Abstract

Change in Jobs for Women Attributed to Technological Development and Counter-streategies (II): Focusing on Platform-based Jobs
Type Basic Period 2019
Manager Eunjin Oh Date 2020-03-03
Fiie 3. Change in Jobs for WOmen Attributed to Technological Dvelopment and Counter Strategies.pdf ( 753.7 KB )

Abstract

 

Change in jobs for women attributed to technological development and counter-strategies() : focusing on Platform-based Jobs

 

Eunjin Oh

Sunmi Shin

Miyoung Gu

Soyoung Kwon

Hyeonjong Kil

 

This study is to forecast what impact the spread of digital platform labor, caused by technological development, will influence women’s labor and to suggest policy tasks on the perspective of gender mainstreaming.

 

To this end, this investigation examines overseas research related to digital platform labor in terms of gender dynamics and conducts statistical analysis to estimate the scale of the type of labor. In addition, it carries out questionnaire survey on, focus group interview and in-depth one with digital platform companies and their employees.

 

The major findings and policy tasks are as follows. Those performing digital platform jobs, who formerly felt a sense of hired as well as self-employed, which is partly the reason why they were sometimes perceived as workers in a gray area, are likely to see such jobs will increase in the coming days. Moreover, factual survey uncovers that the platform jobs are not completely new which came in the wake of technological development but from the restructuring of past ways of working, as evidenced by that fact that an overwhelming majority of such employees were found engaged in similar jobs in the off-line labor market. Over the years, more and more jobs are being specialized and outsourced, which can make the labor market polarize as those jobs will be simple and menial. Meanwhile, digital platform businesses are acting on market expansion strategy, taking advantage of diverse consumerentered technologies. Capitalizing on continued investment, they are very likely to further grow in the future.

 

This study analyzes and reveals the following characteristics of the digital platform labor market. Unfair contractual practices found in the above-mentioned gray area have been gradually addressed, and, thanks to enhanced levels of autonomy about where and what time to work, female workers have enjoyed greater labor flexibility. Moreover, easing information asymmetry led to more job opportunities, thus bringing in higher chances of getting primary, or sideline jobs. But those upsides came with some downsides. Digital platform laborers have to pay burdensome service fees. In addition, they raise to themselves a question of whether they are self-employed or by someone else, which is a criterion that determines whether or not they are entitled for social safety net. Based on these findings, the study uncovers a need for policy measures that can address the problems.

 

This investigation suggests policy missions as below. Autonomous regulation should be provided for digital platform companies to properly manage labor-related issues. For that to happen, diversified supportive systems should also be prepared. Furthermore, a social protection system should be drafted for those working on such platform labor, and both maternal and paternal leave need to be expanded. Moreover, the study proposes that an organization that fully considers and represents jobs and tasks and a supportive system that works for digital platform laborers by type be provided. It suggests other actions as well: the adoption of periodical survey, standard contract, legal advisory, all of which are for promoting fair trades; the appreciation of proper bid prices that can narrow the gender gap in digital platform labor; the strengthening of women’s capability that can tackle the problem of some females not eligible for job training opportunities; the ways of those working on the digital platform building on their career. Lastly, the study proposes that relevant database should be established for specific time-series analyses to identify the scale of the digital platform labor market.