Fiscal policies for scientific research play a pivotal role in advancing the innovation-driven development strategy. Enhancing the quality and efficiency of these policies is essential for improving the overall performance of the national innovation system and achieving Chinese modernization. This study employed a qualitative research approach to systematically examine the practical logic and optimization pathways of China′s fiscal policies for scientific research. The main findings are as follows: (1) The policy framework is grounded in the National Innovation System Theory and the Theory of National Competitive Advantage. The government employs fiscal expenditure and tax incentive policies to orchestrate the allocation of innovation factors and propel the momentum of scientific and technological innovation. (2) Since the 18th National Congress of the Communist Party of China, policy practices have evolved to feature stronger guidance through public spending, more pronounced effects of tax incentives, and a more integrated approach to fiscal coordination. These shifts reflect the adjustment of government functions, the strengthening of enterprises as primary innovation actors, and the development of a modernized industrial system. (3) At present, key challenges include constraints of policy dependency on innovation performance, lack of systematic evaluation of policy synergies, inadequate mechanisms for talent incentives, and underdeveloped mechanisms for research commercialization. Therefore, further efforts are required to realign policy orientation and functional roles to drive enterprise-led innovation, leverage platform development and talent support to overcome barriers in basic research, and enhance institutional guarantees and service systems to foster cross-sectoral collaboration. These insights will contribute to the theoretical and practical discourse on strengthening the foundational systems of all-round innovation.

    Digital industry clusters are a phenomenon of industrial agglomeration in the context of digital economy with digital native enterprises and digital transformation of incumbent enterprises as important components. Due to differences in the ability of different enterprises to access digital resources, digital industry clusters have the problem of poor industry chain integration, the digital divide faced by cluster enterprises has turned from the "access divide" to the "ability divide". From the perspective of "data elementsdigital technology" interaction, the study explored the evolution mechanism of digital industry clusters through an exploratory multicase analysis of Hefei Artificial Intelligence Industry Cluster, Hangzhou Digital Security Industry Cluster, and Wuhan Optoelectronic Information Industry Cluster. The study revealed that: (1) the deepening of interactive degree and promotion of interactive efficiency between data elements and digital technology, drive the clusters to cluster quickly in cyberspace, which has an impact on the cluster development mode and the building of cluster competitiveness; (2) the dualwheel drive of "data elementsdigital technology" promotes the transformation of cluster network relationships from "imitative network embedding" and "progressive network embedding" to "break through network embedding" by changing the digital connection mode of cluster enterprises; (3) in the process of evolution and development, digital industry clusters choose different development modes according to the level of agglomeration they have reached and the problems they have faced, which promotes the extension of the digital economy industry chain. The findings will provide theoretical basis for the efficient and rational allocation of digital resources in China, and promote the sustainable development of digital industry clusters.

   As a new type of production factor in the digital era, data factorization reconstructs the traditional productivity paradigm, and is an important engine to promote the transition of productivity. On the new journey of Chinese path to modernization, it is of great theoretical and practical significance to study how the value of data elements can improve the digital new quality productive forces of enterprises. Using the pilot cities of big data trading centers as a quasi-natural experiment, this paper adopted the data from 287 prefecture level cities in China from 2012 to 2022, combined with a multi period DID model, to evaluate the effectiveness and mechanism of digital new quality productive forces empowered by monetization of data elements. The research found that the establishment of big data trading centers can significantly enhance digital productivity, and that the promoting effect is mainly reflected in the sample group with a higher degree of government intervention and a larger digital divide. The monetization of data can promote the development of new quality productive forces by optimizing the structure of production factors and promoting the development of the digital economy, but the transmission path of optimizing the traditional factor structure is not yet clear. Further research found that data monetization has significant spatial spillover effects. The establishment of big data trading centers under adjacent spatial weights has a significant negative spillover effect on neighboring regions, while under economic spatial weights, the improvement of local data monetization level will have a positive spillover effect on neighboring regions. The conclusion of this study will not only provide new empirical evidence for relevant departments to lay out the construction of big data trading centers, but also provide useful insights for cultivating digital new quality productive forces.

Digital innovation is extremely critical to strengthening corporate competitiveness and driving value chain. Data transactions play an important role in accelerating the high value conversion of data and helping digital innovation breakthroughs. Based on the data of listed companies from 2010 to 2022, this paper used crawler technology, text analysis and manual recognition to identify corporate data transactions, and constructed a dual machine learning model to empirically analyze the impact of data transactions on corporate digital innovation, further expanding the micro-effects and mechanisms of data transactions on digital innovation. The results of the study showed that data transactions have a significant positive impact on corporate digital innovation, and this positive effect is stronger among non-state-owned corporations, large corporations, corporations with high levels of intellectual property protection, and corporations with strong digital infrastructure. The mechanism analysis showed that data transactions have promoted corporate digital innovation through knowledge spillover effect, factor allocation effect, and corporate governance effect. In addition, the effect of the supply-side data transaction, data service transactions, and direct data transactions on promoting corporate digital innovation are more obvious, and data transactions can improve the quality of corporate digital innovation. This study has important implications for encouraging corporates to participate in data transactions, it will expand and strengthen the data factor market, and promote corporate digital innovation through data marketization.

   As the acceleration of public data openness and sharing becomes a core task in China′s digital government construction, understanding how enterprises can leverage public data openness to enhance their technological innovation has become a crucial issue. Based on a sample of Ashare listed firms on the Shanghai and Shenzhen Stock Exchanges from 2015 to 2021, this study employed a DID model to empirically examine the impact of public data openness on corporate technological innovation and its underlying mechanisms. The findings revealed that public data openness significantly enhances corporate technological innovation. The mechanism tests indicated that public data openness promotes corporate technological innovation by reducing uncertainty risks, accelerating cross-entity information flow, and lowering transaction costs associated with innovation. The heterogeneity analysis demonstrated that favorable trust environments, higher government governance efficiency, and robust digital infrastructure strengthen the positive impact of public data openness on technological innovation. Further analyses of public data characteristics showed that the enabling effect of public data openness on corporate technological innovation is more pronounced when public data is of lower geographic granularity and higher specialization. The structural analysis of corporate technological innovation revealed that public data openness contributes to both the quality effect and spillover effect of corporate technological innovation. The economic consequence tests indicated that the improvement in corporate technological innovation driven by public data openness ultimately leads to increased corporate value. This study has explored the enabling effects of public data openness from the perspective of micro-level corporate technological innovation, and will provide theoretical insights into how to better achieve the coordinated development of public data openness and innovation-driven strategies. 

    Transdisciplinary research serves as a crucial pathway for China to address Western technological blockades, achieve breakthroughs in key core technologies, and cultivate new productive forces. An in-depth analysis of China′s transdisciplinary research model helps advance the construction of China′s independent knowledge system, contributes Chinese wisdom to transdisciplinary research, and provides theoretical support for scientific and technological innovation. This study analysed the policy documents from major scientific and technological innovation programs (including the "863 Program", "973 Program", "2011 Plan", and "National Key Research and Development Plan"), along with the first-hand interview data from three major scientific research projects (100,000 m3/h air separation compressor, large full-section tunnelling equipment, and carbon fibre composite material cutting equipment), comprising approximately 400,000 words of textual data. Using the grounded theory analysis and typological construction methods, the study revealed three Chinese models of transdisciplinary research: (1) the government-led tracking development model, which aims to track international frontiers through government-led organized research and implements innovation through introduction, digestion, absorption, and re-innovation; (2) the exploratory demand-oriented independent innovation model, which focuses on independent innovation to address major needs through enterprise-centred industry-university-research cooperation and primarily utilizes integrated innovation; and (3) the multi-stakeholder consultative collaborative innovation model, which pursues comprehensive innovation in science, technology, and talent through multi-stakeholder consultation and dialogue, employing both integrated and original innovation approaches. Based on the characteristics and value of these three models, the study has proposed establishing a classified management system to leverage the advantages of each model and it will provide targeted management recommendations for governments, universities, research institutes, and enterprises to address specific challenges within different models. 

   The critical role of leading enterprises in the new national system for tackling key problems is becoming increasingly evident. Consequently, the formation and enhancement of their capabilities to achieve breakthroughs in core technologies require urgent attention and response. This study focused on the specific practices of Fangda Carbon, a leading enterprise in the carbon industry, in developing breakthrough capabilities for key core technologies during the advancement of high-temperature gas-cooled reactor graphite core components. It summarized the dynamic evolutionary mechanisms underlying the development of such capabilities in leading enterprises. The research found that: (1) The formation of breakthrough capabilities in key core technologies involves two stages: generation of phased objectives and assignment of corresponding meanings. By setting objectives tailored to different contexts and assigning matching significance, enterprises shape the necessary cognitive foundation for breakthrough capabilities. (2) The leap in breakthrough capabilities relies on the dynamic transformation of sensemaking modes, which evolve from "authoritative" to "inspirational" and then to "expansive" stages. Correspondingly, breakthrough capabilities progress through the "functional", "performance", and "architectural" phases. (3) The driving force behind the evolution of breakthrough capabilities is the enterprise′s sense of mission. This study will provide theoretical insights for improving China′s overall capacity for technological breakthroughs and accelerating the development of new quality productive forces.

 Artificial intelligence (AI) technology has become an essential tool for deepening the theoretical research on corporate innovation, thus increasingly embedding itself into enterprise innovation practices and significantly impacting innovation efficiency. Grounded in a corporate lifecycle perspective, this study leveraged the data from 1,103 Chinese hightech manufacturing enterprises listed between 2016 and 2021, by employing the decision tree analysis and multiple machine learning methods to examine AI′s heterogeneous effects on enterprise innovation across different lifecycle stages. The findings are as follows: (1) Most machine learning models demonstrate superior predictive performance in forecasting firms′ innovation performance (patent authorizations) compared to traditional linear regression models, highlighting machine learning′s capability in capturing nonlinear relationships among variables. (2) Enhancing AI capability and increasing AI patent filings significantly boost innovation capacity in maturestage firms, while the innovation performance of growth and declinestage firms depends less on AI technology. (3) The decision tree analysis further indicated that innovation in growth and maturity stages primarily relies on AI patent activities, whereas innovation in declinestage firms depends more heavily on the size of employees and technical personnel. Overall, while AI technology positively correlates with enterprise innovation performance, this relationship varies significantly across corporate lifecycle stages. This study will extend the lifecycle theory and provide practical guidance for enterprises on strategically deploying AI technology according to their developmental stages.
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   Accelerating artificial intelligence (AI) technological innovation is crucial for China to gain the strategic advantages in the new round of global competition and to promote the development of new productive forces. Intellectual property (IP) protection is an essential institutional arrangement for stimulating innovative vitality. However, given the typical characteristics of AI innovation, the effectiveness of IP protection in facilitating innovation remains unclear. Based on the identification criteria of AI patents released by WIPO, we constructed a dataset of over 330,000 AI patent applications from 273 Chinese cities from 2010 to 2021. On this basis, the research employed the intellectual property demonstration city policy as a quasi-natural experiment framework and applies a multi-period DID model to examine the impact of IP protection on AI innovation. The results indicated that the IP demonstration city policy significantly promotes urban AI innovation through mechanisms such as the agglomeration of scientific and digital talents, enhanced innovation-oriented public expenditure, and introduction of venture capital. The heterogeneity analysis showed that the incentive effect of IP protection is pronounced in collaborative patents, foundational technology patents, and the output of invention patents. Further research revealed that IP protection not only increases the quantity of urban AI innovation but also contributes to improving innovation quality. This study will provide detailed evidence for the impacts of IP protection on AI innovation and offer valuable implications for fully leveraging the incentive effects of IP policies.

    It is imperative to expedite the cultivation and advancement of an innovation ecosystem for marine ranches, underpinned by digital intelligence, to facilitate promotion of the high-quality development of the marine economy. The Hengxing Group was used as a case study in this paper, which employed the rooted theory approach to explore how digital intelligence technology reconfigures the elemental structure of the marine ranching innovation ecosystem. The study then went on to explore the process and characteristics of value co-creation in the marine ranching innovation ecosystem driven by digital intelligence technology. The study found that during the exploration period, enterprises concentrate on establishing digital intelligence innovation advantages and reinforcing value perception in digital intelligence through technology leapfrogging and strategic layout. During the linkage period, enterprises prioritize digital intelligence value reconstruction, thus expediting the development of digital intelligence infrastructure to achieve value chain optimization, and fostering the establishment of innovation consortiums. In the transformation period, enterprises attain ecological synergy and value co-generation through comprehensive refinement of operations and management and open innovation cooperation. The study has revealed the value of digital intelligence technology for the cultivation of innovation ecosystems in marine ranching, and it will provide some theoretical references and practical guidance for the high-quality development of the marine economy.

  Domestic substitution of critical components by specialized, refined, distinctive, and innovative (SRDI) enterprises is pivotal for the supply chain reinforcement. Low market adoption rates hinder domestic components from achieving iterative optimization through positive supply-demand feedback loops, resulting ‘cold-start paradox’ in domestic substitution. Currently, host manufacturers exhibit a collaboration gap in driving the iterative optimization of domestic components. There is an urgent need to explore how SDRI enterprises can play a proactive role in fostering a supply-demand virtuous cycle. This study employed the systematic methodology of extenics to construct an action framework of ‘context identification-barrier analysis-strategy generation’, aiming to explore pathways for resolving this paradox. The key findings are as follows: (1) The logic underlying the resolution of the ‘cold-start paradox’ in domestic substitution of critical components differs from that observed in complex product systems. The former is fundamentally a logic of market-driven performance optimization, while the latter is a logic of state-orchestrated original innovation driven by top-down institutional design. (2) Guided by the extenics logic of ‘contextual adaptation-barrier decoupling-targeted intervention’ to resolve the paradox, different contexts must be dynamically identified. Based on two dimensions: the stage of host-supplier co-evolution and the state of knowledge power, three archetypal contexts are identified: ‘niche integration-passive compliance’ ‘complementary following-proactive negotiation’ ‘innovation collaboration-equal consultation’. (3) Addressing the above contexts requires overcoming three core barriers: activating trial willingness, confirming reuse decisions, and sustaining adoption routines. Extension models are constructed to target the core issues of inadequate perceived value, unmet organizational satisfaction, and imbalanced benefit distribution. Applying extension analysis and transformations enables targeted breakthroughs against these three barriers. This research will provide SRDI enterprises with a universally applicable solution for resolving the ‘cold-start paradox’ in domestic substitution, which integrates theory with practice.

   The current complex and ever-evolving landscape has brought to the imperative question of how to facilitate the profound fusion of the digital economy and the tangible business world while concurrently bolstering the innovative capabilities of enterprises. This paper explored the underlying mechanisms through which economic policy uncertainty affects firm innovation, as well as the pivotal role played by digital transformation. Using the data from China′s A-share listed companies, this paper revealed a U-shaped relationship between economic policy uncertainty and firm innovation, the elevation of economic policy uncertainty fosters a surge in strategic innovation, while concurrently precipitating a decline in substantive innovation. After incorporating digitization into the analysis framework, it was found that enterprise digital transformation intensifies the negative impact of economic policy uncertainty on innovation. The U-shaped relationship weakens, and the inflection point shifts to the right, approaching an L-shape. Furthermore, the negative effects of digital transformation are more pronounced in companies with high financing constraints and low industry competition. This study will provide important policy implications for China to promote high-quality development in the ever-changing digital economy era. 

   Building organizational resilience has increasingly become an effective way for firms to cope with complex environments and achieve sustainable development in the era of digital economy. However, existing research lacks exploration of the organizational resilience building mechanism in digital transformation of enterprises. This paper conducted an exploratory single case study based on the digital transformation of Shengquan Company, and deconstructed the mechanism of organizational resilience building from the perspective of interactive memory system based on knowledge dynamic interaction behavior, and refined the logic behind the construction mechanism. The results showed that: (1) Organizational resilience under digital transformation is a special dynamic capability to cope with turbulent environments, and it is a dynamic interaction process of knowledge based on the transactive memory system; (2) Firms mainly build organizational resilience through the knowledge dynamic interaction process mechanism based on the transactive memory system of big data analysis, connection, and response; and (3) The creation logic is the core logic of the organizational resilience building mechanism under digital transformation. This paper has innovatively integrated the perspective of interactive memory system into the research of organizational resilience construction and the research conclusion will provide a reference for the cognitive and construction of organizational resilience of firms under digital transformation.

   Constructing an open innovation ecosystem is a crucial channel for enhancing innovation competitiveness. Although prior studies extensively discuss the established internal and external factors driving firms′ open innovation, there is a scarcity of research focusing on the role of firms as strategic leaders and the deep-seated logic behind this role. Based on the theory of firm behavior, this study used the data from Chinese listed companies from 2011 to 2021 and employed both fixed effects model and interaction effect model to test the hypotheses. The empirical findings revealed that when a firm′s actual innovation performance falls below its innovation aspiration, the firm will increase its openness to innovation in order to reshape their competitive advantage. Higher peer innovation willingness and analyst attention strengthen the perception of innovation pressure, thus promoting the positive effect of this relationship. Additionally, executives with R&D backgrounds and digital transformation empower problemistic search, enhancing the firm′s strategic responsiveness in increasing innovation openness, thereby reinforcing the facilitative effect of innovation performance expectation gap. The heterogeneity analysis revealed that in private enterprises and non-high-tech industries, the positive effect of the innovation performance expectation gap on the firm′s openness to innovation is more pronounced. This theoretical framework has organically combined the response decision under the innovation performance below aspiration with the perception of innovation pressure and problem-oriented search, thereby deepening and expanding the theoretical research on the behavior theory of the firm and innovation openness.

   In the context of digital transformation under the impact of unexpected events, the essence of structural change of enterprise innovation capability is the cumulative strategic change pivot triggered by value conflicts, leading to the generation, removal, maintenance, and enhancement of digital capability and innovation capability. This leads to a shift in capability structure from quantitative to qualitative changes. Our research, based on the exploratory dual case analysis method, selected two case samples, Ali Health and Ping′an Good Doctor to analyze the co-evolutionary trajectory of digital capability and innovation capability within enterprises that are strategically oriented towards achieving a delicate equilibrium between "short-term resilience" and "sustainable value". This investigation unfolded from the vantage point of understanding the formation of strategic change pivots. The research findings are as follows: firstly, a mixed value cognition transformation happened under the impact of unexpected event, shifting both from "economic" value to "economic-social" value and from "marketing" value to "marketing-service" value. This promotes enterprises to shift from short-term resilience orientation focused on survival construction, impact response, and crisis repair to sustainable value orientation focused on sustainable development, long-term orientation, and continuous adjustment. It drives co-evolution of digital capability and innovation capability. Secondly, under the orientation of "short-term resilience and sustainable value", reconfiguration of enterprise digital capability and innovation capability happen along with the addition, removal, maintenance, and enhancement of strategic change pivots triggered by mixed value cognition transformation. The short-term resilience-oriented capabilities are generated and removed, while the survival value-oriented capabilities are added, maintained, and enhanced. Thirdly, under the short-term resilience orientation, there exists a "Balance→Alternation→Coupling" capability co-evolution mechanism between digital capability and innovation capability, while under the survival value orientation, there exists a "Substitution→Parallelism→Spiral" capability co-evolution mechanism between digital capability and innovation capability. The significance of this research lies in its contribution to a more profound comprehension of the co-evolutionary dynamics between enterprise digital capability and innovation capability. This paper will contribute to existing research by identifying the composition of digital and innovation capability and two different types of co-evolution mechanism under "short-term resilience-sustainable value" orientation, which has depended existing understanding of capability co-evolution and strategic change pivot under the impact of unexpected events.

   Existing literatures mainly focus on the overall impact of green finance on green innovation, but generally overlook whether the upgraded green finance tool of energy efficiency credit can effectively stimulate the high-quality, substantive green innovation. Using the energy efficiency credit guidelines policy as a quasi-natural experiment, this study employed a difference-in-differences model with the data from A-share listed companies between 2012 and 2020 to examine the effect and mechanism of energy efficiency credit policy on corporate substantive green innovation. The results showed that the implementation of the energy efficiency credit policy effectively stimulates high-quality, substantive green innovation, but does not induce lowlevel, strategic green innovation. This has provided new micro-level evidence for the Porter Hypothesis. The mechanism analysis revealed that the policy promotes green innovation by attracting green investors, focusing executives′ attention on green issues, and reducing agency costs. The positive impact of the energy efficiency credit policy depends on the favorable moderating effects of factors such as differentiated strategies, internal controls, and media attention. Additionally, the policy has a more pronounced effect in regions with more strict financial regulations, a stronger gambling culture, and higher levels of digital economy development and social responsibility. This study will offer some microlevel evidence to support the acceleration of building a green finance system with Chinese characteristics.

   Resource combination is an effective way to alleviate resource constraints of enterprise green innovation, but little literature has paid attention to it. Based on the resource-based view and social network theory, this paper selected 139 pollutant discharge enterprises in Jiaxing, Zhejiang Province as research samples, adopted the fsQCA method, and analyzed the combined effect of 6 resources factors, including organizational networks, business networks, administrative networks, human redundancy, financial redundancy and technical redundancy on enterprise green innovations from the perspective of configuration. The results showed that: (1) organizational networks, business networks, administrative networks, human redundancy, financial redundancy and technical redundancy are not the necessary conditions to stimulate enterprise green innovations. (2) There are three resource combinations that can stimulate enterprises to adopt green innovations, including human resource driven mainly by internal exploitation, organizational networks driven by internal and external parallel, and administrative networks driven mainly by leveraging outside strength. (3) Different types of enterprises prefer different types of resource combinations through heterogeneity analysis: Large enterprises mainly leverage outside strength, and prefer organizational and business networks driven resource combination; SME mainly focus on internal potential exploration and prefer internal promotion resource combination; both hightech enterprises and general enterprises prefer exploration of their internal potentials. This paper will provide a new perspective to explain the contingency relationship of enterprises adopting green innovations, and those results will provide practical implications for revealing the multiple resource paths of enterprises in decisionmaking on green innovations, which are important for the public affairs department to design more precise environmental policy combinations to motivate enterprises adopting green innovations. 

   The enactment of the Environmental Protection Tax Law marks a pivotal milestone in formulating the fiscal policies for China′s green development. As a prototypical market-based environmental regulation tool, how environmental tax influences corporate green innovation has become a focal issue of concern for both academic and practical sectors. This paper examined the mechanism through which environmental tax affects green innovation among Chinese listed firms, from a perspective of tax policy implementation. Using a sample of A-share listed companies from 2018 to 2022, the study yielded several key findings: First, environmental tax has a significant positive effect on corporate green innovation. This effect is more pronounced among firms located in southern regions, those with higher levels of digitalization, and younger firms. Second, failure tolerance plays a moderating role in the relationship between environmental tax and green innovation—firms with higher failure tolerance exhibit a stronger positive response to environmental tax incentives. Third, the positive impact of environmental tax on green innovation is partly driven by resource reallocation: firms divert financial and technological resources away from other projects, leading to a crowding-out effect. Finally, the study found that as environmental tax expenditure increases, firms are more inclined to invest in substantive rather than symbolic green innovation initiatives. This paper has enriched the literature on how national environmental policies influence corporate green innovation strategies and it will offer a new perspective for assessing the relationship between environmental taxation and green innovation.

   The increasing complexity of scene elements drives the evolution of value-dominant logic on short video platforms, stimulating business model innovation. However, the mechanisms of this innovation remain unclear. This paper, using Kwai as a case study, delved into the mechanisms through which scene empowers business model innovation on short video platforms from the perspective of value-dominant logic evolution. The findings revealed three key insights: (1) Short video platforms evolve their value-dominant logic based on three core values: products, services, and emotional engagement. Through the systematic reconfiguration of supply chains, multidimensional interconnections within value chains, and the effective integration of scene chains, these platforms foster the development of ecommerce, community-based economies, and interest-driven economies. In doing so, the short video platforms empower innovation in business models. (2) Short video platforms, structured around supply chains, guided by value chains, and mediated through scene chains, dynamically align platform supply with consumer demand. They achieve a chain-like match between "platform supply realities" and "user consumption expectations" through the selective configuration of "business scenes—consumer expectations—commercial contexts". (3) Short video platforms connect contents through "discovery", enhance social interactions through "friends", and focus on interests through "following", dynamically realizing emotional alignments of "birds of a feather flock together", "people of one mind fall into the same group", and "scenes are constructed by interest" through scene storylines, relationship cognitive domains, and interest harmony scenes. The short video platforms, therefore, empower business model innovation through scene deconstruction, modification, and reconstruction.