The involvement of major energy-exporting countries in geopolitical conflicts can easily lead to volatility in international energy markets and have an impact on the world economy. Based on a macroeconomic model and using counterfactual analysis and vector autoregression, the differential impacts of geopolitical conflicts on different economies through the volatility of the energy market was analyzed, and China's response measures based on the perspectives of energy security and national security was put forward. The results show that geopolitical conflicts have negative impacts on different economies through crude oil market volatility, with the European economy, which is more dependent on Russian energy, being affected to a greater extent. It is recommended to pay great attention to the risk of geopolitical conflicts, accelerate the formation of a diversified pattern of crude oil imports and energy consumption, stabilize investor expectations, improve the construction of the capital market and maintain the stability of the RMB exchange rate, so as to prevent the negative impacts that geopolitical conflicts may have on China's energy security.

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 impact of artificial intelligence (AI) on the labor market, based on the Routine-Biased Technological Change paradigm, is widely acknowledged. However, existing job classification methods lack detail and accuracy. To address this limitation, the Chinese-BERT-wwm model was optimized to classify recruitment data from listed companies between 2013 and 2019 into routine and non-routine jobs, achieving a test set accuracy of accuracy of nearly 93%. Additionally, the GLM4 model was used to match job titles and descriptions to the "Chinese Occupational Classification (2022 Edition)" to identify digital occupations and analyze the impact of AI technology on labor demand structure. Empirical results show that higher AI technology levels significantly increase demand for non-routine jobs and reduce demand for routine jobs, with pronounced effects in non-state-owned enterprises, high-tech industries, and manufacturing. Further analysis reveals that the increased demand for non-routine jobs is primarily driven by growth in non-routine cognitive positions. Mechanism analysis shows that AI adoption increases non-routine job demand through productivity effects and the creation of new digital occupations, while reducing routine job demand through substitution effects. It expands the application of large language models in economic text analysis.

Advanced scientific and technological advancements, particularly artificial intelligence (AI), are recognized as the driving force behind the emergence of new quality productive forces. The paths and mechanisms of influence between AI and productivity, however, remain unclear. A comparison between new quality productive forces and traditional productivity was first conducted, followed by an elucidation of the characteristics of new quality productive forces elements at the employee, enterprise, and industry levels, along with the application characteristics of AI. At the employee level, the “automation-enhancement" pathway was studied, along with Al's role in capability integration, learning, and reconfiguration. At the enterprise level, Al's role in enterprise functions such as marketing, innovation, and strategic decision-making is studied. Also, the structuring, restructuring, and utilization of resources are investigated. Additionally, the research delves into Al's role in shaping industry-level dynamics via the industrial, innovation, capital, and talent chains, and the mechanisms of labor substitution, spillover integration, technological innovation, and ecological synergies. Recommendations are made to support new quality productive forces development in the short, medium, and long terms. Knowledge on AI's role in new quality productive forces is expanded by the exploration, and discussion with related research is fostered.

Talent governance is the cornerstone of local governance modernization. However, some regions excessively prioritize talent competition in reality, exacerbating the issue of governance fragmentation. A single-case study of talent governance practices in S Province was conducted from the theoretical perspectives of holistic governance and performance management to explore how local governments address governance fragmentation through the integration of policy tools and governance mechanisms, thereby responding effectively to the dual logic of talent governance: enhancing external competitiveness and optimizing internal resource allocation. The findings indicate that the talent governance system in S Province achieves structural coordination, functional integration and external collaboration through top-level design, while its implementation is energized by a performance evaluation mechanism centered on goal accountability. Grounded in the case analysis, the practical pathways and intrinsic mechanisms of the talent governance system in S Province are deeply analyzed, and a practical framework for local talent governance under the dual-logic perspective is developed, which provide some reference for advancing the modernization of local talent governance.

The increasing role of artificial intelligence (AI) technology as a core driver for manufacturing industry transformation has revealed that enterprises' deficiencies in data resource integration and internal management constitute major obstacles to intelligent-driven upgrading. To address this issue, based on the resource orchestration theory, Chinese A-share listed manufacturing companies from 2007 to 2022 were conducted to investigate the impact and mechanism of AI technology on the transformation and upgrading of manufacturing enterprises. It is found that a significant positive correlation is identified between AI technology adoption and manufacturing enterprise transformation, which remained consistent through endogeneity and robustness tests. AI technology also can promote the transformation and upgrading of manufacturing enterprises through two independent mediating effects of enhancing the application level of data factors and improving the quality of internal control, as well as the chain mediating effect of the two. The impact of AI technology on the transformation and upgrading of manufacturing enterprises in non-state-owned, technology-oriented mergers and acquisitions, fast-changing technology-related industries, and high-tech industries is greater. These conclusions expand the mechanism of AI technology in the transformation and upgrading process of manufacturing enterprises and provide a theoretical basis and practical reference for enhancing their transformation and upgrading capabilities.

As a strategic emerging technology, artificial intelligence (AI) plays a significant role in guiding future societal transformation and has an empowering effect to help enterprises realize disruptive innovation. However, there is still a lack of in-depth analysis of the key elements and mechanisms of AI empowering enterprises to realize disruptive innovation in academia. The impact path of AI-empowered disruptive innovation for enterprises remains unknown. The exploratory multi-case study method based on Grounded Theory was applied to construct a theoretical model of AI empowering enterprises to realize disruptive innovation, and the fuzzy-set qualitative comparative analysis method was employed to explore the complex causal mechanism of AI empowering disruptive innovation in enterprises. The results highlight that five key factors for achieving AI-driven disruptive innovation in enterprises are service ecology, cooperation network, technological transition, context-depth-excavation, and organizational structure innovation. Among the five factors, technological transition is a necessary condition for AI to empower disruptive innovation in enterprises. There are three types and four paths of AI empowering disruptive innovation in enterprises including“technology-service ecology type”, “technology-scene-structural innovation type” and “technology-cooperation network type”. The results provide decision-making references for enterprises on selecting an AI empowerment path to drive disruptive innovation based on their unique circumstances.

In recent years, the problem of equalization supply of local public services has been increasingly concerned by all sectors of society. The report of the Party's 20th National Congress and the decision of the Third Plenary Session of the 20th Central Committee also stressed the need to "enhance the equalization and accessibility of basic public services". How to better straighten out the fiscal management system among multi-level governments, and give full play to the two positivity of "superior government" and "local government" in the supply of public services is particularly important for ensuring the equalization and accessibility of public services. From the perspective of the fiscal management system, the relevant theoretical literature on the equalization supply of local public services in China was sorted out. It find that, firstly, significant regional and urban-rural differences exist in the supply of local public services in China, with the imbalance in the supply of education and healthcare being particularly prominent. Secondly, factors including the fiscal decentralization system, local governments' promotion incentives and the fiscal expenditure structure are major causes for the imbalance in local public service supply. Thirdly, public policies like increasing public expenditures, enhancing transfer payments, promoting household registration reform and encouraging government service procurement are conducive to improving the supply of local public services. Finally, reform measures of the fiscal management system, such as the division of affairs rights and expenditure responsibilities and the optimized design of inter-governmental fiscal relations, have a remarkable impact on the balance and accessibility of local public service supply.

Improving the resilience and security of China's integrated circuit (IC) industry chain is the basis for ensuring China's economic security and national security in the era of digital intelligence. On the basis of summarizing the new development trend of the global IC industry chain, it was found that the United States exercises "long-arm jurisdiction" over the global IC industry and strengthens its own manufacturing capabilities under the name of security, leading the IC industry into an unprecedented period of turmoil. Coupled with the U. S. "decoupling" and isolate China from its allies. China's IC industry faces unprecedented risks, and the new industrial cycle's downturn phase further intensifies the competitive risks. However, China's acceleration in technological and product breakthroughs in the IC industry has effectively mitigated the impact of external forces, and the resilience and security of China's IC industry have been effectively alleviated by enforcing technological independence and breakthroughs in cutting-edge technologies. In the future, enhancing the resilience and security of China's IC industry chain and building a national competitive advantage not only requires the active capability of the nation to strengthen policy supply, but also the advanced chips breakthroughs and mature chips capacity expansion, long-term strategic deployment, cultivation of "epoch-making products" and the construction of industrial ecology, safe operation under extreme conditions, and construction of the industrial ecosystem are necessary to drive the high-level security and high-quality development of the IC industry.

Ensuring the stabilization and expansion of foreign direct investment is one of the key priorities in current economic efforts. Exploring the impact of trade friction on foreign divestment and understanding the underlying causes is of great significance for stabilizing foreign investment in the new situation. It took China’s counter-tariff measures against the United States during the Sino-US “trade war” as a starting point to examine the effects of trade friction on foreign divestment in China. It further examined how the increased uncertainty of the import supply chain under trade friction affected foreign divestment in the industrial chain correlation. The findings are as follows. Trade friction exacerbates foreign investment withdrawal in China, especially for export-oriented enterprises, enterprises with a high concentration of imports and those not undergoing digital transformation. Trade friction increases uncertainty of the import supply chain, which is a key factor contributing to foreign divestment. The rising uncertainty of the import supply chain also has spillover effects on foreign divestment in the same industry as well as upstream and downstream industries. The research conclusions can provide a new perspective to explain the phenomenon of foreign divestment in China under trade friction, and also provide a policy basis for achieving “stable foreign investment” from the supply chain aspect.