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Social Network Influences on Non-Agricultural Employment Quality for Part-Time Peasants: A Case Study of Sichuan Province, China

Author

Listed:
  • Kaijing Xue

    (Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, #9, Block 4, Renminnan Road, Chengdu 610041, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Dingde Xu

    (Sichuan Center for Rural Development Research, College of Management, Sichuan Agricultural University, Chengdu 611130, China)

  • Shaoquan Liu

    (Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, #9, Block 4, Renminnan Road, Chengdu 610041, China)

Abstract

In recent years, the issue of employment quality for workers has received increasing attention from the government and academia. As a social resource, a social network can provide people with social support and help job seekers find better jobs by transmitting the information on job opportunities. However, currently, there are few empirical studies on employment quality from the perspective of social networks. Based on data from 194 samples from 400 households in Sichuan Province in 2015, this paper constructs an employment quality index system from the six dimensions of labor wages, working time, employment stability, employment environment, career development, and social security. In addition, from the perspective of the structural features and the overall characteristics of the social network, OLS (Ordinary Least Squares) and the path analysis model are used to quantitatively explore the mechanisms of action paths of the social network in terms of the non-agricultural employment quality of part-time peasants. The results show that: (1) the social network scale and the relative network of part-time peasants are found to positively affect employment quality. (2) Age, gender, and education level have indirect impacts on the employment quality loop through network heterogeneity and network scale. In addition, network heterogeneity and health status indirectly impact employment quality through a network scale. (3) By synthesizing the direct and indirect impacts, the comprehensive impacts of each factor on employment quality, in decreasing order, are: village–county distance > village terrain > family population > network scale > education level > skill > network heterogeneity > health status > age > gender. The results suggest that we should pay attention to the role of social network resources in improving employment quality, and should implement various measures to expand peasants’ social networks, so as to achieve high-quality employment.

Suggested Citation

  • Kaijing Xue & Dingde Xu & Shaoquan Liu, 2019. "Social Network Influences on Non-Agricultural Employment Quality for Part-Time Peasants: A Case Study of Sichuan Province, China," Sustainability, MDPI, vol. 11(15), pages 1-22, July.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:15:p:4134-:d:253341
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    2. Xin Deng & Miao Zeng & Dingde Xu & Yanbin Qi, 2020. "Does Social Capital Help to Reduce Farmland Abandonment? Evidence from Big Survey Data in Rural China," Land, MDPI, vol. 9(10), pages 1-17, September.
    3. Kaijing Xue & Shili Guo & Yi Liu & Shaoquan Liu & Dingde Xu, 2021. "Social Networks, Trust, and Disaster-Risk Perceptions of Rural Residents in a Multi-Disaster Environment: Evidence from Sichuan, China," IJERPH, MDPI, vol. 18(4), pages 1-25, February.
    4. Kai Huang & Xin Deng & Yi Liu & Zhuolin Yong & Dingde Xu, 2020. "Does off-Farm Migration of Female Laborers Inhibit Land Transfer? Evidence from Sichuan Province, China," Land, MDPI, vol. 9(1), pages 1-14, January.
    5. Wei Liu & Jing Gao & Jie Xu & Cong Li, 2023. "Estimating Livelihood Vulnerability and Its Impact on Adaptation Strategies in the Context of Disaster Avoidance Resettlement in Southern Shaanxi, China," Agriculture, MDPI, vol. 13(8), pages 1-15, July.
    6. Huanxin Yang & Kai Huang & Xin Deng & Dingde Xu, 2021. "Livelihood Capital and Land Transfer of Different Types of Farmers: Evidence from Panel Data in Sichuan Province, China," Land, MDPI, vol. 10(5), pages 1-21, May.

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