A Study on the Socio-Demographic Patterns of Platform Workers and Related Factors in South Korea

Background and Purpose: Earning income through an online platform has become a global phoenomenon. In South Korea, a significant number of people are flowing into platform labor instead of traditional labor. Platform labor is usually easy for anyone to engage in. So, many platform workers are composed of low education, women with a career break and the elderly who have many difficulties in entering the traditional labor market. However, recently, there are a growing tendency to participate in platform labor among young and highly educated people in South Korea. This phenomenon shows that there are various reasons for engaging in platform labor, thus, we can expect that platform worker groups may include not only those belonging to the peripheral labor market but also exceptional and various people. Thus, this study aims to (1) identify various socio-demographic patterns of platform workers and (2) investigate how identified socio-demographic patterns are associated with work-related characteristics and psycho-social characteristics among platform workers in South Korea.

Methods: Data were collected in June 2022 through online surveys of 687 Korean platform workers. We conducted latent class analysis (LCA) to identify socio-demographic patterns of platform workers, including gender, age, marital status, education level, monthly income, main/side job status, and job type. After identifying latent classes, we examined the extent to which work-related characteristics and psychosocial characteristics were related to the latent classes. For this purpose, we performed chi-square tests and one-way ANOVA analyses.

Results: LCA identified four differential classes of platform workers; 1) Youth·male·main job (22.7%), 2) High education·female·side job (24.2%), 3) Low education·male·main job (21.7%), and 4) High education·male·main job (31.4%). Chi-square tests and one-way ANOVA analyses showed that there were significant differences in work-related and psycho-social characteristics across platform worker classes. The high education·male·main job class had high incomes compared with other classes. But in this class the satisfaction with work environment safety, work autonomy and authority was lower, and time pressures was higher. The youth·male·main job class reported higher inner concerns, financial concerns, and health hassles and lower work-life balance. Compared with other classes, the high education·male·main job class and the youth·male·main job class were more likely to be depressed(51.9%, 46.2%) and anxious(39.4%, 28.2%). The high education·female·side job class reported higher job pressure and subjective reward inadequacy, but income satisfaction was not low. The low education·male·main job class showed a lower amount of work hours, time slots, and income satisfaction than other classes. Bonding capital was found to be the lowest in the youth·male·main job class, and bridging capital was found to be lower in the high education·female·side job class and the low education·male·main job class.

Conclusions and Implications: This study indicates the importance of understanding the different subgroups of platform workers. Worker’s reasons for engaging in platform labor, work-related characteristics, and psycho-social characteristics can vary. This study will provide meaningful implications for developing effective interventions to improve working conditions and mental health, and social capital for platform workers.