New-quality productive forces are generated by scientific and technological innovation and the realization of key disruptive technological breakthroughs, and it is a powerful engine for high-quality development. New quality productive forces, with strategic emerging industries and future industries as the leading industries, are mainly involved in fields with strong innovation and advanced technologies and are committed to empowering regional high-quality development through scientific and technological innovation. In order to maintain a leading position in the competitive global environment and promote China's high-quality economic growth, it is necessary to stimulate industrial innovation through major disruptive scientific and technological innovations, facilitate transform and upgrade the industrial structure to create a new competitive advantage, and endeavor to cultivate the new quality productive forces.
The high-quality development of cities, as important spatial carriers and geographic activity units for economic and social development, remains an important issue of our time. Can new productive forces, as a key initiative to reshape new dynamics, be an important way to help cities develop in a high-quality manner If so, what is the internal logic of new-quality productive forces influencing the high-quality development of cities？ An overview of the existing literature shows there is a relative lack of empirical research on the relationship between the two. In view of this, this paper tries to put the new quality productive forces and high-quality urban development in the same research framework, and takes entrepreneurial activity as the starting point to explore the mechanism of new quality productive forces on high-quality urban development, so as to further provide a theoretical and practical basis for China's high-quality development.
Employing the panel data of 244 prefecture-level cities in China from 2011 to 2021, this study explores the intrinsic mechanism by which new quality productive forces affect the high-quality development of cities, using new quality productive forces as the entry point. Building on this foundation, the study examines the transmission mechanism through which new quality productive forces influence high-quality urban development by enhancing entrepreneurial activity, with entrepreneurial activity serving as the mediating variable. Subsequently, it delves into the non-linear influence of new quality productive forces on high-quality urban development at varying stages of industrial structure upgrading, talent concentration, and scientific and technological innovation. Then, the study investigates the non-linear impact of new productive forces on high-quality urban development when industrial structure upgrading, talent concentration, science and technology innovation are at different stages, and finally, it analyzes the spatial spillover effect of new productive forces on high-quality urban development according to the spatial levels.
The study finds that (1) new productive forces have a direct role in promoting high-quality development, and from the perspective of the financial environment of entrepreneurship and the level of talent capital, cities with a higher level of financial development and talent capital have an obvious role in promoting high-quality development; at the same time, entrepreneurial activity is an important channel through which the new productive forces promote the high-quality urban development. (2) The impact of new quality productive forces on high-quality urban development is affected by the threshold effect of industrial structure upgrading, talent concentration, and scientific and technological innovation level, and the impact of new quality productive forces on high-quality urban development presents a non-linear effect of increasing marginal utility under the development level of higher threshold variables. (3) The impact of new quality productive forces on high-quality development has a significant positive spatial spillover effect, and the development of local new quality productive forces can drive the high-quality development of areas with close economic ties.
Possible marginal contributions of this article are that,firstly, from the perspective of empirical measurement, the study explores the mechanism of the impact of new quality productive forces on high-quality urban development, and focuses on the impact of new quality productive forces on the high-quality development of cities; moreover, by incorporating industrial structure upgrading, talent concentration and scientific and technological innovation level into the analysis framework, it explores the threshold effect of the new quality productive forces on the high-quality urban development.

Advanced technology serves as the intrinsic impetus for the development of new-quality productivity. Moreover, disruptive technology represents an advanced level of technology and serves as the cutting-edge driver for the advancement of new-quality productivity. In essence, to cultivate and develop new quality productive forces, it is urgent to invest in innovation and optimize the allocation of high-quality production factors, and break through key disruptive technological innovations.
Since 2019, China has implemented the industrial policy of "chain leader system", with leading-chain enterprises as the main governance entities, committed to gathering resources and optimizing allocation, and smoothing key disruptive technological bottlenecks. The governance of industry chains, led by leading-chain enterprises, is a collaborative process that includes multiple parties, primarily overcoming resource limitations through institutional arrangements and focusing on addressing disruptive technological challenges.
To investigate the relationship between the industrial chain governance of leading firms and the enhancement of new quality productive forces, this study examines Chinese A-share listed companies from 2009 to 2022. It elucidates theoretically the impact mechanism of industrial chain governance of leading-chain enterprises on new quality productive forces, and the moderating role of market-oriented environment on this relationship. Furthermore, it examines the peer effects in industrial chain governance of leading-chain enterprises, and subsequently formulates relevant theoretical hypotheses and conducts empirical tests.〖HJ*3〗
The main innovations and marginal contributions of this article are reflected in four aspects. Firstly, the quantitative identification of leading-chain enterprises broadens the micro-identification scope for subsequent industrial chain research. Secondly, it measures the new quality productive forces and industrial chain governance levels of enterprises, providing a reference for studying the ecological dominance of leading-chain enterprises. Thirdly, the article conducts empirical tests to examine the promoting effect of industrial chain governance on new quality productive forces, as well as the peer effects of the market-oriented environment, thereby expanding the research on the economic impacts of industrial chain governance and the cultivation factors of new quality productive forces. Fourthly, the study explores the industry and regional peer effects of leading-chain enterprises' industrial chain governance, enriching the research on the peer effects of leading-chain enterprise behavior and offering guidance and reference for governments and enterprises to enhance industrial chain governance.
The main conclusions of this study are as follows: (1) The industrial chain governance of leading-chain enterprises can significantly improve the level of new quality productive forces. After a series of robustness tests, the research conclusion still holds; (2) The market-oriented environment can positively moderate the effect of industrial chain governance on improving new quality productive forces; (3) There is a significant industry peer effects in the industrial chain governance of leading-chain enterprises, and the industrial chain governance of enterprises in the same group of economic zones will significantly affect the industrial chain governance of enterprises in the same group of subordinate provinces.
This study provides the following suggestions for enterprises and governments. For leading-chain enterprises, firstly, it is necessary to enhance the agglomeration ability of new economic factors, follow the formation laws of new quality productive forces, plan the cultivation path of new quality productive forces, and leverage the agglomeration effect of new-quality labor and new-quality capital. Secondly, it is necessary to enhance the optimization combination and collaborative allocation ability of new-quality economic factors, lead the optimization and upgrading of supporting industries, coordinate and deploy multi-threaded research and development work, and achieve intensive resource management. For non leading-chain enterprises, it is necessary to coordinate with industry and regional leading-chain enterprises to gather high-quality economic factors, follow up on technological research and development trends, and simultaneously strengthen industrial supporting upgrading. For the governments, it is necessary to moderately adjust the boundaries of rights and responsibilities with leading-chain enterprises, strengthen the aggregation of new qualitative elements by leading-chain enterprises, expand the scope for optimizing the allocation of new-quality economic elements by leading-chain enterprises, furnish a comprehensive market environment and foundational systems for cultivating new quality productive forces by leading-chain enterprises.

Delving into the scenario paradigm and understanding how data elements facilitate the emergence of new quality productive forces is essential for advancing Chinese-style modernization. In the digital economy, data has become a key resource in global competition, with scenario-driven innovation emerging as a distinctive approach. Grasping the scenario paradigm and delving into how data elements facilitate the emergence of new quality productive forces is essential for advancing Chinese-style modernization. The essence of scenario-driven innovation lies in its ability to tightly integrate technology, market demands, and societal needs, thereby creating a dynamic and interactive ecosystem of innovation. Data elements serve as the connective tissue, enabling optimal resource utilization through precise analysis and forecasting, which in turn boosts production efficiency, technological innovation, and industrial upgrading.
Building on a profound understanding of the theoretical essence of scenario paradigms and new quality productive forces, this paper constructs a research framework of "vortex model" with resource allocation as the core and data elements empowering the co-evolution of "scenario-technological innovation-new quality productive forces". Considering the pivotal role of industry in the national economy, "Root Cloud" is selected as an exploratory case study. Initially, extensive secondary data is collected, and open coding is conducted to form first-order codes, which distill the typical operational characteristics and behavioral patterns of the case companies. Subsequently, first-order codes with similar characteristics are aggregated to form abstract and theoretical concepts, resulting in second-order themes. Finally, these second-order themes are synthesized to form an integrated theoretical dimension.
The study examines how Internet platform companies use data elements to foster new quality productive forces under varying industrial scenarios, identifying three key modes: "Product Intelligence," "Smart Manufacturing," and "Industrial Chain Ecology." The findings reveal that (1) optimizing resource allocation, which enhances the efficiency of production factor mobility, is a core indicator for forming new quality productive forces and achieving high-quality development. The integration of data elements with traditional factors, driven by the "digital hand," drives the overall reset of resource sequences and optimizes resource allocation, playing a catalytic role in the formation of new quality productive forces. There are differences in the coupling degree of productivity characteristics under different scenarios and the new quality productive forces.(2) Higher digital intelligence levels in scenarios correlate with more pronounced new quality productivity traits, especially in smart manufacturing and industrial chain ecosystems. (3) The iterative upgrade from "mechanical model - object model - connection model-composite object model" is a "bridge-type" factor for data elements to empower the emergence of new quality productive forces. Continuously innovating and optimizing models, through this series of upgrades, companies like Root Cloud can to accurately integrate data with physical equipment.
In summary, leveraging the advantages of scenario paradigms and harnessing the value of data elements is of significant theoretical and practical importance for accelerating the cultivation of new types of productive forces. This study not only enriches the theoretical connotations of scenario-driven innovation and new types of productive forces but also provides new perspectives and strategies for the realization of Chinese-style modernization. Firstly, the development and utilization of data value are essential. It is a necessary path to achieve new quality productive forces by enhancing the construction capabilities of digital models and optimizing data analysis capabilities, involving data elements in the construction of new quality production factors. Secondly, leveraging scenario advantages to drive technological innovation is crucial. Innovation can be driven by thoroughly exploring data element applications in key fields, identifying specific scenario needs, and aligning data supply with these demands. This approach not only fosters technological advancements but also integrates scientific and technological outcomes into critical development scenarios. It aids in the transformation of traditional industries and nurtures strategic, emerging, and future industries through the creation of digital scenario frameworks. Thirdly, it is important to capitalize on the large scale of data elements and the advantages of the new national system so as to guide the effective supply of market-oriented data elements, promote the industrialization and commercialization of data elements, and open up new tracks to promote the emergence of new quality productive forces.

Promoting the sound and fast development of new quality productive forces is a crucial step for China to respond to the new challenges of the global science and technology revolution and industrial transformation in the new era and achieve high-quality economic development. In the context of the digital era, the infiltration of digital technologies such as big data, artificial intelligence, and blockchain into the real economy has given rise to new models and industries such as smart manufacturing and digital agriculture, and changed the way traditional industries produce and operate. The integration of digital economy and real economy has become an important systemic base and strategic driving force for the development of new quality productive forces. However, infrastructure bottlenecks and uneven regional development limit the role of digital-physical integration in promoting the development of new quality productive forces. How to further promote the integration of digital economy with real economy, with a focus on developing new quality productive forces, is a key question that must be addressed at present.
Existing research has addressed the role of economic activities generated in the process of digital-physical integration in promoting new quality productive forces, but it has not yet clarified how digital-physical integration can better form new quality productive forces. In fact, no single factor can adequately elucidate the intricate dynamics propelling the advancement of new quality productivity; thus, a broader perspective is essential for a more holistic understanding. While a one-size-fits-all approach is insufficient for guiding regions in selecting development drivers that align with their unique circumstances, necessitating further investigation into diverse pathways tailored to specific realities. Additionally, empirical research that systematically examines the evolution of data-physical integration and its qualitative influence on new quality productivity remains scarce.
Considering the complex interactive effects of the elements of digital-physical integration, this paper, based on the view of complex systems, constructs an analysis framework of "digital foundation-digital industry-digital finance-industrial structure-industrial agglomeration-industrial chain modernization" for digital-physical integration. It uses the dynamic qualitative comparative analysis method to analyze and reveal the relationship between the path evolution of digital-physical integration and the emergence of new quality productive forces in the case of 30 provinces, autonomous regions, and municipalities across China from 2013 to 2022.
The research results show that (1) neither the digital economy nor the real economy possesses a single, indispensable condition for fostering high new quality productive forces. (2) In the aggregated configuration analysis, there are mainly three constituting pathways, namely, digital finance empowerment type, full-chain digital upgrade type, and high-tech industry agglomeration type. (3) A comparison of the configuration results indicates that a robust digital foundation and a thriving digital industry are pivotal in catalyzing new quality productive forces during digital-physical integration, whereas digital finance and industrial agglomeration exhibit a substitutable relationship. (4) The inter-group analysis shows that the aggregated configuration has a temporal universality, while the formation of new quality productive forces has undergone an evolutionary process from high-tech industry agglomeration-oriented to digital finance empowerment-oriented and further differentiation. (5) The intra-group analysis indicates that the formation of new quality productive forces requires tailored development, and the agglomeration-oriented configuration of high-tech industries is suitable for areas where the industrial chain is not yet fully developed, while areas with better digital finance development are more poised to cultivate new quality productive forces.
This paper establishes an analytical framework of "digital economy-real economy" linkage configuration for the emergence of new-quality productive forces, revealing the complex causal relationships behind the emergence of new-quality productive forces. It analyzes the development of new-quality productive forces, which has undergone a transformation from the regulation of a materialized economic system to the regulation of a virtualized economic system. The paper has developed the perspective of complex systems regarding the creation of new technologies.Furthermore, it offers tailored recommendations for enhancing new-quality productive forces, tailored to local contexts, such as bolstering the construction of digital infrastructure and the digital industry, encouraging and supporting the development of digital finance, and accelerating the industrial chain's modernization.

It is well acknowledged that integration of S&T (science and technology)and economy is the core of innovation-driven development strategy and the inevitable requirement for achieving high-quality economic development; however, the integration of S&T and economy in China is far from being satisfactory, and this issue has been hindering the high-quality development of China′s economy. The existing experience has proved that there is much room for improvement in the innovation system and China′s overall innovation capability. China adheres to the "two-wheel drive" of S&T innovation and institutional innovation so as to promote the realization of innovation ecology through the integration of mechanisms, and accelerate the penetration and diffusion between S&T and the economy.
The construction of "Innovation China" promoted by the China Association for Science and Technology (CAST) in 2020 is an institutional innovation with the integration of various mechanisms and cross-border synergy of multiple subjects, and it is also a practice of multi-entity collaborative innovation ecology. On the basis of 19 typical cases of "Innovation China" from 2020 to 2021 and other research materials, the paper starts from the three dimensions of "innovation subject—innovation resources—innovation environment", uses the grounded theory of qualitative research method and NVivo11 software-assisted coding to deeply analyze the mechanisms and paths of integration of S&T and economy at the present stage to provide theoretical and practical ideas for better integration of S&T and economy in China.
The results show that there are three key mechanisms in the integration of S&T and the economy, which are the cooperative mechanism of multiple subjects, the market-led resource integration mechanism and the dynamic evolution mechanism of the innovation ecosystem. With the guarantee of the three mechanisms, various regions will choose appropriate paths for the integration of S&T and economy according to their actual conditions, including the paths of resource matching, platform building, and ecological creation. The three paths will be deepened step by step to promote efficient coordination between scientific and technological innovation and economic development. Specifically, the three key mechanisms are interlinked and interact with each other, and the three are inseparable. In the integration of mechanisms, they jointly ensure better integration of S&T and the economy. Firstly, the cooperative mechanism of multiple subjects is the prerequisite for the effective connection between technological demand and supply, and it is an important foundation for the evolution of the innovation ecosystem. Secondly, the market-led resource integration mechanism is an important direction of science and technology development, the key to truly promoting the transformation of the innovation chain into the industrial chain, and a breakthrough to form a good innovation ecology under the market mechanism. Thirdly, the dynamic evolution mechanism of the innovation ecosystem is the systematic support for the dynamic and continuous improvement of the economic integration of science and technology and the environmental guarantee to promote the continuous connection of science and technology supply and demand and the full integration of innovation resources in the market.
Starting from many typical cases of "Innovation China", the paper fully explores the mechanisms of the integration of S&T and economy shown in the cases by using the grounded theory, and puts forward three alternative paths of the integration of S&T and economy, which provides systematic theoretical and practical ideas for solving the problem of “two skins” of S&T and economy in China. Then, the paper puts forward further policy suggestions for reference. However, there are some deficiencies in the study. For instance, the universality of the conclusions based on the typical cases and local research data of "Innovation China" is yet to be verified. In the future,researchers could conduct additional research on various innovation subjects and other pilot cities (parks) other than CAST to avoid the sample bias in the paper as much as possible, and further enrich the research results of the paper by analyzing quantitative data to verify the improvement effect of S&T and the mechanism of economic integration on the integration degree of science and technology.

Academic engagement is a main channel to transfer knowledge achievements to the industrial field, and it is an important source for shaping industrial competitive advantage. With the accelerated evolution of the new round of technological revolution and industrial transformation, the importance of academic engagement is becoming increasingly prominent. Currently, little is known about whether and how academic engagement affects academic entrepreneurial performance, and the conclusions of research based on different geographical contexts are even divergent. Due to the differences in the inherent logic and action rules between scientific research and social service activities, academics participating in industry-university cooperation face dual pressures of role identity and institutional norms. Therefore, in the special institutional and cultural context of China, how academics integrate conflicting roles to effectively promote the transfer and transformation of scientific and technological achievements is a problem worthy of further exploration.
Following role identity theory and institutional theory, this study constructs a research framework in which academic engagement is the independent variable, role identity is the mediator, a conductive institutional environment is the moderator, and academic entrepreneurial performance is the result. It further explores the mechanism and boundary conditions of academic engagement affecting academic entrepreneurial performance, which will deepen the understanding of the micro-process of entrepreneurship and achieve results in conflict-changing situations. Through a questionnaire survey, valid sample data from 368 academics is selected, and an empirical analysis is conducted using SPSS and the Bootstrap method.
The results indicate that, as a proactive behavior of individuals, academic engagement has a positive impact on academic entrepreneurship performance. Role identity plays a partial mediating role between academic engagement and entrepreneurial performance. In the process of engagement, academics can accelerate the integration of different roles and create more value by assuming the responsibilities assigned to them. The conducive institutional environment significantly affects the positive relationship between academic engagement and academic entrepreneurial performance. The conducive environment positively enhances the effect of academic engagement on academic entrepreneurial performance and also has a positive moderating mechanism on the mediating effects of role identity between academic engagement and entrepreneurial performance.
The main contributions of this paper include three aspects. Firstly, it enriches the research on academic engagement in the Chinese context. According to the analysis of the connotation of academic engagement, this paper integrates role identity theory and institutional theory to construct a research framework for the impact of academic engagement on academic entrepreneurial performance and promotes the application of role identity theory and institutional theory in the field of academic engagement by exploring the core issue of whether and how academic engagement affects academic entrepreneurial performance. Secondly, the mediating mechanism and boundary conditions of academic engagement on academic entrepreneurial performance are clarified. By incorporating the two variables of role identity and the conducive environment into a unified analytical framework, the interaction between the two variables is explored, which advances the understanding of the internal logic of academic engagement on academic entrepreneurial performance, and also enriches the contextual factors affecting academic entrepreneurial performance. Thirdly, it provides a new method for effectively evaluating the results of academic engagement. The proposed formula for calculating the academic engagement index can cover these activities involving different terms, similar nature, and overlapped implementation processes, thus avoiding the disadvantages of using a single activity (indicator) for evaluation. This is crucial for evaluating the results of academic engagement, for it is helpful to address the differences in the current literature and further deepen the evaluation and understanding of academic engagement.
This study provides practical insights into successful industry-university relationships: firstly, the government should actively create an environment that encourages academic engagement; secondly, universities may consider the establishment of more specialized institutions and assistance for scientists to focus on promoting the deep integration of industry-university cooperation; thirdly, academics who lack personal industry connections or experience should attach importance to cultivating awareness and the ability to integrate different roles.

Resources, energy and ecological environment have become important factors impacting China's economic development, and it is urgent to explore a new sustainable development path that coordinates the economy and environment. As an important content of implementing the sustainable development strategy, the improvement of ecological efficiency at the provincial level is the top priority of all to promote the "win-win" of the economy and environment. The large-scale use of emerging technologies such as artificial intelligence can realize the intelligence of the entire industry, promote resource utilization in the production process, reduce pollutant emissions, and effectively balance the relationship between the economy and environment, so as to improve provincial ecological efficiency. There has been some progress in academic studies on industrial intelligence, but no study has explored the relationship between industrial intelligence and provincial ecological efficiency. In view of this, with the panel data of 30 provinces (excluding Tibet) in the Chinese mainland from 2010 to 2021, this paper explores the impact of industrial intelligence on provincial ecological efficiency and the regional heterogeneity of this impact. The mediating role of green technology innovation and the moderating roles of industrial agglomeration and green finance are also explored.
The conclusions of this study include four aspects. Firstly, industrial intelligence impacts provincial ecological efficiency positively; industrial intelligence has significant promoting roles on provincial ecological efficiency in the eastern and central regions, but has no significant promoting role in the western region. Secondly, green technology innovation plays a partial mediating role in the impact of industrial intelligence on provincial ecological efficiency. Thirdly, industrial agglomeration plays a U-shaped moderating role in the impact of industrial intelligence on provincial ecological efficiency. Finally, green finance plays a positive moderating role in the impact of industrial intelligence on provincial ecological efficiency.
The theoretical contributions include four aspects. Firstly, different from previous studies, from the perspective of industrial intelligence, this paper verifies its positive impact on provincial ecological efficiency, clarifies the different impacts of industrial intelligence on provincial ecological efficiency of different regions, and makes a useful supplement to studies of industrial intelligence. Secondly, this paper clarifies the path role of green technology innovation in the impact of industrial intelligence on provincial ecological efficiency, and provides a new idea for the study on how industrial intelligence promotes the improvement of provincial ecological efficiency. Thirdly, this paper reveals the nonlinear role of industrial agglomeration in the impact of industrial intelligence on provincial ecological efficiency, and enriches relationship study of industrial agglomeration, industrial intelligence and provincial ecological efficiency. Finally, this paper verifies the situational role of green finance in the impact of industrial intelligence on provincial ecological efficiency, and expands the integration study of green finance and industrial intelligence on provincial ecological efficiency.
This paper provides several suggestions for relevant departments. Firstly, relevant departments can establish special funds to support industrial intelligence technology study, and can also guide industries to actively explore the application of intelligence technology, and build an ecosystem of the interconnected upstream and downstream of industrial chain, so as to promote the improvement of provincial ecological efficiency. In addition,the regions should promote the development of industrial intelligence according to local conditions so as to improve provincial ecological efficiency. Secondly, relevant departments can formulate environmental protection regulations and green emission reduction standards, etc., and effectively promote green technology innovation. Thirdly, when the level of industrial agglomeration is low, relevant departments should guide all industries to realize division and cooperation and complementary advantages according to resource endowment. Otherwise, when industrial agglomeration reaches a certain level, relevant departments can guide industries to cooperate with universities and research institutes, provide platforms and resources for industrial intelligence, so as to improve provincial ecological efficiency. Finally, relevant departments can adopt green fiscal policies to guide funds to the green field, and can also guide industries to effectively use funds in the development of industrial intelligence, so as to improve provincial ecological efficiency.

With the vigorous rise of a new round of technological revolution and industrial transformation, digital technology has become a new driving force for global innovation and development. As the most innovative and dynamic industry, the innovation capability of high-tech industries directly affects national technological strength and international competitiveness. In this context, how to use digitization to stimulate the innovation vitality of high-tech industries has become an important issue of widespread concern in the academic community.
Previous studies have revealed that digitalization can positively impact innovation and promote an increase in innovation investment. A few scholars have subdivided innovation investment and studied the impact of digitization on different types of innovation investment. But there is still a lack of research on the internal segmentation of innovation investment and the impact of digital transformation on different types of innovation investment. Due to significant differences in resource requirements, knowledge base, risks, and benefits among different types of innovation activities, the impact of digitalization on different types of innovation investment will also be different. It is necessary to explore the differential impact of digitalization on different types of innovation investment from a heterogeneous perspective. Most existing studies have classified innovation into exploratory innovation and exploitative innovation based on its novelty and knowledge base. Both types of innovation essentially belong to R&D innovation, and the important role of non-R&D innovation has long been ignored. However, the innovation foundation of China's high-tech industry is weak, the innovation endowment has regional heterogeneity, and non-R&D innovation still plays an important role, and the proportion of non-R&D innovation investment in China's high-tech industry has been more than 16% in the past five years. In the context of digitalization, it is necessary to distinguish innovation investment in high-tech industries into R&D innovation investment and non-R&D innovation investment, and further explore the mechanism of digitalization affecting the two kinds of innovation investment. In addition, the government and market are important external driving forces for enterprise innovation, and the government's behavior and market role cannot be ignored. Thus, this study further explores the moderating roles of the intensity of government support and the level of marketization in this process.
With China's high-tech industry as the research object, the study constructs a theoretical framework for the impact of digitalization on heterogeneous R&D investment. Using provincial panel data on high-tech industries from 2012 to 2021, it empirically tests the differential impact of digitalization on different types of innovation investment, and further explores the mechanisms of government and market. The results show that digitalization has a significant promoting effect on both R&D innovation investment and non-R&D innovation investment in high-tech industries, and its marginal impact on R&D innovation investment is much higher than that of non-R&D innovation investment. The mechanism test shows that digitalization has different mechanisms for different types of innovation investment. Digitalization increases R&D innovation investment by increasing R&D personnel, and increases non-R&D innovation investment by promoting industrial agglomeration. Further analysis reveals that the intensity of government support can strengthen the promoting effect of digitalization on R&D innovation investment, but it will weaken the promoting effect of digitalization on non-R&D innovation investment. The degree of marketization significantly suppresses the positive effect of digitalization on R&D innovation investment, but has no significant moderating effect on the relationship between digitalization and non-R&D innovation investment, resulting in market failure.
Compared with existing literature, this study divides innovation investment into R&D innovation investment and non-R&D innovation investment, and includes the two types of innovation investment in the same analytical framework for comparative research, making up for the limitations of existing literature's excessive emphasis on R&D innovation and neglect of non-R&D innovation. Then, from the dual perspectives of the government and the market, it explores the differences in the moderating effects of the two in the process of digitalization affecting high-tech industry innovation investment, provides a theoretical basis for promoting a better combination of a promising government and an effective market, and gives full play to the role of the government and the market in the field of innovation.

In the digital economy, it is crucial to cultivate a data element market and encourage enterprise participation in the market-oriented circulation of data elements. However, existing theories have not developed an effective analytical framework for understanding the dynamic factors of enterprise data element supply. Due to the unique characteristics of data elements compared to other production elements, current research primarily consists of theoretical studies and lacks empirical analysis, which hampers the ability to effectively explain the complex synergistic mechanisms of dynamic factors. Therefore, how to realize the effective incentivization of data release and participation in market-oriented circulation becomes a critical issue.
To address this important question, this study follows the theories of potential difference and push-pull and aims to construct an analytical framework for the dynamic factors of enterprise data element supply from the perspectives of internal and external forces. Specifically, internal forces include data potential and economic benefits, while external forces encompass government support, data differentials, demand differentials, capability constraints, and risk constraints. Examining these forces is crucial for understanding the motivations and barriers that influence enterprise participation in data element supply activities. The study employs the NCA and fsQCA methods to analyze the configuration effects among a sample of 311 senior executives from data-driven enterprises. These methods enable a nuanced examination of the synergistic effects of various dynamic factors and provide a comprehensive understanding of the conditions that generate a high willingness to supply data elements.
The study yields several significant conclusions. Firstly, the key internal (data potential and economic benefits) and external (government support, data differentials, market demand, capacity constraints, and risk constraints, etc.) dynamic factors affecting the supply of data elements to enterprises are identified and the importance of dynamic factors such as data potential and data differentials is emphasized. Secondly, the formation of willingness to supply data factors is the result of multi-condition synergistic effects, without the presence of necessary conditions for the generation of high willingness. Thirdly, the study identifies five pathways that lead to high willingness to supply, and these five pathways are able to reflect the fact that different enterprises, in the light of their own actual situation, can achieve a high level of willingness to supply through a combination of internal and external dynamic factors. Fourthly, the study summarizes three dynamic models: "government support-market demand driven", "internal-external driving force synergistic driven" and "government support-data potential driven". A cross-sectional comparison of the three dynamic models shows that stronger government support and market demand play a universal role in high willingness to supply. Thus, to promote the generation of high willingness among enterprises, the two-wheel drive combining government support and market demand becomes the key. The government should actively explore the implementation of relevant incentives and support policies according to their characteristics, support the main body of enterprises’ supplying data elements, and stimulate the entry of more market demand for data elements to create a stable policy environment and a good market order. Meanwhile, when selecting the appropriate dynamic model, enterprises need to consider the context and specific circumstances, tailoring their approach to participate in data element supply more effectively.
This paper contributes significantly in three aspects. Firstly, this paper enriches the relevant research from a configurational perspective. Taking into account the characteristics of data elements that distinguish them from other production elements, a systematic analytical framework is proposed, which remedies the inadequacy of previous results that have mostly studied single-dimensional conditions of incentives or disincentives. Secondly,it extends the research scope of potential difference theory and push-pull theory and extends their application to data elements supply research, which is a useful supplement to the existing research based on potential difference theory and push-pull theory. Finally, the current research on data element supply is still at the stage of theoretical exploration, with a predominance of qualitative analysis in the literature and relatively few empirical studies. This paper pioneers the integration of NCA and fsQCA methods into the research on data element supply, enriching the methodological approaches in this field.

Basic scientific research serves as the cornerstone for enterprises to achieve breakthrough innovation; however, currently, it has not received enough attention from enterprises. In recent years, enterprises account for only about 5% of China's investment in basic research, significantly lower than the 23% to 36% seen in developed countries. In fact, the Chinese government has consistently encouraged the establishment of the state key laboratories (SKLs) in enterprises. Distinguished from the SKLs established in universities and research institutions, the SKLs in enterprises primarily focus on addressing the future development demands of society and industries, and conduct applied basic research and pre-competitive common technology research. Regrettably, the academic community has primarily focused on the output characteristics and economic consequences of SKLs in universities and research institutes, paying less attention to SKLs in enterprises. Considering that basic research, as a typical public good, has a low monopoly and lacks direct commercial value, it is still uncertain whether the construction of SKLs in profit-maximizing enterprises can promote basic research, leading to the first question: Can and how does the construction of SKLs promote basic research in enterprises? This study further argues that the impact of SKLs on basic research varies due to differences among enterprises, and thus, it intends to verify if the effects of utilizing SKLs for basic research differ among enterprises of different scales and industries. Third,some scholars have pointed out that there might be a negative correlation between basic research outcomes and the market value of enterprises in specific industries. Existing studies have focused on whether enterprises engaged in basic research can generate technological value or market value, but they have ignored the crucial issue of how to enhance the value of basic research. Therefore, the third issue addressed in this paper is: Are the basic research outcomes generated within the enterprise SKLs more valuable?
Shanghai and Shenzhen A-share listed companies from 2005 to 2020 are taken as the research objects, and the control samples are screened by the PSM model to screen control samples. After screening, 3 864 annual observation samples are obtained, totaling 345 listed companies. Among them, 160 enterprises with SKLs are the experimental group, and the remaining 185 enterprises are the control group. The impact of SKLs construction on enterprise basic research is empirically tested by the PSM-DID method. The results indicate that SKLs construction promotes enterprise basic research, bringing a significant increase in the quantity of basic research outcomes, although the improvement of the quality of basic research outcomes is not significant. These effects of SKLs construction are more pronounced in large enterprises and industries with low competition levels. Moreover, the SKLs construction can increase the internal knowledge stock of enterprises, improve the ability of enterprises to absorb external knowledge, promote technological innovation, and create technological value, while also enhancing human capital, transmitting positive signals, and enhancing market value. In short, it improves the technological value and market value of basic research, particularly high-level basic research.
This study presents several novelties. Firstly, it enriches the research on the operational impact of SKLs. Secondly, through the utilization of the scenario of batch construction of SKLs in enterprises, the empirical research effectively eliminates the interference of parallel economic events, reduces endogenous noise, and establishes a clearer causal relationship between SKLs construction and enterprise basic research. Subsequently, it examines the impact of the construction of SKLs on the value of enterprise basic research, shifting the research focus from the commonly-explored question of "whether basic research can create value" to the neglected key proposition of "how basic research can create value". Finally, the study suggests that the government should enhance support for enterprise SKLs, strengthen the construction of talent teams within these laboratories, and expedite the system construction of basic research property rights protection to better incentivize enterprises to engage in basic research.

The incubator has played an important role in supporting the growth of new ventures and promoting the rapid development of the regional economy. However, the homogeneity of ventures in the incubator hinders effective value transformation. While most of the existing studies on the growth performance in the context of ecosystems are from a single perspective. On the one hand, the situational characteristics of ecosystems need to be further refined. On the other hand, the micro mechanism of the interaction between new ventures and the ecosystems needs to be further explored. As a complex and dynamic whole, the interdependence and collaboration among the various elements are crucial for creating value and maximizing the overall benefits in an entrepreneurial ecosystem. So how to make use of the ecological benefits provided by the incubator to promote the high-quality development of new ventures has become an urgent problem for both the theoretical and practical circles.
Using resource orchestration theory and strategic matching theory as theoretical foundations, this study focuses on 27 companies that have established a presence in the incubation parks, are actively engaged in physical operations, and have been recognized for their exemplary roles within the park, such as being designated as technology, manufacturing, or service demonstration enterprises. These companies are selected for their representativeness, innovative capabilities, and growth potential, offering valuable insights and inspiration to other businesses. Additionally, the study uses the criterion of being in operation for less than 8 years to identify and include new startups in the analysis. To enhance the reliability and validity of the survey, this study employs well-established scales from both domestic and international sources to craft the questionnaire items. The questionnaire is tailored to the research context following preliminary interviews, and is administered through on-site research and interviews conducted offline. Then the fsQCA method is used to explore the complex mechanism of the interaction between the actors of new ventures and the resource context in the entrepreneurial ecosystem from the perspective of configuration.
It is found that, firstly, there is not any single factor that constitutes a necessary leading to high/non-high growth performance, but resource diversity plays a general role in high growth performance path. Secondly, there are two equivalent configurations of the high-growth performance path, which can be further summarized into “making money by leveraging the situation” and “intensive collaboration”. There are two equivalent configurations of the non-high growth performance path, which can be further summarized as the “compound the difficulty” and the “dreamer with no action”. Thirdly, in a situation where resources are diverse but lack complementarity, the combination of resource capacity and resource leverage and the entrepreneurial ecological orientation can be effective substitutes for each other.
The managerial enlightenments of the paper are as follows. Firstly, new ventures should recognize the important role of resource diversity in achieving high growth performance, either by obtaining resources through diversified channels, or promoting the efficient absorption and utilization of resources. Secondly, new ventures can also broaden their ways of obtaining resources. For example, implicit resources through cooperative learning or explicit resources from the external environment to build resource combination. Taking the entire ecosystem as a whole, new ventures can better integrate themselves into the entrepreneurial ecosystem and achieve high-performance growth. Finally, new ventures should explore multiple paths of achieving high growth performance in the situation, and adjust their strategic orientation and resource management behavior flexibly.
This study has certain limitations regarding the size and scope of the sample, which could be mitigated by employing larger sample sizes or alternative quantitative analysis techniques. The current dataset lacks the depth and breadth required for a comprehensive analysis. For future studies, it is recommended to incorporate temporal dimensions and utilize the sophisticated Time Series Qualitative Comparative Analysis (TSQCA) method to examine panel data. This approach would provide a more nuanced understanding of how the interplay between resource context, resource orchestration, and entrepreneurial ecosystem orientation influences the growth performance of emerging ventures.

Spin-off technology enterprises are featured with unique attributes and laws. By introducing and absorbing core resources such as technology and knowledge of the parent enterprise, it moves into the organizational practices and processes of the parent enterprise so that it has competitive ability and advantages in the early stage of its establishment to promote the upgrading of enterprise value chain. The current environment is constantly changing, and dynamic capability emphasizes that spin-off technology enterprises should remain sensitive to the external environment and exert dynamic capability in their development process to promote enterprises to enhance entrepreneurial vitality, form competitive barriers, and achieve value chain upgrading. However, few scholars have explored the dynamic capability of spin-off technology enterprises and have not paid attention to the change and intermediary role of dynamic capability in different stages of value chain upgrading. Therefore, following the theory of dynamic capability and from the perspective of dual innovation, this paper aims to answer what dynamic capabilities spin-off technology enterprises should have at different development stages, and in what paths these dynamic capabilities promote the upgrading of enterprise value chain.
This paper chooses Western Superconducting as the research object and draws on the grounded methodology proposed by Jia Xudong and Heng Liang. In this case study , it builds a relationship model of "dynamic capability of spin-off technology enterprises, dual innovation and value chain upgrading at different development stages" with the aim of opening the "black box" of dynamic capability of spin-off technology enterprises to promote the value chain upgrading process. First, key events in different development stages of Western Superconducting are coded, and relevant concepts are continuously gathered to form the initial category. Second, by using STRAUSS and CORBIN's conditional action-outcome model, the categories derived from open coding are linked together and summarized into nine main categories, i.e., the ability to identify opportunities, integrate resources, learn, change and make upgrades, utilize innovation, explore innovation, and realize upgrading of process , product and function upgrading.Finally, on the basis of an in-depth excavation of the abstraction level, the core category is summarized, the correlation between the core category and the main category is determined, and the relationship model implied in the specific phenomenon is extracted to form the story context.
Through the case study, it is found that (1) the dynamic capability of spin-off technology enterprise is represented by opportunity identification, resource integration, learning and absorption, and transformation and renewal; (2) the dynamic capability of spin-off technology enterprise varies in different development stages, promoting the upgrading of enterprise value chain: the embryonic stage is represented by opportunity identification, resource integration, learning and absorption; the initial stage is represented by opportunity identification, learning and absorption; and the growth stage is represented by opportunity identification, learning and absorption; (3) dual innovation plays a mediating role in the dynamic capability of spin-off technology enterprises and the upgrading of their value chain. The research conclusions have certain contributions.Firstly, this paper focuses the dynamic capability theory on spin-off technology enterprises, explores their different dynamic capability hierarchy at different development stages, and expands the research boundary of dynamic capability theory. Secondly, from the perspective of dual innovation research, it reveals the effective path of dynamic capability of spin-off technology enterprises to promote the upgrading of value chain, and defines the intermediary role of dual innovation. Thirdly, this paper uses the grounded theory research method to make up for the shortcomings of traditional quantitative research methods. Fourthly, this paper clarifies the different dynamic capabilities of spin-off technology enterprises in different development stages, which provides a solid basis for the cultivation of science and technology enterprises. Finally, by exploring the dynamic capability of spin-off technology enterprises,it manages to refine the mechanism of its effect on the value chain upgrading of enterprises to provide reference for the value chain upgrading path of spin-off technology enterprises.

Basic research plays a significant role in driving scientific and technological innovation. With the increasingly severe global competition in science and technology, it is challenging for individuals or single organizations to carry out basic research on their own. Collaborating with others is an effective way to solve common problems in basic research. Scientific collaboration with external partners helps in acquiring complementary scientific knowledge, which eventually enhances the sustainable innovation capability of enterprises. However, scientific collaboration poses serious challenges, including coordination problems, absorption difficulties, and intellectual property protection dilemmas for "little giant" firms which are the core of high-quality small and medium-sized enterprises (SMEs). Therefore, in order to promote the high-quality development of SMEs, it is crucial to explore ways to integrate basic and applied research through scientific collaboration.
The existing literature focuses on the analysis of the impact of the breadth and depth of business or technological collaboration on firms' innovation activities, but the importance of scientific collaboration in promoting the integration of basic and applied research is neglected. Although the existing studies have explored the impact of collaboration with different types of bridging scientists on firms' innovation from a human capital perspective, little is known about the specific ways in which firms engage in scientific collaboration. Recently, some scholars have observed scientific collaboration from the perspectives of social network and social capital, but the role of scientific collaboration breadth and depth on firms' technological innovation processes is understudied. Moreover, scant research has turned the gaze on the boundary conditions of openness to scientific collaboration. Meanwhile, scholars have been highlighting the importance of investing in basic research to enhance self-reliance and self-improvement in science and technology. This investment is expected to bring a breakthrough in bottleneck technology. However, most of the relevant literature focuses on the basic research investments of large and medium-sized state-owned enterprises. Besides, the collaboration modes with colleges, universities, and other research institutes have been discussed, but there is a lack of in-depth analysis of the specific ways of scientific collaboration among SMEs and its role in the technological innovation of firms. Additionally, there is a scarcity of empirical research in this regard.
Following the theory of inter-organizational learning and the lens of knowledge recombination, this paper focuses on the role of scientific collaboration breadth and depth in the exploratory innovation of "little giant" firms. It also examines the moderating roles of firms' knowledge diversity and the technological turbulence of the external environment. By analyzing the paper publication records and patent application data of 933 "little giant" firms during the period of 1997 to 2020, it is confirmed that scientific collaboration breadth and scientific collaboration depth have an inverted U-shaped and negative impact on "little giant" firms' exploratory innovation, respectively. Besides, with the increase in knowledge diversity, the inverted U-shaped relationship between scientific collaboration breadth and exploratory innovation becomes steeper, while the negative relationship between scientific collaboration depth and exploratory innovation becomes weaker with the increase in technological turbulence. Considering the negative impact of scientific collaboration on exploratory innovation, "little giant" firms should concentrate limited resources on expanding partnerships and technological fields to identify, absorb, and integrate heterogeneous scientific knowledge and information. Meanwhile, the findings also suggest "little giant" firms should enhance their cooperation stickiness with partners to defend against uncertain external risks.
This paper makes an important contribution to the theoretical framework of inter-organizational learning and cross-boundary knowledge search. It reveals the complex relationship between different types of scientific collaboration behaviors and exploratory innovation. Additionally, the paper comprehensively analyzes the boundary conditions of scientific collaboration's role in exploratory innovation activities. The research on "little giant" firms is not rich and mostly focuses on R&D collaboration issues in large and medium-sized enterprises; thus, this paper enriches the existing literature. By revealing how SMEs can design scientific collaboration strategies to promote exploratory innovation, this paper provides both theoretical support and practical insights for the scientific collaboration on exploratory innovation of the "little giant" firms.

With the continuous development in data science, artificial intelligence, blockchain, and other fields, digital technology has become a new means for enterprises to redefine business models, improve organizational structures, and enhance customer experiences. Digital transformation has become one of the key directions for promoting high-quality economic development and building a world-leading technological nation. The comprehensive abilities and teamwork of executives are particularly crucial for agilely formulating corporate strategies. Executive team stability is a critical factor, referring to the continuity and consistency of top management over a certain period. It represents a well-balanced state achieved through multiple rounds of bargaining among various stakeholders, reflecting the cohesion and synergy of the team. Thus, there come the questions of whether executive team stability supports the sustained execution of strategies for digital transformation, aiding in the corporate digital development, or if it contradicts the demands for internal organizational changes and adjustments, thereby hindering the corporate ability to adapt to market demands and the competitive environment, ultimately reducing the likelihood of successfully completing digital transformation. Differing from traditional literature that explores the driving factors for digital transformation, such as corporate capabilities, ownership structure, and government subsidies, this paper examines the factors affecting digital transformation from the perspective of organizational behavior. It identifies and tests the specific paths through which executive team stability influences digital transformation, clarifying the relationship between executive team stability and digital transformation, which is of significant importance in guiding practical business decisions and improving the success rate of digital transformation.
On the basis of the data from listed companies on the Shanghai and Shenzhen Stock Exchanges from 2010 to 2021, this study focuses on the micro-level entities of corporate executives to explore the guiding role of executive team stability in digital transformation. The analysis reveals that a stable executive team has a significantly positive impact on digital transformation, specifically by increasing R&D investment to provide technological support, reducing short-termism among executives to provide long-term strategic support, and enhancing corporate governance to create a favorable environment, thus effectively promoting digital transformation in enterprises. Furthermore, heterogeneity analysis demonstrates that the role of executive team stability in facilitating digital transformation is particularly pronounced in mature companies, companies with executives having financial backgrounds, and companies in high-tech industries.
The findings uncover the intrinsic mechanism of how the executive team assists in digital transformation, enriching the research on the economic outcomes of executive changes and the factors influencing digital transformation. Moreover, it provides critical policy reference for achieving digital transformation and high-quality development in China's current business environment.
The contributions and innovations of this paper are as follows. Firstly, within the framework of "executive team stability (executive changes)-R&D investment/short-termism/corporate governance (path selection)-digital transformation decisions (organizational behavior)", this study identifies and tests the mechanism and paths through which executive team stability influences digital transformation, unveiling the "black box" of how executive team stability affects digital transformation decisions, thereby enriching the research on the factors influencing digital transformation and providing essential policy references for China's current goal of achieving digital transformation. Secondly, compared to existing research on the relationship between executive teams and digital transformation, this study broadens the research scope by selecting all listed companies on the Shanghai and Shenzhen Stock Exchanges as the research sample, which is more universally applicable than studies focused solely on traditional manufacturing companies; by focusing on heterogeneity at the corporate, executive, and industry levels, it explores how the role of executive team stability in digital transformation is influenced by variations in corporate lifecycle, executive financial backgrounds, and industry contexts, aiming to provide targeted advice for companies with different characteristics to optimize their digital transformation strategies. Lastly, regarding research methods, this paper conducts word frequency statistics and manual selection based on recent national-level policies related to digital transformation, resulting in a total of 238 digital transformation keywords. This approach allows for a more comprehensive and accurate assessment of digital transformation within companies, enhancing the credibility and persuasiveness of the research.

Employee creativity, as the starting point of innovation and a prerequisite for organizational success, garners substantial attention from both managers and researchers. However, many enterprises often witness employee performance falling short of their full potential, with human resources being underdeveloped and underutilized. Therefore, many researchers are examining the role of human resource management (HRM) in fostering employee creativity. HRM involves the human resource plans of enterprises. But individuals have their own ways of processing information, and employees may not always perceive certain concepts or policies according to the organization′s intentions. Perceived developmental human resource management (PDHRM) is the employees′ perception that the degree of support and input from organizational HRM in their development has been proven to have a positive impact on employees′ attitudes, behaviors, and performance. However, research on how PDHRM affects employee creativity is still in the exploratory stage.
Previous studies have preliminarily validated the impact and utility of developmental human resource management from the perspective of information transmission based on signal theory. In view of this, this study further explores the mechanism and boundary conditions of the impact of PDHRM on employee creativity from the perspective of social information processing theory.
This study focuses on job autonomy perception, which refers to the degree of freedom, independence, and self-determination of employees in the work process. It aims to figure out the mechanism by which PDHRM affects employee creativity. It employs a quantitative research method to propose and test research hypotheses based on the social information processing theory. The study hypothesizes that PDHRM has a significant positive impact on employee creativity and perceived job autonomy; and perceived job autonomy plays a mediating role between developmental human resource management perception and employee creativity.
Specifically, this paper presents a mediating model in which PDHRM influences employees′ creativity through perceived job autonomy and discusses the moderating role of organizational structure at the cross-level. The single-point questionnaire survey conducted among 108 executives and 754 employees from 108 enterprises in Shanghai,Jiangsu,Shandong and Anhui. A multi-level analysis performed using Mplus7.4 provides results indicating that PDHRM has a positive impact on employees′ creativity, and the mediating effect of perceived job autonomy is moderated by organizational structure. Specifically, when the organizational structure tends to be organic, it enhances the positive influence of PDHRM on perceived job autonomy. Simultaneously, PDHRM exerts a more indirect and positive influence on employees′ creativity through the mediating role of perceived job autonomy.
The findings of this study make contributions to the existing literature in several ways. Firstly, this study explores the mechanism through which PDHRM influences employee creativity, thereby enhancing academic understanding of the relationship between HRM and employee creativity. Additionally, it provides an analytical foundation for comparing the effects of different types of HRM. Secondly, combined with social information processing theory, it explains the mediating role of perceived job autonomy in the process of employee creativity influenced by PDHRM. It offers a new explanatory basis for understanding the relationship between PDHRM and employees′ work attitudes, behaviors and output. Thirdly, this study verifies the moderating effect of organizational structure, revealing the conditions under which PDHRM can enhance employees′ perceived job autonomy. It expands academic understanding of the functional form of organizational structure and the boundary conditions under which PDHRM is effective, while also responds to the call for refining research on the impact of HRM.
Finally, this study provides inspiration for enterprises dealing with the changes of internal and external factors, as well as strategic requirements at different stages of development. This includes exploring and adopting PDHRM, ensuring employees′ autonomy, and timely adjusting their organizational structure. Follow-up research can make multi-time point measurements or adopt experimental methods to demonstrate causal relationships between variables; in order to improve the objectivity of creativity assessment, it is feasible to make peer evaluation to measure employee creativity; future research can further control intrinsic motivation and other types of human resource management to improve the reliability of research results when revealing the relationship between triggering factors and employee creativity.