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

Kaijing Xue (), Dingde Xu () and Shaoquan Liu ()
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Kaijing Xue: Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, #9, Block 4, Renminnan Road, Chengdu 610041, 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

Sustainability, 2019, vol. 11, issue 15, 1-22

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.

Keywords: quality of working life; part-time farmers; network resource; analysis of paths (search for similar items in EconPapers)
JEL-codes: Q Q0 Q2 Q3 Q5 Q56 O13 (search for similar items in EconPapers)
Date: 2019
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