Measuring Well-Being of Migrant Gig Workers: Exampled as Hangzhou City in China

Behav Sci (Basel). 2022 Sep 27;12(10):365. doi: 10.3390/bs12100365.

Abstract

The consistent innovations and applications of information technology drive the vigorous development of the gig economy, and generate gig workers such as food delivery workers and couriers, and make a great contribution to stabilizing employment and increasing income. Gig workers, mostly made up of migrants, and suffer from job and status difficulties. Research on the well-being of migrant gig workers can reveal the practical problems and provide suggestions for narrowing the wealth gap to promote social fairness and justice. Taking Hangzhou city in China as an example, this paper explores the well-being of food delivery workers, couriers, and online car-hailing drivers as representatives of migrant gig workers. Firstly, the relevant data are acquired through the questionnaire. Secondly, the characteristics of this group are analyzed through descriptive analysis, namely: most of them are migrant workers aged between 20 and 39 with low occupation satisfaction due to insufficient social security coverage and limited well-being, despite relatively high income. Based on the analysis of differences in demographic variables and structural equation modeling, the factors affecting the well-being of migrant gig workers are studied, which mainly are occupation satisfaction, social interaction, and social security. The results show that occupation satisfaction is positively affected by family characteristics, social interaction, and social security. In addition, family characteristics and social security positively impact social interaction, but the former has no significant effect on well-being. Finally, this paper enriches the research on the well-being of specific migrant gig workers and gives policy suggestions for enhancing the well-being of migrant gig workers in Hangzhou city from the perspective of optimizing the mechanism, pilot construction, and platform provision.

Keywords: difference analysis of demographic variables; gig economy; migrant; structural equation model; well-being.