Journal of Digital Convergence (디지털융복합연구)

The Society of Digital Policy and Management (한국디지털정책학회)
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Determinants of Wage for Web-based Platform Workers: In perspective of evaluation by previous employers

웹 기반형(Web-based) 플랫폼 노동자의 임금 결정요인: 이전 고용주에 의한 평가의 관점에서

  • Lim, Jisun (Division of Economics and Law, Korea Military Academy)
  • Received : 2022.01.18
  • Accepted : 2022.04.20
  • Published : 2022.04.28
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Abstract

The purpose of this study was to find the wage determinants of web-based platform workers. For this purpose, a total of 3,575 web-based platform workers' information from Freelancer.com, a global platform labor market, in September 2018 were used and whether or not newly available indicators such as evaluations by previous employers had a significant effect on the wage increase of platform workers using OLS and QR methods. As an OLS estimation results, the number of reviews, as well as education and experience, affects the wages of platform workers. However, as a result of the QR estimation, experience rather than education, recommendation rather than a review has a more significant effect on the wage of web-based platform workers as the wage level rises.

본 연구는 웹 기반형(web-based) 플랫폼 노동자의 임금 결정에 관한 연구이다. 이를 위해 2018년 9월 전 세계적 플랫폼 노동시장 중 하나인 Freelancer.com에서 웹 크롤링(web-crawling)한 총 3,575명의 구직자 정보를 사용하였으며, 전통적 노동시장에서 유의하였던 학력, 경력과 더불어 플랫폼 노동시장에서 새롭게 사용 가능해진 이전 고용주에 의한 평가가 플랫폼 노동자의 임금상승에 유의한 영향을 주는지 OLS 및 QR 분석방법을 사용하여 추정하였다. OLS 분석결과 플랫폼 노동자의 임금은 과거 유의하였던 학력, 경력뿐 아니라 이전 고용주에 의한 평가(리뷰 수)에 의해서도 영향을 받는 것으로 나타났다. 다만, QR 분석결과 플랫폼 노동자의 임금수준이 상승함에 따라 교육보다는 경력이 리뷰 수보다는 추천 수가 플랫폼 노동자의 임금상승에 더욱 유의미한 영향을 주는 것으로 나타났다.

Keywords

Acknowledgement

This paper was supported by Hwarang-Dae Research Center at Korea Military Academy in 2021.

References

  1. T. A. Leopold, V. Ratcheva & S. Zahidi (2016). The Future of Jobs: Employment, Skills and Workforce Strategy for the Fourth Industrial Revolution, January 2016, Geneva: World Economic Forum.
  2. S. Zahidi, V. Ratcheva, G. Hingel & S, Brown. (2020). The Future of Jobs Report 2020, October 2020, Geneva: World Economic Forum.
  3. S. Lund, A. Madgavkar, J. Manyika, S. Smit, K. Ellingrud, M. Meaney & O. Robinson. (2021). The Future of Work After COVID-19, Febuary 2021, NewYork: McKinsey Global Institute.
  4. SIA. (2018). The Human Cloud, the Gig Economy & the Transformation of Work. London: Staffing Industry Analysists (SIA).
  5. G. Friedman. (2014). Workers Without Employers: Shadow Corporations and the Rise of the Gig Economy. Review of Keynesian Economics, 2(2), 171-188. https://doi.org/10.4337/roke.2014.02.03
  6. K. S. Choi & S. H. Kim. (2019). Global Gig Economy Status and Implication. International Eonomic Review, 2019(2), 1-22.
  7. V. D. Stefano. (2015). The Rise of the Just-In-Time Workforce: On-demand Work, Crowdwork, and Labor Protection in the Gig-economy. Comparative Labor Law and Policy Journal. 37, 471-503.
  8. J. Berg, M. Furrer, E. Harmon, U. Rani & M. S. Silberman. (2018). Digital Labour Platforms and the Future of Work: Towards Decent Work in the Online World. Geneva: International Labor Organization
  9. J. H. Jung, J. J. Huh, S. I. Nam, S. W. Lee, J. H. Keum, K. S. Choi & G. Y. Park. (2017). A Study of The Future of Work and Labor Market Strategy, March 2017, Sejong: Korea Labor Institute.
  10. J. Fromm & A. Read (2018). Marketing to Gen Z: The Rules for Reaching This Vast-And Very Different-Generation of Influencers. New York: AMACOM.
  11. S. R. Park. (2021.05.13). More Than Half of 'Gen Z' Around the World Say "They Want to Start a Business Rather than Get a Job". Chosun-biz, https://biz.chosun.com/international/international_general/2021/05/13/4WS2GJCCOBAHJDDVLYWLM5T4PI/
  12. M. S. Kim. (2019.07.19). 74% of Millennials and Generation Z Agree with N-jobs with Various Jobs, Not Just One Job. Recruit Times. http://www.recruittimes.co.kr/news/articleView.html?idxno=85328
  13. J. J. Kim, W. J. Shin & Y. W. Kim. (2021). Status and Characteristics of Digital Platform Labor II: Web-based, Regional-based scale and condition. Korea Labor and Social Research Institute Issue paper, 2021(5), 1-33.
  14. Korea Bureau of Statistics. (2021.10.03.) Size and Proportion of Wage Earners by Gender/Work type. Economic Activity Survey. https://kosis.kr/statHtml/statHtml.do?orgId=101&tblId=DT_1DE7106S&conn_path=I3
  15. G. S. Becker. (1962). Investment in Human Capital: A Theoretical Analysis. Journal of Political Economy, 70(5), 9-49. https://doi.org/10.1086/258724
  16. T. W. Schultz. (1962). Reflections on Investment in Man. Journal of Political Economy, 70(5), 1-8. https://doi.org/10.1086/258723
  17. J. Mincer. (1974). Schooling, Experience, and Earnings. New York: National Bureau of Economic Research (NBER).
  18. K. J. Arrow. (1971). Some Models of Racial Discrimination in the Labor Market. Santa Monica: RAND Corporation.
  19. E. S. Phelps. (1972). The Statistical Theory of Racism and Sexism. The American Economic Review, 62(4), 659-661.
  20. P. B. Doeringer & M. J. Piore. (1971). Internal labor markets and manpower analysis: with a new introduction. New York: Routledge.
  21. R. Hodson & R. L. Kaufman. (1982). Economic Dualism: A Critical Review. American Sociological Review, 727-739.
  22. S. K. Lee. (2014). Definition and Conditions of a Two-sided Market. Information and Communication Policy Research, 21(4), 73-105.
  23. U.S. Bureau of Labor Statistics. (2018). Electronically mediated work: new questions in the Contingent Worker Supplement. Monthly Labor Review, 2018(9), 1-32.
  24. F. Bogliacino, C. Codagnone, V. Cirillo & D. Guarascio. (2019). Quantity and Quality of Work in the Platform Economy. Handbook of Labor, Human Resources and Population Economics.
  25. U. Rani, R. Kumar Dhir, M. Furrer, N. Gobel, A. Moraiti. & S. Cooney. (2021). World Employment and Social Outlook: The Role of Digital Labour Platforms in Transforming The World of Work. Geneva: International Labour Organisation.
  26. D. Farrell, F. Greig. & A. Hamoudi. (2018). The Online Platform Economy in 2018: Drivers, Workers, Sellers, and Lessors. New York: JPMorgan Chase Institute.
  27. G. E. Bolton, E. Katok. & A. Ockenfels. (2004). How Effective Are Electronic Reputation Mechanisms? An Experimental Investigation. Management Science, 50(11), 1587-1602. https://doi.org/10.1287/mnsc.1030.0199
  28. M. Kokkodis, & P. G. Ipeirotis. (2016). Reputation transferability in online labor markets. Management Science, 62(6), 1687-1706. https://doi.org/10.1287/mnsc.2015.2217
  29. J. V. Hall. & A. B. Krueger. (2018). An Analysis of The Labor Market for Uber's Driver-Partners in The United States. Industrial and Labor Relations Review, 71(3), 705-732. https://doi.org/10.1177/0019793917717222
  30. S. K. Park. & B. K. Lee. (2018). A Qualitative Study of Gig Economy Resource Providers' Experiences and Perceptions of Future Jobs. Journal of The Internet Information Society, 19(1), 141-154.
  31. J. H. Lee. (2021). Determinants of Shortening Job Hunting Period in Platform Labor Market: Analysis by Using Web Crawling and Survival Model. Journal of Digital Convergence. 19(5), 1-13. https://doi.org/10.14400/JDC.2021.19.5.001