution code: 82-315.
Editorial Department of Studies in Science of Science
Can Generative AI Improve Corporate Values, Employee Perceptions, and Organizational Practices? A Human-Centric Case Study of Project Management SMEs in Indonesia
This study investigates the growing role of generative AI tools, particularly ChatGPT, in the context of Indonesian SMEs, with a focus on their influence on SMEs values, employee perceptions, and organizational practices. Adopting a mixed-methods approach, the study combines a literature review, two industry workshops, and a survey involving 52 professionals from various sectors. The analysis integrates thematic interpretation of qualitative data with an exploratory quantitative assessment. The findings reveal that 74% of respondents reported mixed or negative attitudes toward AI adoption, mainly due to concerns related to job security and data privacy, even though many acknowledged its potential to enhance productivity and support business automation. Furthermore, 42% of participants perceived positive changes in corporate values following the introduction of AI tools, while strong agreement emerged regarding the usefulness of generative AI in business planning, monitoring and control, and organizational integration. Although several statistically significant relationships were identified, including differences in AI use across types of organizations and work functions, these results should be interpreted cautiously because of the limited sample size. Overall, the findings underscore the need for Indonesian SMEs to balance the efficiency gains offered by generative AI with ethical considerations, human supervision, and targeted capability development. This study contributes to the growing discussion on digital transformation by offering early empirical evidence on how generative AI is beginning to reshape managerial practices, employee responses, and organizational culture within SMEs in Indonesia.
Copyright (c) 2026 Studies in Science of Science https://creativecommons.org/licenses/by-nc/4.0
Assessing the Contribution of Green Finance and Digital Economic Development to Regional Carbon Emission Mitigation
This study examines the relationship between green finance, the digital economy, and efforts to reduce carbon emissions. The analysis employs a comprehensive dataset covering the period from 2010 to 2022, collected from thirty-one provinces, autonomous regions, and municipalities across China. The findings reveal several important insights. First, green finance plays a significant role in promoting regional carbon emission reduction. Similarly, the development of the digital economy also contributes to lowering regional carbon emissions. Furthermore, green technology innovation serves as a key moderating factor in the relationship between green finance and carbon emission mitigation. The results also indicate the presence of a threshold effect in the influence of green finance on regional carbon emission reduction, with varying impacts depending on regional population size. In addition, the contribution of green finance to carbon emission reduction differs across regions, with the strongest impact observed in western China, followed by the central region, while its effect in the eastern region is relatively weaker. Likewise, the digital economy demonstrates regional variations in its influence on carbon emission reduction, showing a stronger contribution in eastern regions, whereas its effect appears less pronounced in the central and western regions.
Insurance Market Development, ICT Diffusion, and Economic Growth in Sub-Saharan Africa
This study extends the existing literature by examining the mediating role of information and communication technology (ICT) diffusion in the relationship between insurance development and economic growth in Sub-Saharan Africa (SSA). Using panel data from 36 SSA countries over the period 2007–2020 and applying the generalized method of moments (GMM), the results show that insurance penetration covering total, life, and non-life insurance along with ICT diffusion, significantly promotes economic growth in the region. The findings further indicate that ICT diffusion strengthens the growth-enhancing effect of insurance, highlighting its critical intervening role. Disaggregated ICT indicators reveal that fixed broadband, telephone subscriptions, and internet usage amplify the impact of total and life insurance penetration on economic growth, while fixed broadband plays a particularly strong role in enhancing the contribution of non-life insurance. Overall, the results suggest that although insurance development supports economic growth, its effectiveness is substantially reinforced through ICT infrastructure. Accordingly, the study underscores the importance for insurers to adopt digital technologies and leverage ICT diffusion to maximize their contribution to economic growth in SSA.
Key Drivers of Economic Growth in Developing Countries: A Comparative Study of Turkey and Bangladesh
This study examines the dynamic relationship between gross domestic product (GDP) growth and key macroeconomic indicators in Turkey and Bangladesh using panel data from the World Bank covering the period 1981–2020. The analysis focuses on population growth, inflation, literacy rate, natural resource utilization, investment, and foreign direct investment (FDI) to uncover their causal links with GDP growth. Employing the Dumitrescu–Hurlin panel causality test, the results reveal statistically significant causal relationships between GDP growth and the selected macroeconomic variables, with population growth emerging as the most influential determinant. The findings provide important insights into the distinct economic structures of the two emerging economies and offer policy-relevant implications for fostering sustainable and inclusive growth. Overall, the study contributes to the literature on economic development by highlighting the critical role of macroeconomic fundamentals in shaping long-term growth trajectories in emerging economies such as Turkey and Bangladesh.
SME Performance Outcomes: The Role of Technological Absorptive Capacity and E-Business Innovation
This study examines the relationship between technological absorptive capacity and SME business performance, with e-business innovation as a mediating mechanism. Using data from 179 sunflower oil–processing SMEs in Tanzania and applying PLS-SEM, the findings show that technological absorptive capacity significantly enhances business performance, both directly and indirectly through e-business innovation. The mediation effect is partial, indicating that absorptive capacity influences performance partly by fostering e-business innovation. Multigroup analysis reveals no statistically significant differences between SMEs in the Dodoma and Singida regions, although effect sizes are generally stronger in Dodoma, where the mediating role of e-business innovation is also more pronounced. Overall, the study provides empirical evidence of the importance of technological absorptive capacity and e-business innovation in improving SME performance and offers relevant implications for managers, policymakers, and researchers.
The Role of Research and Development in Fostering Innovation and Economic Growth in Developing Economies
This study investigates the mechanisms through which research and development (R&D) influences economic growth in developing countries. Using nine indicators drawn from three main categories in the World Economic Forum database, the analysis covers 32 lower-middle-income countries for the year 2019. Grounded in an R&D ecosystem framework, the study incorporates key components institutions, human capital, capital markets, R&D, and innovation that jointly shape economic development. Structural equation modeling (SEM) is employed to construct and test a path model capturing the interrelationships among these components. The results show that R&D activities and capital market institutions significantly enhance innovation performance; however, neither R&D nor innovation exhibits a direct or significant effect on economic growth. Consistent with a Schumpeterian institutional perspective, the findings suggest that innovation-driven growth mechanisms may be constrained in middle-income economies. The absence of a significant link between innovation and growth implies that, although R&D and capital markets foster entrepreneurial innovation, their contribution is insufficient to translate into sustained economic expansion. Overall, the results provide additional empirical support for the existence of a middle-income trap in developing economies.
Assessing the Impact of Eco-Innovation, Economic Complexity, and Digitalization on the Circular Economy in Europe
Facing escalating resource depletion and environmental degradation, the transition to a circular economy (CE) has become imperative, with the European Union (EU) emerging as a leading yet uneven performer. This study examines the effects of eco-innovation, economic complexity, and digitalization on CE performance in 22 EU countries from 2010 to 2021. Employing POLS, DKSE, and MMQR estimations, alongside the Dumitrescu–Hurlin panel causality test, the analysis captures both average and heterogeneous effects across CE development levels. The results reveal that all three factors significantly promote CE advancement, with digitalization exerting the strongest influence, followed by economic complexity and eco-innovation. Notably, eco-innovation is more effective in countries with lower CE performance, while economic complexity plays a greater role in more advanced CE contexts, whereas digitalization consistently enhances CE across all levels. Causality tests indicate a unidirectional relationship from economic complexity to CE. Overall, the findings highlight the need for differentiated and context-sensitive policy frameworks that integrate digital transformation, industrial sophistication, and eco-innovative capacity to accelerate the EU’s circular transition.
Digital Infrastructure Development and Economic Growth: Firm-Level Evidence from Investment Efficiency
This study empirically investigates the impact of digital infrastructure development on corporate investment efficiency in the context of China’s Broadband China policy. Using a sample of Chinese listed firms from 2007 to 2021, the analysis employs a difference-in-differences approach, complemented by propensity score matching and instrumental variable techniques, to evaluate the policy’s effects on inefficient investment, overinvestment, and underinvestment. The results show that the Broadband China policy significantly improves corporate investment efficiency by alleviating inefficiencies, particularly those associated with excessive investment behavior. These effects are more pronounced in regions with relatively advanced infrastructure. Heterogeneity analysis further reveals substantial differences across locations, with firms situated in provincial capitals benefiting more from the policy than those in non-capital cities. Mechanism analysis indicates that improvements in managerial efficiency play a mediating role in the relationship between digital infrastructure development and corporate investment behavior. Overall, the findings provide both theoretical and empirical support for governmental initiatives aimed at strengthening digital infrastructure and promoting balanced regional economic development. Based on these results, the study proposes differentiated policy recommendations to enhance managerial efficiency through digital infrastructure development and to reduce regional disparities. Future research may extend the analysis by incorporating broader datasets and examining the effects of digital infrastructure on other firm-level outcomes, such as innovation performance and market competitiveness.
Does Financial Agglomeration Promote Balanced Growth? Evidence from Enterprise-Level Structural Change
This study investigates Chinese listed companies over the period 2013–2023 to systematically examine the relationship between financial agglomeration, enterprise structural upgrading, and economic growth disparities at the firm level. The empirical findings can be summarized as follows. First, a higher degree of financial agglomeration significantly reduces economic growth disparities among enterprises. Second, enterprise structural upgrading plays a crucial role in narrowing growth disparities across firms. Third, enterprise structural upgrading acts as an important mediating mechanism through which financial agglomeration influences economic growth disparities. Fourth, the disparity-reducing effect of financial agglomeration is more pronounced for large enterprises, while its impact on small and medium-sized enterprises is relatively weaker. Fifth, financial agglomeration is more effective in mitigating growth disparities in highly competitive industries, whereas its effect is less significant in industries characterized by lower levels of competition. Finally, in high-competition industries, the mediating role of enterprise structural upgrading between financial agglomeration and economic growth disparities is significantly stronger.
How Innovation Policies and Intergovernmental Relations Affect Cross-Regional Collaborative Innovation —A Case Study of the Artificial Intelligence Sector in the Yangtze River Delta Region
Cross-regional collaborative innovation is an important way to promote the emergence of new quality productivity, and governments at all levels guide enterprises to cross-regional collaborative innovation by formulating innovation policies. Therefore, it is of great significance to explore the influence mechanism of policy and intergovernmental relations on cross-regional collaborative innovation. The article constructs a cross-regional collaborative innovation impact analysis model based on the characteristics of innovation policies and inter-governmental relations and their differences, and conducts an empirical study on the artificial intelligence industry in the Yangtze River Delta region with the help of the TERGMs model. The study shows that: (1) the level of policy characteristics: the greater the innovation policy strength, the smaller the policy volatility, and the greater the financial support are favorable to cross-regional collaborative innovation; (2) the level of inter-governmental relations: the stronger the policy response is, the more favorable it is to cross-regional collaborative innovation; and (3) the level of policy differences: the greater the difference in the strength of innovation policies, the smaller the difference in the policy volatility, the greater the correlation of the policy content, and the greater the difference in the policy response is more favorable to cross-regional collaborative innovation. The conclusions of the study can provide a theoretical basis for the government to optimize the innovation policy to guide cross-regional collaborative innovation.
Copyright (c) 2025 Studies in Science of Science https://creativecommons.org/licenses/by-nc/4.0
Research on the mechanism and effect of digital transformation on the resilience of industrial chain——Comparison of resilience dimensions of manufacturing industrial chain
With the coordinated promotion of digital industrialization and industrial digitization, digital transformation continues to reshape the development process of traditional industries in China and has become an important driving force for building the resilience of manufacturing industry chain. This article empirically explores the impact of digital transformation on the resilience of manufacturing industry chain using the spatial Durbin model. The results show that digital transformation significantly enhances the resilience of the local manufacturing industry chain, but has a certain negative effect on neighboring regions, and the talent aggregation and the technological innovation play a mediating role in the relationship between the digital transformation and the resilience of the manufacturing industry chain. Heterogeneity analysis shows that digital transformation in the eastern and central regions has a significant promoting effect on the resilience of local manufacturing industry chains, and has a siphon effect on neighboring regions. But the digital transformation in the western region has a positive impact on the resilience of both local and neighboring manufacturing industry chains. Further analysis reveals that the digital transformation of the overall country has the most significant impact on the innovation dimension of the resilience of the manufacturing industry chain, and there are significant differences in the impact of digital transformation on the resilience dimensions of the manufacturing industry chain in different regions. The conclusion of this paper provides strong reference for accelerating the integration of digital economy and real economy and helping to enhance the resilience of manufacturing industry chain.
Who Can Gain More "Technological Dividends"?—A Study on the Heterogeneous Impact of Generative Artificial Intelligence on Researchers
With the iterative breakthroughs in technological applications of generative artificial intelligence (GAI), an increasing number of researchers have begun utilizing GAI to assist scientific work. This new wave of "technological dividends" and its potential "intelligence gap" warrant close attention. Based on empirical survey data from researchers at multiple Chinese universities, this study employs cutting-edge machine learning algorithms to systematically examine the impacts of GAI on researchers' innovative behaviors, working hours, and their heterogeneous treatment effects. The findings reveal:First, while GAI significantly stimulates researchers' innovative behaviors, it simultaneously leads to a corresponding increase in working hours, indicating that the current "technological dividends" of GAI are primarily manifested in the aspect of innovation incentives.Second, the effects of GAI demonstrate significant heterogeneity among researchers, with research output, age, and gender being critical factors influencing these differential treatment effects. Specifically, male researchers and high-output individuals exhibit more pronounced improvements in innovative behaviors under GAI's influence, while experiencing relatively limited negative impacts on working hours. Further verification confirms that high-performing researchers characterized by superior productivity constitute the main beneficiaries of GAI's "technological dividends" at the current stage.
Good Governance for Good Intelligence: Credible Governance of Artificial Intelligence Alienation
Improving the credible governance system of artificial intelligence is necessary to promote technological innovation and a legal guarantee to comprehensively respond to technological alienation and promote the development of new quality productive forces. Uncontrollable artificial intelligence has triggered a serious crisis of confidence in its application and even threatened social stability and national security. To balance development and security, the governance consensus of "credible development" should be condensed, and the flexibility and effectiveness of governance should be improved by following the theory of life cycle and technical governance. On the one hand, improves the legal compliance guidance framework before, during, and after the event, and reduces regulatory costs while improving regulatory deterrence; on the other hand, it is necessary to innovate the technology governance system, introduce regulatory technologies such as private cloud computing, supervision fine-tuning, and SAGE analysis, and improve the human-machine collaborative framework to fully implement data, algorithms, and content credible regulatory requirements. To improve the artificial intelligence safety supervision system, prevent the risk of alienation, and create a "mutually beneficial symbiosis" man-machine relationship.
R&D, Innovation, and Firm Outcomes: Market Value and Performance Evidence from the G7
This study provides the first empirical evidence on how innovation and firm growth influence performance across G7 economies, using a unique panel dataset of 252 firms observed from 2020 to 2024. Focusing on two key dimensions of firm performance labor productivity and asset turnover the analysis incorporates multiple innovation indicators, including R&D Intensity, R&D-to-Assets, and R&D Growth Rate. To mitigate potential endogeneity arising from reverse causality and omitted variable bias, the study employs a heteroskedasticity-based instrumental variable estimator that constructs internal instruments from the model’s error structure. The empirical results consistently show that innovation exerts a positive and significant causal effect on labor productivity, reinforcing its role as a critical driver of firm-level efficiency. Conversely, innovation demonstrates a negative and significant relationship with asset turnover, indicating short-term operational efficiency trade-offs, particularly among firms pursuing aggressive R&D strategies. Further analysis reveals that these innovation effects are moderated by firm profitability and industry-specific conditions, underscoring the strategic and contextual determinants of innovation outcomes. Overall, the findings highlight the dual nature of innovation simultaneously enhancing productivity while imposing transitional efficiency costs and provide important implications for corporate innovation strategy and public policy within advanced economies.
Open Source Innovation: Theoretical Connotations, Knowledge Framework and Future Prospects
With the rapid development of the digital economy and artificial intelligence, open innovation models have become increasingly widespread, emerging as a crucial driver of scientific and technological progress and economic growth. However, discussions in existing literature on aspects such as discussing the connotation of open source innovation, differentiating theoretical perspectives, and analyzing and engaging in dialogue on research topics are scattered, lacking systematic review and summary. This paper conducts a comprehensive review of 321 papers related to the theme of open source innovation that were included in SSCI-indexed journals from 2001 to 2023. Based on a review of the origin of open source innovation, it deeply analyzes the theoretical connotations of this concept and summarizes the dominant theoretical perspectives for distinguishing the existing connotations of open source innovation. Further, this paper constructs an “Element-Mechanism-Outcome (EMO)” knowledge framework for open source innovation. It summarizes four basic elements of open source innovation (open source developers, open source projects, open source communities, and open source licenses), three major mechanisms in the operation process of open source innovation (development collaboration mechanism, community regulation mechanism, and business operation mechanism), and three aspects of effectiveness in the value evaluation of open source innovation (scientific and technological effectiveness, industrial effectiveness, and social effectiveness). This paper also puts forward the future research prospects of open source innovation, thereby contributing to the expansion of knowledge in theoretical research on open source innovation and providing insights for the policy practice of open source innovation.
Does Efficiency Matter in M&A? Evidence from Indonesia’s Industrial Estate Group Companies
The consolidation of Industrial Estate companies in Indonesia into a single holding company is reshaping the structure, behaviour and business models of key actors in the country’s industrial development landscape. This study examines whether there is a relationship between the efficiency levels achieved by Industrial Estate companies and their degree of involvement and strategic role in mergers, acquisitions and consolidation processes within the holding. Because this relationship may operate in different directions, both highly efficient and poorly performing parks may be targeted for integration. The issue is relevant for a wide range of stakeholders, from policy-makers and the holding’s management to investors and regulators. We measure efficiency using two Stochastic Data Envelopment Analysis (SDEA) models. Based on a hand-collected data set of 113 Indonesian Industrial Estates, belonging to 48 corporate groups over the period 2022–2024, the results indicate that consolidation and M&A decisions essentially involve parks located at both ends of the efficiency spectrum, characterised by either relatively high or relatively low efficiency levels.
A Strategic Competition Between China and Japan in the Indo-Pacific: Case From The Whoosh High-Speed Train Projects in Indonesia
China’s launch of the Belt and Road Initiative (2013) and Japan’s subsequent Partnership for Quality Infrastructure (2015) have intensified their rivalry over infrastructure exports across Asia. Existing scholarship largely contrasts these initiatives in terms of competition and norm diffusion, but pays less attention to the underlying forces shaping their policy designs. This article proposes a framework in which great-power rivalry and cross-national policy learning jointly guide how infrastructure strategies are formulated. Strategic competition encourages each country to differentiate itself and claim particular market and political spaces, whereas learning from one another’s practices gradually pushes their approaches closer together. We examine these dynamics along three dimensions: how the initiatives are defined, how state-backed support is structured, and how far they rely on multilateral versus bilateral arrangements. Using Indonesian railway projects as a paired case, we show how China, as a relative latecomer, leveraged political and financial innovation to enter a field long dominated by Japan, and how both sides subsequently adjusted their policies after the Jakarta– Bandung high-speed rail tender and the second phase of the Jakarta mass rapid transit project.
Infrastructure export strategies Policy learning
Measurement of ‘Changing Lanes and Overtaking’ Achievement Degree in China's Industry--An Empirical Analysis of the Automotive Industry Mainstream Technology Track
Since the initiation of the reform and opening-up policy, China has pursued a development strategy characterized by following the lead of advanced economies. This approach has resulted in China's long-term positioning at the lower end of the global value chain, which is dominated by developed countries. Consequently, China has faced significant challenges in achieving upward mobility within the value chain. Currently, many of China's industries are at a critical juncture of development and transformation, among these, the new energy vehicle industry stands out as the most dynamic sector, demonstrating considerable potential for China to achieve "Changing Lanes and Overtaking" development. Therefore, grasping the critical window period for "Changing Lanes and Overtaking" and ly identifying the extent of its realization are of vital importance for China to break through the path dependency of core technologies in traditional industries and to achieve high-quality development. Based on the INNOJOY patent database, this study selects two mainstream technological trajectories within the automotive industry as research objects: the technological trajectory of traditional internal combustion engine vehicles and that of lithium battery vehicles. A comprehensive three-dimensional analytical model, incorporating the dimensions of technology, economy, and law, along with its corresponding indicator system, is constructed to conduct a multidimensional analysis of the patent information related to these technological trajectories. The entropy weight method is employed to assign weights to each indicator, reflecting their relative importance. Subsequently, the TOPSIS method is utilized to conduct a comprehensive evaluation of the value of each patent. This process results in the formation of a patent quality index for each country, which is then applied to compare the patent competitive advantages among different nations. The findings reveal that in the technological trajectory of traditional ICE vehicles, the gap between China and countries with high-quality ICE vehicle patents remains substantial. This gap is evident from multiple perspectives, including the overall and newly added key core patents, as well as from the aspects of total and valid patents. As a result, it appears unlikely that China will be able to achieve technological catch-up in the short term. In contrast, in the technological trajectory of lithium battery vehicles, China ranks third in the comparison of all key core patents, trailing only the United States and Japan. When considering the total index of patent quality for valid key core patents, China has surpassed Japan and now ranks second as of July 2024, notably, the annual increment of valid key core patents has consistently ranked second from 2012 to 2017. Furthermore, from the perspective of the patent quality index across the dimensions of technology, economy, and law, China consistently ranks in the top three, and the annual increment of valid key core patents has maintained a second-place position for 5-9 consecutive years from 2012 to 2017. These results indicate that China has preliminarily achieved "Changing Lanes and Overtaking" in the automotive industry. This study provides empirical evidence and reference for latecomer countries and their latecomer industries regarding the feasibility of "Changing Lanes and Overtaking" and potential future development directions.
Russia's awareness and concerns about high-tech cooperation with China under the new situation: an investigation and research based endogenous perspective of Russia
With the increasing complexity of the international situation and considering the realistic conditions of high political mutual trust between China and Russia, there is great potential for high-tech cooperation between the two countries. This article is based on a survey and research conducted on the Russian citizen over 25 years old, combined with expert consultation, attempting to demonstrate the overall understanding of the Russian government, think tank community, and society towards high-tech cooperation with China under the new situation. The study found that the Russian society has a strong willingness to cooperate with China under the influence of national strategic choices and has a high overall evaluation, especially in the fields of digital and information technology, and has expectations for the Chinese market environment. Although the scale and intensity of Sino-Russian high-tech cooperation are not as strong as that of Russia-USA and Russia-Europe, China's strategic dominant position in Russia's foreign high-tech cooperation will continue under the impetus of the “common agenda” to counter Western technological sovereignty. Based on the perspective of endogenous Russia, this research conducts an exploratory investigation and research on Russia's awareness and concerns about high-tech cooperation with China under the new situation, which provides clues and basis for promoting the high-quality development of Sino-Russian cooperation in the field of high-tech, and also provides inspiration for decision makers to respond and predict corresponding Russian policies.
New Productivity: A Comparison of European and American Policies and Lessons for China
New productivity—anchored in digitalisation, green transition and innovation-driven growth—has become a core theme in major economies’ structural upgrading strategies. This paper compares how the European Union and the United States conceptualise, cultivate, and govern “new productivity”, and distils policy implications for China. Drawing on policy documents, strategic plans and sectoral initiatives, the study finds that the EU emphasises mission-oriented and regulation-led new productivity, driven by green transformation, digital sovereignty, and social cohesion (e.g. Green Deal, Digital Compass, industrial policy under “open strategic autonomy”). By contrast, the US follows a more market-driven and security-oriented approach, characterised by flexible industrial policies, massive innovation funding in key technologies, and reshoring/“friend-shoring” framed by national security and techno-geopolitics. The paper argues that China should neither mechanically imitate European planning logics nor American competition logics, but build a China-specific new productivity paradigm that simultaneously: (1) strengthens basic research and original innovation capacity; (2) accelerates digital–green–manufacturing integration; (3) leverages super-large market advantages and the “new nationwide system” to build open yet controllable innovation ecosystems; and (4) improves institutional arrangements for talent, data and platform governance. These insights provide theoretical support and policy reference for China to cultivate new productive forces under great-power competition and deep global uncertainty.
Development strategies for China’s integrated circuit industrial ecosystem in the Post-Moore Era
The post-Moore era marks the period following the breakdown of “Moore's Law,” which predicted that microprocessor performance would double approximately every two years. In this era, integrated circuits are approaching the physical limits of material density and process technology, while energy consumption costs are rising significantly. The onset of the post-Moore era has led to three major technological shifts. First, in advanced silicon-based semiconductor manufacturing, the first-mover advantage of leading nations, regions, and companies is gradually eroding. Second, new competitive arenas are emerging in advanced packaging technologies and the development of alternative materials for silicon-based chips. Third, the rise of the RISC-V architecture is challenging the longstanding market dominance of Intel x86 and ARM architectures. The post-Moore era has also reshaped the competitive landscape, characterized by oligopolistic market structures and the increasing nationalization of key industry players. These developments offer new opportunities for China’s integrated circuit industry. In light of China’s burgeoning digital economy, which continuously creates new scenarios and markets, we propose that the Ecosystem strategy for the development of China's integrated circuit industry in the post-Moore era should encompass four types. First, mature ecosystem, which adheres to the singular technological path of More Moore, and the goal is to enhance the industry's autonomy and controllability, as well reducing the risk of being subjected to critical constraints. Second, scenario-driven ecosystem, which follows the integrated technological path of More than Moore and More Moore, and the aim is to leverage China's rich application scenarios to expand the boundaries of the integrated circuit industry ecosystem, while continuously promoting the industry's digital transformation and achieve autonomous control over the integrated circuit industry ecosystem from the end of key application scenarios. Third, future industry ecosystem, which integrates all three technological paths, with a key focus on breakthroughs in Beyond CMOS technology, and the objective is to capitalize on the advantages of a new nationwide system, to plan moderately ahead, and to seize the high ground in future international competition. Fourth, internationalized ecosystem, which emphasizes expanding China's diversified industrial ecosystem into the international market, and the purpose is to actively integrate into the global innovation ecosystem, further expand the scope of scenario-driven ecosystems, and enhance the resilience of the ecosystem. To address the challenges in the development of China's integrated circuit industry in the post-Moore era, it is essential to leverage the advantages of China's super-large scale market and its new nationwide system. First, in the domain of mature ecosystems, reconstructing the industrial chain, along with the support and guidance of industrial policies, can help build a second ecosystem that is autonomous, controllable, and compatible. Second, based on the combined technological approach of System-on-Chip (SoC) and System-in-Package (SiP), the rich application scenarios can be utilized to expand the boundaries of the industrial ecosystem. Simultaneously, by infiltrating through scenario applications, it is possible to gain dominance in these emerging industrial ecosystems. Third, proactively layout advantageous industrial ecosystems around future industries. Additionally, there should be innovation in the organizational models of industrial internet and the promotion of industry-level data element market construction, ensuring that various production relationships meet the development needs of key core technologies in future industries. Fourth, based on the characteristics of dominant countries and dominant enterprises in different segments of the industrial chain, China can adjust its strategies targetedly to actively integrate into the global innovation ecosystem and international industrial ecosystems.
Does R&D collaboration among enterprises promote technological convergence? ———Moderating effect of engagement level with universities / scientific research institutions
Technology convergence has become the primary way enterprises achieve technological innovation and cultivate disruptive technologies. Enterprises’ R&D cooperation was recognized as one of the crucial factors in promoting technological convergence. However, in the context of accelerated technology convergence in multiple fields, how enterprise R&D collaboration affects technology convergence remains unclear. Based on knowledge management theory and resource dependence theory, we constructed the multilayered complex network of enterprise R&D cooperation—technology convergence and measured the technology convergence degree of enterprises from the breadth, depth, and difference. Then, we explored the impact of enterprise R&D cooperation on technology convergence at different technology lifecycles and the moderating effect of engagement level with universities/scientific research institutions. We conducted empirical research on smartphone-related enterprises and found that (1) the strength of enterprises’ R&D cooperation, technology heterogeneity of enterprises’ R&D cooperation partners, and enterprises’ average R&D cooperation time all have a promoting effect on technology convergence depth and difference. The effects are more significant in the emergence and post-growth stages. (2) The strength of enterprises’ R&D cooperation, technology heterogeneity of enterprises’ R&D cooperation partners, and enterprises’ average R&D cooperation time all have an inhibitory effect on technology convergence breadth. The effects are different in each technology lifecycles. (3) The engagement level with universities/scientific research institutions positively regulates the inhibitory relationships between the strength of enterprises’ R&D cooperation, technology heterogeneity of enterprises’ R&D cooperation partners, enterprises’ average R&D cooperation time, and technology convergence breadth. The engagement level with universities/scientific research institutions negatively regulates the strength of enterprises’ R&D cooperation, technology heterogeneity of enterprises’ R&D cooperation partners, enterprises’ average R&D cooperation time, and technology convergence depth and difference. This paper revealed the intrinsic mechanism of enterprises’ R&D cooperation on technological convergence, which provided crucial theoretical and practical references for guiding enterprises to promote technology convergence through R&D cooperation, thereby cultivating disruptive technologies.
Various patterns in different markets: Research on patent war types in the perspective of Chinese enterprises
Patent warfare is a series of offensive and defensive actions centered around patent ownership and use, aimed at attacking business rivals and gaining commercial benefits by exploiting loopholes in policies and regulations. Originating in the United States, patent warfare is spreading globally, profoundly impacting the competitive landscape of industries and becoming a new problem and challenge for the global patent system. Facing the risks and challenges of global patent warfare, this study uses patent wars encountered by Chinese companies in the United States, China, Germany, the United Kingdom, and India as research samples, employing qualitative comparative analysis to conduct empirical research. The research shows that with the spread of patent warfare in recent years, it has evolved into differentiated characteristics, which can be divided into five main types. Not only are the initiators and attack methods of patent wars diversified, but the types and characteristics of patent wars also exhibit heterogeneity in emerging and mature markets. Therefore, to cope with the risks and challenges of global patent warfare, Chinese companies must adopt differentiated prevention and response strategies based on the type of patent war and the different markets and patent war actors.
Research on the influence of Sino - US technology rivalry on patent litigation of Chinese firms in the US
Nowadays, the uncertainty of the international environment is rising. On the one hand, deglobalization is intensifying, new technological nationalism is prevailing, and the global economic structure is being reshaped. On the other hand, as geopolitical conflicts between countries continue and Sino-US trade frictions intensify, Chinese multinational enterprises are facing unprecedented challenges. Among them, the core event is still that the United States imposed tariffs on Chinese imports in 2018, which subsequently escalated into the Sino-US trade war and technology game, in which the United States targeted Chinese high-tech enterprises and increased sanctions on industries in the "Made in China 2025". All the above phenomena show the concern of the United States about the rapid progress of China's science and technology. For Chinese multinational enterprises, it is not only necessary to strengthen the awareness of independent innovation, but also to protect their own technology from being infringed, which is also a topic worthy of attention in the theoretical and practical circles. This paper theoretically analyzes the intrinsic mechanism of the impact of the Sino-US Technology Rivalry on the number of patent litigation faced by Chinese firms in the United States, starting from the mechanisms of "Decoupling" and "Competition." Political tensions between the United States and China, on the one hand, limit the movement of technology and personnel between the two countries, thereby reducing potential patent disputes; On the other hand, it will increase the possibility that US enterprises will use patent litigation as a competitive weapon to suppress the core technology of Chinese enterprises, and the number of patent lawsuits will increase. Two contradictory "forces" make the relationship between the political tension between China and the United States and the number of Chinese enterprises being sued in the United States become confusing. By constructing a Staggered Difference -in- Differences model and using a sample of 151 Chinese high-tech companies that have faced patent litigations in the United States from 2013 to 2022, the paper examines the effect of the Sino-US Technology Rivalry on the number of patent litigation. The study finds that due to the reduction in technological activities and exchanges between researchers in China and the United States, the number of patent litigation against Chinese high-tech companies in the United States has significantly decreased after the Sino-US Technology Rivalry, and this effect remains robust after multiple tests. Further research reveals that the international diversity of companies weakens the negative effect, while the intensity of R&D strengthens the negative effect. This article tries to contribute to the following three aspects. First, this paper enriches the literature on political tensions and corporate strategic relationships, and finds that the US-China technology game has a negative impact on patent litigation through the progressive different-difference model, providing new evidence of the consequences of the US-China technology game at the micro-enterprise patent strategy level. Secondly, this paper enriched the relevant literature on cross-border patent litigation, innovatively proposed two mechanisms of "decoupling" and "competition", fully analyzed the impact path of external events on patent litigation at the macro level, and tested the regulatory role of international diversity and R&D intensity. Finally, this paper provides practical guidance for Chinese enterprises and government to deal with the technology game between China and the US.
The theoretical construction and policy enlightenment of the new system for mobilizing the resources nationwide
Establishing and improving a new national system for tackling key core technologies is an inevitable requirement for China to solve the "bottleneck" problem and achieve scientific and technological self-reliance. However, current theoretical research on this new national system lacks depth and cannot effectively address relevant domestic and international controversies. This study proposes the theoretical foundation of a new national system from the perspective of innovation-driven development and constructs a theoretical analytical framework of "national will—national capacity—interaction mechanism." It argues that the national will formed under crisis-driven conditions is an important prerequisite for implementing the new national system. Under the guarantee of strong national capacity, a dynamic interaction mechanism is formed between the government and the market, and between the public and private sectors, thereby transforming the institutional advantages of the new national system into advantages for national innovation-driven development.
How does strategic consensus facilitate enterprises to break through the digital pilot dilemma?
With the new round of technological revolution and industrial transformation, a growing number of enterprises have embarked on digital strategic transformation, accelerating the integration of new-generation information technology with their business scenarios. However, in practice, many enterprises are still stuck at the pilot stage of digital transformation for certain businesses, facing challenges such as high transformation costs and low production efficiency, thus trapped in a pilot dilemma. How to effectively help enterprises break through this pilot dilemma and promote the transition from limited pilot projects to full-scale implementation of digital transformation has become an important practical issue. Existing research has focused on studying the influencing factors of enterprise digital transformation at the senior management level. It overlooked the proactive role of employees in the transformation process. As a process of organizational strategic change, the implementation and promotion of enterprise digital strategies cannot rely solely on the drive of senior management. It requires the participation and support of all the employees. Only when employees reach a common understanding and identification with the established strategies of the enterprise will they consciously and actively engage in the strategic practice process, thereby effectively enhancing the level of digital transformation. In this sense, this study introduces a context-driven perspective to explore the mechanism of strategic consensus influencing the scope of enterprise digital application from differentiated contextualized innovation behavior. By using 244 pairs of "leader-employee" questionnaire data to carry out empirical analysis, the results show that: (1) Strategic consensus has a significant positive impact on enterprises' expansion of the scope of digital application. When employees at all levels reach a consensus and high identification with the vision and goals of enterprise digital transformation, it helps promote the integrated application of digital technology across various business links, assisting enterprises in breaking through the digital pilot dilemma. (2) Strategic consensus promotes the expansion of the scope of enterprise digital application through contextualized innovative behavior. The common understanding of enterprise digital transformation among employees at all levels can encourage them to actively engage in user contextualized innovative behavior, product contextualized innovative behavior and operational contextualized innovative behavior, thereby driving the transition of the scope of enterprise digital application from limited pilots to full-scale implementation. Lastly, employees' digital literacy amplifies the positive impact of strategic consensus on contextualized innovative behavior and strengthens the mediating effect of scenario-based innovation behaviors, thus helping enterprises break through the digital pilot dilemma. The theoretical contribution of this study lies in enriching the research on enterprise digital transformation at the employee level by comprehensively considering the influence of employee cognition and behavioral factors on enterprises' breaking through the digital pilot dilemma, and revealing the mechanism of this process. Furthermore, by examining the role of contextualized innovative behavior, this study expands the connotation and application of the context-driven theoretical perspective, verifies the mediating role of employee contextualized innovative behavior between employee strategic consensus and the scope of enterprise digital application, and reveals the path of strategic consensus influencing the scope of enterprise digital application. Finally, this study delves into the scenarios under which strategic consensus can better stimulate contextualized innovative behavior, thereby expanding the scope of enterprise digital application.
The impact of intelligent manufacturing on Chinese manufacturing enterprises' performance in GVC
Intelligent manufacturing has become a key driver for upgrading China’s manufacturing industry and enhancing its position in global value chains (GVCs). This paper investigates how intelligent manufacturing capabilities affect Chinese manufacturing enterprises’ GVC performance from both value capture and value chain position dimensions. Drawing on panel data of Chinese listed manufacturing firms, combined with indicators of digital technology adoption, automation level, and data-driven decision-making, we construct an intelligent manufacturing index and embed it into a firm-level GVC performance framework. Using fixed-effects and mediation models, the study finds that intelligent manufacturing significantly improves firms’ GVC performance by increasing value-added margins, export sophistication, and the probability of moving toward higher-end segments of the value chain. Mechanism analysis shows that this positive effect operates mainly through three channels: upgrading product quality, enhancing production flexibility and efficiency, and strengthening collaborative innovation with upstream and downstream partners. Heterogeneity tests further reveal that the promoting effect is more pronounced in high-tech industries, coastal regions, and firms with stronger absorptive capacity. The findings provide empirical evidence that intelligent manufacturing is an effective pathway for Chinese manufacturing enterprises to move from “big” to “strong” in GVCs, and offer policy implications for digital upgrading and GVC reconfiguration.
Research on algorithmic black boxes: A cognitive science perspective
Studying algorithmic black boxes from a cognitive dimension represents a third pathway beyond the existing technical and normative approaches. This perspective emphasizes understanding algorithmic black boxes through conceptual frameworks similar to those used for human cognition. Compared to the "black box" of the human mind, algorithmic black boxes face higher demands for transparency, which has given rise to the "algorithmic black box-transparency-accountability" framework. However, this focus often overshadows other important attributes of black boxes, such as their strangeness and legitimacy.Contrary to cognitive common sense, algorithmic black boxes also possess positive cognitive functions. They unify transitions across organizational levels in cognition and facilitate the shift from causal relationships to mechanisms. This capability challenges the myth of algorithmic explainability, avoids the illusion of explanatory depth, and provides directions for horizontal or nested explanations to unfold the black box. A visual "gray box" ladder explanation method, positioned between "white box" and "black box" approaches, can be employed.The analytical framework of the information and control phases s a re-evaluation of scenario-based regulation methods. Trust in algorithms can be categorized into three types: inherent trust, learned trust, and situational trust, corresponding to factors related to humans, algorithms, and the environment, respectively. Reducing "algorithm aversion" is influenced by the objectivity of algorithms, the autonomy of human processes, concerns about social judgment, and the degree of intrusion algorithms impose on human thought.
Breaking through technology blockade: A study on corporate venture capital investment strategy of high - tech companies
Technological innovation is a core element in developing new productive forces. Faced with the US-initiated technological blockade against China, breaking free from dependence on foreign technology and promoting technological self-reliance is crucial for the high-quality development of China's high-tech industry. This paper examines how Chinese high-tech companies utilize venture capital to overcome technological blockades and tackle key core technologies, using the US Entity List sanctions as a backdrop. The study finds that compared to high-tech companies not subject to Entity List sanctions, sanctioned companies significantly increased their venture capital investment after being sanctioned. Furthermore, venture capital significantly increased the number of patent applications, patent citations, and patent knowledge breadth for these companies in key core technology areas. Further analysis shows that when sanctioned companies have higher market positions, greater trustworthiness, and stronger absorption capabilities, they have a stronger incentive to initiate venture capital to overcome technological blockades. In terms of specific investment behavior, sanctioned high-tech companies are more likely to invest in startups with high upstream industry relevance and in early-stage development. This study reveals the important role of corporate venture capital in overcoming foreign technological blockades and tackling key core technologies, providing important insights for the independent innovation of Chinese high-tech enterprises.
Layered network spillovers in China’s new energy governance: Global carbon emission reduction through new energy city pilots
As the world's largest producer of renewable energy, China's renewable energy governance is both domestic and global. Exploring whether China's renewable energy governance practices have reduced global carbon emissions and enhanced global governance capacity is of significant practical importance. This study finds that China's renewable energy governance has a significant carbon reduction spillover effect. Specifically, it has significantly increased the depth and breadth of the signing of global environmental governance rules through RTAs (Regulatory Agreements). Looking at the details of the signed rules, trade-related aspects of China's renewable energy governance have the strongest carbon reduction spillover effect on implementation mechanisms and environmental target setting; technology-related and investment-related aspects are consistent, with external aid and institutional establishment being the most prominent; infrastructure-related aspects have the strongest carbon reduction spillover effect through the signing of external aid and implementation mechanisms. Furthermore, China's trade, technology, and infrastructure-related aspects of renewable energy governance with countries participating in the Belt and Road Initiative can accelerate the signing of global environmental governance rules through RTAs. Meanwhile, in terms of the distribution of related countries, China's trade-related carbon reduction spillover is highest with Europe, Africa is most directly affected by China's technology and infrastructure-related aspects of renewable energy governance, and Asia is best affected by investment-related carbon reduction effects. It is worth noting that the Sino-US friction will inhibit the spillover effect of China's trade-related new energy governance on global carbon emission reduction, but will strengthen the spillover effect of China's new energy governance technology-related linkages.