Based on the China Migrants Dynamic Survey (CMDS) data from 2018 and the data from 58 large- and medium-sized cities in China, in this paper a hierarchical linear model was used to investigate the impact of demographic characteristics, social participation, and economic and social development on the perceived social integration of new urban immigrants at the individual and urban levels. The results revealed the following: (1) social participation, gender, age, education, health status, flow time and housing type of new urban immigrants had a significant positive impact on their perceived social integration, while income showed a U-shaped relationship with the sense of urban social integration; (2) macro-urban characteristics regulated the correlation between micro-individual factors and perceived social integration; (3) the significant advantages of new urban immigrants with higher education and more social participation in the process of integration into urban society were more obvious in cities with higher levels of economic development or public services. These findings enriched relevant research on the factors influencing the social integration of new urban immigrants and provided valuable insight with which the government could use to improve urban construction and promote the equalization of basic public services.

The development of the digital economy has alternative and complementary effects on employment in the agricultural labor force. While replacing a large part of the agricultural labor force, digital agricultural technology is also expected to create new jobs and multiply the economic development effect. Finally, it will have a large number of positive spillover effects on rural development. To better understand the effects and relationships of digital agriculture on agricultural labor employment in this process, we gathered microdata from 1098 agricultural laborers in 122 counties (cities and districts) of 16 cities in Shandong Province, China. Compared with previous research, the advantage of our study is that structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) are jointly applied to assess the effects of digital agriculture on agricultural labor force employment and the combinatorial path of inter-effect relationships. The analysis results demonstrate that the effects of digital agriculture on agricultural labor force employment mainly include substitution, complementary, flywheel, agglomeration, structural, synergistic, and spillover effects. Through substitution and complementing effects in a chain reaction, which have effects through intermediate links, the first six effects can lead to spillover effects. We determine two modes with a total of eight configurations that can trigger the spillover effect of digital agriculture on agricultural labor force employment. Therefore, it is necessary to choose an effective combination of paths to improve the utilization rate of agricultural resources and promote the diffusion of improved agricultural technologies. If the positive effects of digital agriculture on agricultural labor force employment are reasonably exerted, the development of sustainable agriculture could be accelerated. This would promote the overall development of the agricultural labor force and lead to the revitalization of rural areas and the integration of urban and rural areas.

No abstract

No abstract

Research objective: To use a curve to represent the optimal development path of the tertiary industrial structure. Research methods: Based on the triangular midline, the change path of the three industrial structure was studied, and the development path was optimized clockwise and counterclockwise. The results show that the change path of the tertiary industrial structure in 16 cities in Yunnan Province is as follows: the cities with clockwise optimization development account for 43.75%, and the cities with counterclockwise optimization development account for 50%; The change path of the tertiary industrial structure in 129 counties and urban areas of Yunnan Province is as follows: clockwise optimized development of 41.09% of counties and urban areas, counterclockwise optimized development of 34.88% of counties and urban areas; There are great differences in the efficiency of the three industrial structure changes. Research innovation: The triangle center line is used to study the change path of the three industrial structure, and the clockwise and counterclockwise optimization development path of the industrial structure is proposed. Research value: Study regional industrial structure from multiple perspectives.