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Published in last 1 year |  In last 2 years |  In last 3 years |  All Please wait a minute... For Selected: Download Citations EndNote Ris BibTeX Toggle Thumbnails Select The Impact of Digital Literacy on the Employment Quality of Rural Female Labor Force CHEN Li, WENG Zhen-lin Journal of Jiangxi University of Finance and Economics    2024, 0 (4): 87-100.   Abstract （25）            Knowledge map    Save By making use of the data of China Household Tracking Survey (CFPS) database, this paper studies the influence of digital literacy on the employment quality of rural female labor force. The results show that digital literacy has a significant effect on the improvement of the employment quality of rural female labor force, and has a greater impact on the subjective employment quality. On the one hand, digital literacy can promote the objective employment quality of rural female labor force through expanding the information channels; on the other hand, digital literacy can weaken the subjective employment quality of rural female labor force through reducing the relative income evaluation. The heterogeneity analysis shows that digital literacy has a more significant effect on the objective employment quality of rural female labor groups with lower per capita household net income, while it has a significant effect on the subjective employment quality of high-income groups. The positive influence of digital literacy on the objective employment quality of rural female labor groups is mainly concentrated in the age groups between 16 and 45 years old, and the influence on the objective and subjective employment quality of the groups with lower and middle education is more obvious. Each dimension of digital literacy has a different impact on employment quality. Therefore, in the future, the government should continue to increase the construction of digital infrastructure, cultivate the digital literacy of rural women, improve the protection of employment rights and interests, and promote the improvement of employment quality. Reference | Related Articles | Metrics | Comments（0） Select Occupational Location and Employment Quality: Micro Evidence from Migrant Workers’ Voting with Their Feet LIU Xiao-yu, ZHANG Jin-hua, SHEN Ya-fang Journal of Jiangxi University of Finance and Economics    2024, 0 (4): 101-114.   Abstract （16）            Knowledge map    Save The high-quality and full employment of migrant workers is a key link in promoting the integrated development of urban and rural areas, promoting the citizenship of migrant workers, and achieving common prosperity. Based on the Rosen-Roback spatial equilibrium model, this paper demonstrates the impact of occupational location on the employment quality of migrant workers and its internal mechanism from the perspective of urban scale by using the data of China Migrants Dynamic Survey. The results show that, under the vote with feet, the occupational location of migrant workers has a significant effect on high-quality employment, which is expressed in the four aspects: wage income, labor burden, occupational level and employment security. Through the knowledge spillover effect, the labor pool effect and the social network effect, occupational location can deepen the accumulation of human capital, improve the efficiency of job matching, and expand the breadth and depth of social capital, then improving the employment quality of migrant workers. This effect of employment quality is characterized by significant heterogeneity of groups, and the interrupt effect generated from frequent urban mobility changes in occupational location is not conducive to high-quality employment of migrant workers. Therefore, it is necessary to accelerate the development of small and medium-sized cities, improve public employment services, build a unified labour market, promote the construction of new urbanization, pay attention to disadvantaged groups of rural migrant workers, optimize labour relations and labour protection, ensure employment and livelihoods, and help migrant workers to achieve high-quality employment. Reference | Related Articles | Metrics | Comments（0）