With the deepening of globalization, latecomer firms continue to emerge in the market and are gradually evolving from innovation catch-up to innovation frontier. Although there are already latecomer firms that are fully developed and gradually located in the leading position in the innovation ecosystem, there is little research on the mechanism of the dynamic process of catching up with the leading firms based on the same innovation ecosystem in the context of innovation catching up. By analyzing the longitudinal case study of the fire-fighting enterprise Tanda, the analytical framework of "catching-up pressure-catching-up process-catching-up result" was built. It is found that in the ecological integration stage, the three windows of opportunity, namely, technology, system and market, comprehensively identify and guide enterprises to adopt different strategic responses, which expands the research on the coupling of windows of opportunity and strategy. In the innovation catching-up stage, the evolution of innovation is characterized by a progressive trend from "imitation innovation-independent innovation-collaborative innovation". The integration of innovation ecology shows a gradual deepening process from "embedding" to "evolution" to "stabilization", and realizes its own ecological position in the innovation ecosystem. It is help to provide reference ideas for further research on the theory of window of opportunity, to further improve the research on catching up of latecomer enterprises in China, and to expand the theoretical research system of innovation ecosystem.

Based on the data of A-share listed companies in Shanghai and Shenzhen from 2012 to 2022 to measure the level of new quality productive forces of enterprises (NQP), a multi-period difference-in-differences model was constructed to study the impact of data factor agglomeration on the new quality productive forces of enterprises with the national-level big data comprehensive experimental zone as a quasi-natural experiment. It shows that data factor agglomeration promotes the development of new quality productive forces of enterprises, and this conclusion still holds after PSM-DID, placebo test and other robustness tests. Mechanism tests show that data factor agglomeration can empower the development of firms' new quality productive forces by improving human capital level and promoting green technology innovation; with the increase of industry competition and media attention, the role of data factor agglomeration in promoting firms' new quality productive forces increases. Heterogeneity analysis shows that the effect of data factor agglomeration on new productivity of enterprises is more significant in non-state-owned enterprises, technology-intensive enterprises, high-tech industries and regions with better digital infrastructure. The findings provide insights into how to utilize new factors of production to cultivate new productivity.

Different fresh-keeping efficiency of fresh e-commerce platform leads to differences in product freshness and price, which affects consumers' purchase decisions. At present, the competition in the fresh e-commerce market is fierce and the operation is chaotic. In order to scientifically guide the healthy development and operation of the fresh e-commerce platform, the competition model of the duopoly fresh e-commerce platform was constructed based on Hotelling. The product freshness competition and price game of the two fresh e-commerce platforms under the influence of fresh efficiency were studied, and the effects of consumer characteristics and preservation efficiency on the competition game of the two fresh e-commerce platforms were discussed. The results show that the fresh e-commerce platform with high fresh-keeping efficiency has low unit fresh-keeping cost, and the strategy of providing high-freshness and high-price products is effective, and vice versa. For fresh products, no matter what the consumers' characteristics are, the low-price strategy can not effectively seize the market share. therefore, the fresh e-commerce platform should improve its fresh-keeping efficiency, reduce the fresh-keeping cost, and effectively profit from the high-tech freshness and high-price product strategy.

In the era of digital economy, digital technology innovation has become a core factor driving China's economic development. Based on the data of China's A-share listed companies and the list of the top five suppliers and distributors of listed companies from 2009 to 2022, the impact and mechanism of digital innovation in upstream and downstream enterprises of the industrial chain on digital innovation in midstream enterprises. By combining international patent classification with text analysis method, digital innovation patents was empirically investigated to characterize the level of digital innovation. The results show that the improvement of digital innovation levels in upstream and downstream enterprises significantly promotes digital innovation in midstream enterprises, indicating a significant positive spillover effect in the industrial chain. This effect is more significant in upstream enterprises, enterprises in the same industry, and enterprises with the same ownership type. Technological knowledge diffusion and market performance incentives are the two channels for the spillover effect. The micro-mechanisms of spillover effects among upstream, midstream, and downstream enterprises within industrial chains are revealed. Theoretical references and practical insights are provided for promoting digital innovation and key technological breakthroughs in enterprises, as well as facilitating the integration of the digital economy with real economy along industrial chains.

The Third Plenum of the 20th Central Committee of the Communist Party of China further emphasized the need to accelerate the cultivation of new quality productive forces, and pointed out the construction of a national integrated technology and data market, and the promotion of market-oriented reforms in factors. New quality productive forces is the inheritance and innovation of Marxist productivity theory, and data elements interact with other production factors through their own characteristics, thus nurturing new quality labor materials, nourishing new quality labor objects, shaping new quality labor force, and becoming an important quality of new quality productive forces. But this process is also accompanied by practical problems such as insufficient labor capacity, imbalanced supply and demand of labor objects, unsmooth transformation of labor materials, imperfect technological innovation mechanisms, and insufficient development of emerging industries, which hinder the high-quality development of new quality productive forces. In view of this, it is urgent to take important discourse on new quality productive forces as guidance, build a comprehensive talent training system, and consolidate the source of the formation of new quality productive forces. Promote market-oriented allocation reform of data elements and smooth the path of new quality productive forces growth. Form a tripartite collaboration among the government, market, and enterprises to improve the support system for new quality productive forces. Deepen the construction of the scientific and technological innovation system to adapt to the rapid changes in new quality productive forces. Build strategic emerging industrial clusters, build a solid foundation for the development of new quality productive forces, and then accelerate the formation of new quality productive forces to promote Chinese path to modernization.

To accelerate the construction of data factor market, activate the 'vitality' of market development and optimize the 'order' of resource allocation. It is urgent to build a multi-level and multi-agent data factor ecosystem and its new mechanism of market incentive and effective supervision and collaborative governance, so as to effectively promote the circulation and utilization of data factors and the release of value, and give full play to the role of data as a new factor of production to empower the development of new quality and productivity. Based on this, the hierarchical structure of the data element market was analyzed, the economic theoretical logic and social welfare effects of data element value creation was explained, and a collaborative governance model for data element value creation with five main entities includin government, supply side, demand side, platform, and data merchant was constructed. Propose to build an ecosystem of "market led, government guided, and supply-demand linkage" throughout the entire process and chain of data element circulation and trading, with multiple linkage and co construction, in order to activate the development vitality of the multi subject and multi-level data element market and achieve high resource allocation efficiency of data resource elements. Explore the regulatory priorities and their shifts at different stages, and clarify the principles of synergy between market incentives and effective government regulation. Finally, propose implementation path suggestions for the process of data element valuation, in order to promote the high standard supply, efficient circulation, high-level application, and effective supervision of data elements, and achieve high-quality development of the data element market.

As the new round of technological revolution and industrial transformation deepens, the integration of the digital economy and manufacturing has become a key force in driving industrial upgrading. The theoretical framework known as the "techno-economic paradigm" refers to the economic patterns that emerge after technological innovation reshapes the macro and microeconomic structures and operational models. It reveals the evolutionary process through which the digital economy empowers the transformation and upgrading of manufacturing, spanning the stages of "technological system-economic structure-social institution." Although the focus of U. S. policies related to the digital economy may differ, they essentially adhere to the evolutionary logic of the "Techno-Economic Paradigm." These policies revolve around digital top-level design, digital technology development, digital talent training and cultivation, digital collaborative innovation, and the digital ecosystem. The ultimate goal is to drive the evolution of enterprises, industries, and economic systems, thereby achieving the digital transformation and upgrading of the manufacturing sector. In light of the current challenges faced by China's manufacturing industry, efforts to empower manufacturing transformation through the digital economy should focus on strengthening top-level design and policy frameworks, enhancing technological innovation and standards development, bolstering digital talent support, promoting collaborative innovation in all aspects, and building a hierarchy of manufacturing enterprises.

Traditional industries are a crucial part of the national economy and play an essential role in the development of new quality productive forces. Due to their large scale and major role in the economic structure, these industries face challenges in digital and intelligent transformation. The Industrial Internet platform is key in bridging the gap between old systems and new economic drivers, helping to advance the development of new quality productive forces. A case study of HBIS Group was used to explore the theoretical logic and practical paths of Industrial Internet platforms in this process. The theoretical framework is based on the structure of "data + models + computing power + applications. It focuses on key areas such as factor innovation, technological innovation, industrial upgrading, green development, and industrial park clusters. A three-part empowerment model was created, covering strategic leadership, scenario-driven applications, and ecosystem integration. Five main implementation paths are identified: ensuring independent control and strengthening data foundations, using steel industry strengths to push technological innovation, promoting green development for environmental gains, building an industrial ecosystem for transformation and upgrading, and enhancing industrial park clusters for better collaboration. These insights provide useful guidance and recommendations for developing new quality productive forces in traditional industries.

Based on China's Land Economic Survey (CLES) data, empirical analysis was conducted on the impact of internet use on farmers' land transfer behaviors using models such as Eprobit, Eregress, and PSM-DID. The 4-way counterfactual total effect decomposition method was employed to verify the "synergistic" mechanism between the internet and social relationship networks. The research findings are as follows. Internet usage can further optimize land factor allocation and facilitate farmers' land transfer. Mechanism analysis indicates that strong social networks only have an intermediary effect, while weak social relationship networks have both intermediary and interactive effects, implying the transformation of the agricultural land transaction market. Further analysis reveals that the synergy between the internet and weak social relationship networks can effectively promote the transaction connection between small farm entities and new management entities. Internet usage leads to the long-term and contractualization of land market transactions. The results show that internet usage is of significant importance in weakening the constraints of social relationship networks and promoting the effective connection between small-scale agricultural economies and modern agriculture.

In an innovation-driven market environment, creative deviance in employees is increasingly observed in modern enterprises. To explore individual factors influencing creative deviance behavior, a moderated mediation model was constructed grounded in the proactive motivation framework. The study investigated the influence of narcissistic employees on creative deviance through creativity-driven norm-breaking motives. Additionally, the moderating role of employees' sense of occupational calling is explored. Based on 375 survey responses from employees in innovation positions, it was found that narcissism significantly enhances creative deviance. Creativity-driven norm-breaking motives mediate the relationship between narcissism and creative deviance, while the sense of occupational calling positively moderates both the direct effect of narcissism on creativity-driven norm-breaking motives and the mediating effects. The findings provide insights into the literature on creative deviance and offer guidance on directing employee creative deviance.