What Factors Are Associated with Job Insecurity Among Platform Workers in South Korea?

Background and Purpose

With the growth of gig work through online platforms, the number of Korean platform workers (PW) is rapidly increasing and is estimated to be 2,920,000 persons in 2022, about 52% of them are in the delivery and transport sectors. They are known to be in a highly precarious work environment (WE), where they are expected to be on-call at all times or respond to digital communication tools even outside of their regular working hours, which may lead to Job insecurity (JIS) and reduce psychological well-being.

JIS is a significant job stressor negatively associated with employees’ mental health outcomes, in which precarious employment is placed with threatened loss. However, there have been few studies to examine JIS and related factors of PW in South Korea. Accordingly, this study aimed to identify various correlates (demographic, psycho-social, WE factors) of PW that may affect JIS. This study will provide meaningful implications for the future psychological well-being challenges as well as JIS posed by platform work in a post-pandemic economy.

Methods

Data and samples:

Using purposive sampling, we conducted an online survey on 687 PW nationwide in 2022. 550 PW engaged in the pickup and delivery of motorcycles, and taxi transportation were included in the final analysis. The study was approved by the Institutional Review Board of OOO University.

Measures:

The dependent variable is JIS, which was measured using a short-form scale (De Witte, 1999) with four Likert items. A three-factor model was used to predict JIS, which included demographic characteristics (DEMC), psych-social factors (PSYF), and WE factors. First, DEMC, such as age, gender, education, marital status, and income were used. PSYF such as personal strength of their resilience containing self-perception and future perception, anxiety, and powerlessness were considered. Lastly, WE factors included job satisfaction and job pressure. and perceived legitimacy of wage levels (PLWL). We used the forward Step-wise selection provided by SPSS 28, performing iterative procedures to select the best subset of predictors for each step, terminating at the 8th step when there were no more predictors that changed favorably from the previous one.

Results

The best predictor was job satisfaction (b = -0.13, p < .001) and then job pressure (b = 0.16, p < .001) in the WE factor. The next-best predictor was powerlessness (b = 0.11, p < .001), anxiety (b= -0.09, p < .01), and personal strengths (b = -0.05, p < .05) in that order in the PSYF. Next, gender (female=0) (b = -0.51, p < .05), education level (b =0.09, p < .05) of DEMC were selected. Lastly, the PLWL of the WE factor was included (b = -0.26, p < .05).

Conclusion and Implications

It has been found that JIS was much more affected by the WE than by PSYF including personal coping resources or DEMC. Policies should focus on improving the WE to increase job satisfaction, reduce job pressure, and reduce feelings of powerlessness and anxiety. Also, various job types should be developed to match workers' education levels and skills.