Marxist political economy holds that technological change can promote employment from multiple dimensions, such as increasing the total employment volume, improving labor skills, and transforming the relations of production. Amid the new wave of scientific and technological revolution, artificial intelligence (AI) has become a crucial engine driving high-quality and full employment in China. Following the development path of "technology - industry - occupation - standard", AI integrates the technical support system, intelligent industrial clusters, career development carriers, and risk prevention mechanisms into an organic whole. It systematically empowers China's employment service system and lays a solid foundation for meeting the people's needs for a better life. However, this process still faces many challenges. These include the employment displacement effect of AI, the deepening of algorithmic control caused by "digital Taylorism", the risk of collusion between capital and technology due to ambiguous data ownership, and structural employment contradictions resulting from the lag in education transformation.To address these issues, we must adhere to the "two unswervinglys" (to unswervingly consolidate and develop the public sector of the economy, and to unswervingly encourage, support and guide the development of the non-public sector of the economy), standardize and guide the healthy development of capital, continue to strengthen the AI industry, protect the ownership of digital production factors, tap into the stock of human capital and improve its quality, build a high-quality employment service system, and promote the sustained release of AI-driven employment dividends.

In crowdsourcing contests, a big challenge is to screen good ideas from a large number of alternative ideas. To address this challenge, this study develops a relation-based intelligent method for idea screening (Rela-IdeaS). This method adopts the strategies of retaining ideas with high quality and eliminating ideas with low quality based on idea novelty and feasibility. Specifically, this study employed the latent dirichlet allocation method to classify the ideas into various themes based on their novelty. Furthermore, the Jaccard coefficient method was used to construct semantic networks of each idea theme and its included ideas. With the help of cumulative distribution functions, these semantic networks were transformed into cumulative distributions Moreover, we used Kolmogorov-Smirnov statistics to measure the distance between semantic networks of ideas and idea themes. Finally, the ideas in each theme were ranked for further screening based on their values of feasibility (i.e., network distance). We applied our method to screen ideas from three crowdsourcing contests. The results indicated that using the proposed method to screen the ideas with low quality has a good precision rate. For screening the ideas with high quality, the method has a good recall rate. Additionally, compared to the commonly used methods, i.e., methods based on idea text length, crowd voting, and the SBERT model, our method performed better in precision and recall rates.

Based on panel data from 30 provinces (autonomous regions, municipalities) in China between 2013 and 2022, this paper constructs an evaluation index system for the digital business environment and employs fixed-effects models and mediation effect models to examine and analyze the mechanism through which the digital business environment facilitates industrial structure upgrading. The research finds that the development of the digital business environment promotes both the overall industrial structure and internal transformation and upgrading. This effect is primarily realized through optimizing resource allocation, enhancing innovation capacity, and fostering mass entrepreneurship. The impact of the digital business environment on industrial structure upgrading exhibits significant heterogeneity due to differences in locational conditions, economic development levels, and internal dimensions of the digital business environment. In the future, government departments should increase investment in and construction of digital infrastructure to fully unleash the potential of the digital business environment in promoting industrial structure upgrading. Additionally, they should continuously adjust the focus of industrial structure upgrading based on differences in locational conditions and economic development levels, thereby providing solid support for high-quality economic development.

With the expansion of agricultural insurance coverage, the drawbacks of traditional manual loss assessment methods in agricultural insurance have become increasingly apparent. In this context, the low-altitude economy, leveraging its advantages of standardization and efficiency in loss assessment operations, provides strong support for the high-quality development of agricultural insurance and the process of agricultural modernization. This paper systematically reviews and analyzes the current standards related to the low-altitude economy and agricultural insurance loss assessment, and comprehensively explores the technical adaptation pathways and application strategies of the low-altitude economy in this field, using cases such as floods in Yunnan and snow disasters in Nanjing. Traditional manual loss assessment methods in agricultural insurance suffer from issues such as low efficiency, poor accuracy, and high costs. Although the low-altitude economy can effectively alleviate these problems, it still faces practical challenges in application, including limited drone endurance, insufficient data processing capabilities, cumbersome airspace application procedures, and poor industrial integration. Accordingly, a standardized system for agricultural insurance loss assessment centered on “technology-operational processes-data-security” should be established, with efforts focused on strengthening technological innovation, optimizing policy regulation, and promoting industrial collaboration. This will systematically enhance the modernization level and service efficiency of agricultural insurance loss assessment.

The integration of low-altitude economy and smart logistics is driving the modern logistics industry towards intelligence, efficiency and green development. Drones and intelligent delivery systems break through traditional transportation limitations and have obvious advantages in urban and remote area deliveries. Big data and artificial intelligence can optimize logistics routes through real-time data analysis, improving system response speed and accuracy. The integration of low-altitude economy and smart logistics has given rise to new business models such as on-demand and instant delivery, promoting the personalization, flexibility and diversification of the logistics industry ecosystem. Although there are still challenges in technological breakthroughs, policy and regulation adaptation, and data security protection, which may restrict the development of related fields, these issues are gradually being resolved through continuous technological innovation and collaborative efforts among multiple stakeholders within the industry. With technological breakthroughs, industrial collaboration and international cooperation, the integration of low-altitude economy and smart logistics will continue to drive the sustainable development of the global logistics industry, enhancing the efficiency and flexibility of the global logistics network.

This paper uses the data of the Shanghai and Shenzhen A-share affiliated group from 2004 to 2022 to empirically examine the impact of the two types of benefit flows formed by related-party transactions, namely “tunneling” and “efficiency promotion”, on the ICM allocation efficiency of affiliated groups and their underlying mechanisms. The research results show that related-party transactions, as a neutral behavior, have a “double-edged sword” effect on the ICM allocation efficiency of affiliated groups. The benefit inflow type of related-party transactions supports the efficiency promotion view and improves the ICM allocation efficiency; the benefit outflow type of related-party transactions supports the tunneling view and reduces the ICM allocation efficiency. Further research finds that the impact of related-party transactions of affiliated groups on ICM allocation efficiency and their underlying mechanisms vary due to differences in corporate governance levels and business correlations among different divisions. Meanwhile, profitability and cash holding levels have an impact on the relationship between related-party transactions of affiliated groups and ICM allocation efficiency. In the future, In the future, the government should strengthen information disclosure by regulatory authorities and enhance external oversight. Business groups should prioritize corporate governance standards, which play a critical role in influencing related-party transactions, thereby steering the economic outcomes of such transactions toward an efficiency-promoting perspective.

Facing the unprecedented changes in a century, enhancing resilience is a key capability that enterprises need to cope with crises and grow against the odds. Based on the data of A-share listed companies in Shanghai and Shenzhen from 2012 to 2022, this article analyzes the impact and mechanism of institutional investors' on-site research on enterprise resilience. The research shows that on-site research by institutional investors can significantly enhance enterprise resilience, which can be achieved through the information effect, that is, alleviating the financing constraints of enterprises, and the governance effect, that is, increasing the innovation investment of enterprises. Media attention and the state-owned nature of enterprises both play a negative moderating role in the process of institutional investors' on-site research promoting the enhancement of enterprise resilience. Heterogeneity analysis reveals that the promotion effect of on-site research by fund-type investment institutions on the enhancement of enterprise resilience is the greatest. On-site research for enterprises in the growth and decline stages can promote the enhancement of enterprise resilience, while on-site research for enterprises in the mature stage may weaken enterprise resilience. In the future, a regular on-site research working mechanism should be promoted to strengthen information communication and sharing between enterprises and investors, so as to continuously enhance enterprise resilience.