Green data elements are a new type of production factor that can create green value for production entities and serve as an important source for cultivating new quality productive forces. Based on expounding the connotation and characteristics of green data elements, the promoting effect of green data elements on the high-quality development of manufacturing enterprises was explored. Using empirical data from China's Shanghai and Shenzhen A-share listed manufacturing enterprises from 2015 to 2022, the results indicate that green data elements have a positive impact on the high-quality development of manufacturing enterprises, manifested in the dual improvement of economic and social benefits. Data foundation support and executives' green experience positively moderate the relationship between green data elements and the high-quality development of manufacturing enterprises. Suggestions for future avenues of inquiry are proposed, including investigations into the measurement of green data elements embedding, the intermediary mechanism of digital-green synergy, the heterogeneity effect from the perspective of production factor collaboration, and examinations of boundary conditions at both the macro-regional and micro-enterprise levels. The focus on green data elements has played a positive role in advancing the theoretical study and practical exploration of the scene-based application of data elements.

New quality productive forces is not only a new driving force for China's economic growth, but also a booster of high-quality development. New quality productive forces was generated by the revolutionary breakthrough of technology. And emerging digital technology has become one of the most important means, which empowers the new quality productive forces through mechanisms such as realizing the digital transformation of the three elements of productivity, promoting the significant improvement of production efficiency, creating new fields and new tracks, cultivating the growth of emerging industries and future industries, leading the optimization and upgrading of traditional industries with digital-real integration, and forming green productivity through low-carbon transformation. From the perspective of specific development paths, the effective implementation of representative emerging digital technologies, such as artificial intelligence, industrial robots, metaverse, and digital content, has strengthened the quality of factors of production, spawned new demands, new forms and new modes, and increased the momentum for the development of new quality productivity. In the future, China should firmly grasp the role of emerging digital technologies in promoting new quality productive forces, increase the investment in innovation in the field of emerging digital technologies, actively cultivate innovative talents in the field of emerging digital technologies, and improve the construction of a modernized industrial system to support the development of emerging digital technologies, so as to accelerate the formation and growth of new quality productive forces.

As an innovative theory formed in the process of China's modernization, the organic combination of new quality productive forces and digital transformation is a major theoretical challenge at the current historical stage. The relationship between digital transformation and new quality productive forces was empirically examined through a study of China's A-share listed manufacturing companies from 2013 to 2023. Results indicate that digital transformation contributes significantly to the new quality productive forces. Further research found that digital transformation contributes to new quality productive forces by improving firms' technological innovation capabilities, and that executives' digital background plays a positive moderating role between digital transformation and new quality productive forces. Heterogeneity analysis showed that the marginal effect of digital transformation to improve the new quality productive forces of enterprises is more significant in state-owned enterprises and enterprises in the central and eastern regions. The findings provide a theoretical foundation for enterprises' digital transformation in generating new quality productive forces and offer valuable references and inspirations for exploring specific implementation paths.

As a long-term state policy, talent strategy is of great significance to national development and regional construction. The key to the construction of a high-quality talent system is to optimize the development environment for scientific and technological innovation, so as to achieve an increase in the sustainable efficiency of talent introduction. Based on this, the DPSIR-DEA-Malmquist index model was built. The 31 Chinese provincial (Due to the lack of data, the statistical data mentioned here do not include the Hong Kong Special Administrative Region, the Macao Special Administrative Region and Taiwan Province.) talent introduction activities from 2014 to 2020 were taken as the research object, and the sustainable efficiency of talent introduction was analyzed. Further, considering the practical significance of the technological innovation climate for talent introduction activities, the threshold regression was then used to analyze its impact mechanism. The results show that the sustainable efficiency of provincial talent introduction in China has been steadily demonstrated and continuously enhanced, and the regional differences have been significantly narrowed in both the geographical and spatial and temporal levels. The decomposition of Malmquist index in the level of technical efficiency shows an "N-shaped" trend, which is basically relatively consistent with the trend of Malmquist index. However, the index of technological progress shows a trend of "M-shaped", indicating that it is not the upward driving force for the improvement of the sustainable efficiency of talent introduction. The role of technological innovation climate in talent introduction of all stages has been tested by the threshold effect of technical efficiency. When the technical efficiency crosses the threshold of 1.775, scientific research service personnel, national policy-based education funds and continuous funds all have a significant and positive impact on the sustainable efficiency of talent introduction. Therefore, the current situation of emphasizing talent recruitment over utilization should be changed. The construction of the scientific-tech innovation atmosphere should be intensified. The sustainable efficiency of talent introduction should be given full play. These are regarded as the keys to reversing the Matthew effect of the talent strategy and promoting the regional scientific development.

The popularity of AI big models has set off a wave of AI investment, innovation, and application worldwide. From the perspective of industrial policy system, industrial talent cultivation, industrial technology research and development, industrial security creation, and industrial ecological construction are included in the analysis framework, and the industrial policy analysis framework to promote the development of AI grand model in the United States was constructed. At present, the development of China's AI big model industry has made a series of achievements, including the increasing improvement of the policy design to promote the development of AI big models, the increasing enrichment of the number and type of domestic AI big models, and the increasing number of users and applicable scenarios of AI big models. However, there are a series of shortcomings and shortcomings in terms of lack of technology, lack of human resources, ecological construction, international cooperation, etc., thus resulting in the slow development of related industries. So, it is necessary to systematically increase R&D investment in AI, actively cultivate and introduce AI talents, make efforts to build an AI ecosystem, and comprehensively promote international cooperation in the field of AI, in order to promote the construction of China's AI big model industrial policy system and further realize the rapid development of the industry.

As the most dynamic market entities, small and micro enterprises (SMEs) play a significant role in promoting China's economic development. Therefore, SMEs have always been the key support target of China's tax reduction policies and the focus of scholars' attention. The literature collection process was first introduced, with an analysis of literature characteristics and an exploration of the basic connotation of “SMEs” from multiple perspectives. Secondly, based on the dual perspectives of micro-enterprise operations and macroeconomic impacts, the research findings on the effectiveness of tax reduction policies for SMEs were comprehensively reviewed. After that, the main factors influencing the tax reduction effects for SMEs were analyzed from three aspects: the tax system, micro-enterprises and macroeconomic environment. Furthermore, the optimization path for tax reduction policies for SMEs was discussed. Finally, the current research deficiencies related to SMEs were analyzed, and four directions that future research in this field should focus on were pointed out. These include conducting in-depth research on the implementation effects and impact mechanisms of tax reduction policies for SMEs, thoroughly examining the linkage effects among tax reduction policies and between tax reduction policies and other macroeconomic policies, introducing more precise analytical tools to enhance the accuracy and effectiveness of tax reduction policy design, and conducting international comparative studies to provide references for the improvement of tax reduction policies in China.

The dual goals of green financial policies are to direct funds into green industries and promote the transformation of polluting enterprises. A differenceindifferences model was utilized to examine how the Green Credit Guidelines, introduced in 2012, affected the performance of polluting enterprises. Data from 968 nonfinancial listed companies on the Ashare market in China between 2004 and 2017 were analyzed. The Green Credit Guidelines are found to reduce both the shortterm and longterm performance of enterprises in heavily polluting industries. This negative impact is achieved through the channels of financing constraints, investment constraints, and internal control quality effects. After the implementation of the Green Credit Guidelines, the scale of investment by polluting enterprises in fixed assets, intangible assets, and other longterm assets decreases. The financing constraints of polluting enterprises measured by the SA index tighten. The management status of polluting enterprises measured by the internal control quality index deteriorates. Heterogeneity analysis shows that the Green Credit Guidelines has a more obvious impact on the performance of stateowned polluting enterprises and polluting enterprises in areas with low marketization and weak environmental regulation. Reliable evidence is provided on the impact of green credit on the economic performance of enterprises at the micro level, and policy insights are given on how green finance policies can aid in the green transformation of polluting enterprises.

New quality productive forces, spurred by scientific and technological innovation, are the key driving factors leading global innovative and sustainable development. Science and technology innovation enterprises, as the core force driving technological breakthroughs, play a crucial role in promoting the development of new quality productive forces in China. Therefore, exploring how these enterprises leverage technological breakthroughs to achieve the formation of new quality productive forces is of paramount importance. Based on resource orchestration theory, Chengzhi Yonghua was taken as a case study and employs an exploratory case analysis method to deeply analyze the process of how science and technology innovation enterprises utilize breakthroughs in key core technologies to promote the formation of new quality productive forces. It finds that in the three stages of material technology breakthrough, full-chain technology upgrading, and multi-dimensional industrial layout, core technologies have advanced from autonomy to diversification and then to high-end development. Driven by resource orchestration strategies, the strategic positioning has shifted from domestic technology breakthrough to market expansion leadership and finally to technology innovation leadership, while the productive forces have evolved from a substitutive form to an innovative form and ultimately to new quality productive forces. It opens the "black box" of the process by which breakthroughs in key core technologies by science and technology innovation enterprises drive the formation of new quality productive forces, providing practical guidance for the development of new quality productive forces within these enterprises under the context of technological innovation.

In order to continuously do a good job in talent work,and further build a talent strong country with high quality, and achieve high-level technological self-reliance and self-improvement, in recent years, especially since the 18th National Congress of the Communist Party of China, the relevant functional departments of the country have successively issued many talent policy documents to promote the gradual optimization and improvement of the talent policy system in China. Based on the systematic review of 808 talent policy texts released at the national level since the 18th National Congress of the Communist Party of China, a three-dimensional analysis framework of "ideas-goals-tools" talent policy was construsted. Then, based on the LDA topic generation model, methods such as word frequency analysis and topic analysis for in-depth investigation were comprehensively used. It can be discovered that China's talent policy embodies the unity of principle, planning, and operability in the conceptual dimension, emphasizes systems and institutional mechanisms reform and clear feasibility in the goal dimension, and highlights flexibility, practicality, and collaborative innovation in the tool dimension. Overall, the systematic features of talent policy are quite obvious.Based on these results, it is suggested that the core concept of“talent is the first resource”should be adhered,efficient and clear policy objectives should be set, a balanced combination of policy tools should be constructed,promoting the linkage and cooperation between policy concepts, policy objectives, and policy tools should be accentuated at the same time.

Resistance to change plays a key role in the success or failure of organizational change, and most studies regard change resistance as a negative change reaction behavior. Recently, some scholars believe that resistance to change has not only negative side, but also positive side. However, there is no relevant measurement tool to represent the full connotation of resistance to change, which will affect the academic and practical circles' comprehensive understanding of resistance to change. Based on grounded theory, the literature on resistance was combed to change and open interviews with enterprise workers was conducted, the connotation and structure of resistance to change in depth was exploved, and a resistance to change scale was developed. And through the content validity, structure validity and criterion validity of the resistance change scale, the measurement scale was revised and verified. The results show that resistance to change consists of two dimensions, individual orientation and organization orientation, with a total of seven items. In addition, further empirical research is conducted to test the differentiated impact of individual-oriented and organization-oriented resistance to change on turnover intention. It is clarified the connotation and structure of resistance to change and developed a measurement scale of change resistance, which provided a reference and measurement basis for expanding the theory of organizational change and condensing the behavior law of change response.