Gender, Work, and Digital Labor Platforms in Asia: A Systematic Review
DOI:
https://doi.org/10.64391/ijssat.v1i1.005Keywords:
digital labor platforms, gender inequality, occupational segregation, algorithmic managementAbstract
This systematic review investigates the gendered dynamics of work on digital labor platforms across Asia, synthesizing findings from interdisciplinary literature to examine patterns of occupational segregation, wage disparities, and algorithmic bias. Drawing on studies from diverse contexts, the review reveals that digital platforms, while offering flexible employment opportunities, often reproduce and reinforce traditional gender inequalities. Women are disproportionately concentrated in lower-paid, lower-status roles, both across and within occupational categories, and face systemic wage gaps influenced by social norms, limited access to digital infrastructure, and algorithmically mediated discrimination. Institutional factors such as weak labor protections and fragmented regulatory environments further exacerbate these disparities. The review highlights that technological solutions alone are insufficient to ensure equity; instead, a combination of inclusive platform design, stronger legal frameworks, and policy interventions targeting structural inequalities is essential. The paper concludes by emphasizing the need for intersectional, evidence-based strategies to promote fair and equitable participation in the growing platform economy in Asia.
Downloads
References
Azad, P., & Hari, K. (2024). Wage inequality across regions in India: Exploring the role of education and skills. Journal of Public Affairs. https://doi.org/10.1002/pa.2919 DOI: https://doi.org/10.1002/pa.2919
Bigman, Y., Wilson, D., Arnestad, M., Waytz, A., & Gray, K. (2022). Algorithmic discrimination causes less moral outrage than human discrimination.. Journal of experimental psychology. General. https://doi.org/10.1037/xge0001250 DOI: https://doi.org/10.1037/xge0001250
Borrowman, M., & Klasen, S. (2020). Drivers of Gendered Sectoral and Occupational Segregation in Developing Countries. Feminist Economics, 26, 62 - 94. https://doi.org/10.1080/13545701.2019.1649708 DOI: https://doi.org/10.1080/13545701.2019.1649708
Buchholz, M., & Storper, M. (2025). Black and Latinx workers reap lower rewards than White workers from years spent working in big cities.. Proceedings of the National Academy of Sciences of the United States of America, 122 6, e2409935122. https://doi.org/10.1073/pnas.2409935122 DOI: https://doi.org/10.1073/pnas.2409935122
Campero, S. (2020). Hiring and Intra-occupational Gender Segregation in Software Engineering. American Sociological Review, 86, 60 - 92. https://doi.org/10.1177/0003122420971805 DOI: https://doi.org/10.1177/0003122420971805
Campos-Soria, J., Marchante-Mera, A., & Ropero-García, M. (2011). Patterns of occupational segregation by gender in the hospitality industry. International Journal of Hospitality Management, 30, 91-102. https://doi.org/10.1016/J.IJHM.2010.07.001 DOI: https://doi.org/10.1016/j.ijhm.2010.07.001
Derenoncourt, E., & Montialoux, C. (2020). Minimum Wages and Racial Inequality*. Quarterly Journal of Economics. https://doi.org/10.1093/QJE/QJAA031 DOI: https://doi.org/10.1093/qje/qjaa031
Dolado, J., Felgueroso, F., & Jimeno, J. (2003). WHERE DO WOMEN WORK? : ANALYSING PATTERNS IN OCCUPATIONAL SEGREGATION BY GENDER (*). Annals of economics and statistics, 293-315. https://doi.org/10.2307/20079056 DOI: https://doi.org/10.2307/20079056
Fischbacher, U., Kübler, D., & Stüber, R. (2023). Betting on Diversity - Occupational Segregation and Gender Stereotypes. Manag. Sci., 70, 5502-5516. https://doi.org/10.2139/ssrn.4324210 DOI: https://doi.org/10.1287/mnsc.2023.4943
Froehlich, L., Olsson, M., Dorrough, A., & Martiny, S. (2020). Gender at Work Across Nations: Men and Women Working in Male‐Dominated and Female‐Dominated Occupations are Differentially Associated with Agency and Communion. Journal of Social Issues. https://doi.org/10.1111/josi.12390 DOI: https://doi.org/10.1111/josi.12390
Ghasemaghaei, M., & Kordzadeh, N. (2024). Understanding how algorithmic injustice leads to making discriminatory decisions: An obedience to authority perspective. Inf. Manag., 61, 103921. https://doi.org/10.1016/j.im.2024.103921 DOI: https://doi.org/10.1016/j.im.2024.103921
Han, J., & Hermansen, A. (2024). Wage Disparities across Immigrant Generations: Education, Segregation, or Unequal Pay?. Industrial & Labor Relations Review, 77, 598 - 625. https://doi.org/10.1177/00197939241261688 DOI: https://doi.org/10.1177/00197939241261688
Hsiung, C. (2022). Gender-Typed Skill Co-Occurrence and Occupational Sex Segregation: The Case of Professional Occupations in the United States, 2011–2015. Gender & Society, 36, 469 - 497. https://doi.org/10.1177/08912432221102148 DOI: https://doi.org/10.1177/08912432221102148
Huang, Y., Chen, Q., Luo, L., & Lin, Z. (2024). Algorithmic Discrimination and Market Competition: Exploring the Ethical and Legal Issues of Algorithm Management by Internet Companies. Philosophy and Social Science. https://doi.org/10.62381/p243504 DOI: https://doi.org/10.62381/P243504
Indrayani, S., & Muzan, A. (2025). Kesenjangan Upah dan Keadilan Sosial terhadap Sistem Pengupahan di Indonesia. Al-Muzdahir : Jurnal Ekonomi Syariah. https://doi.org/10.55352/ekis.v7i1.1505 DOI: https://doi.org/10.55352/ekis.v7i1.1505
Javed, M., Jadoon, A., Malik, A., Sarwar, A., Ahmed, M., & Liaqat, S. (2022). Gender wage disparity and economic prosperity in Pakistan. Cogent Economics & Finance, 10. https://doi.org/10.1080/23322039.2022.2067021 DOI: https://doi.org/10.1080/23322039.2022.2067021
Juhn, C., Murphy, K., & Pierce, B. (1993). Wage Inequality and the Rise in Returns to Skill. Journal of Political Economy, 101, 410 - 442. https://doi.org/10.1086/261881 DOI: https://doi.org/10.1086/261881
Kelly-Lyth, A. (2023). Algorithmic discrimination at work. European Labour Law Journal, 14, 152 - 171. https://doi.org/10.1177/20319525231167300 DOI: https://doi.org/10.1177/20319525231167300
Köchling, A., & Wehner, M. (2020). Discriminated by an algorithm: a systematic review of discrimination and fairness by algorithmic decision-making in the context of HR recruitment and HR development. Business Research. https://doi.org/10.1007/s40685-020-00134-w DOI: https://doi.org/10.1007/s40685-020-00134-w
Martin-Caughey, A. (2021). What’s in an Occupation? Investigating Within-Occupation Variation and Gender Segregation Using Job Titles and Task Descriptions. American Sociological Review, 86, 960 - 999. https://doi.org/10.1177/00031224211042053 DOI: https://doi.org/10.1177/00031224211042053
Pan, J. (2015). Gender Segregation in Occupations: The Role of Tipping and Social Interactions. Journal of Labor Economics, 33, 365 - 408. https://doi.org/10.1086/678518 DOI: https://doi.org/10.1086/678518
Pithale, R. (2025). Bridging the Wage Gap: The Role of Minimum Wages in Reducing Income Inequality in India. International Journal For Multidisciplinary Research. https://doi.org/10.36948/ijfmr.2025.v07i01.37559 DOI: https://doi.org/10.36948/ijfmr.2025.v07i01.37559
Polachek, S. (1987). Occupational segregation and the gender wage gap. Population Research and Policy Review, 6, 47-67. https://doi.org/10.1007/BF00124802 DOI: https://doi.org/10.1007/BF00124802
Wallerstein, M. (1999). Wage-Setting Institutions and Pay Inequality in Advanced Industrial Societies. American Journal of Political Science, 43, 649. https://doi.org/10.2307/2991830 DOI: https://doi.org/10.2307/2991830
Wang, X., Wu, Y., Ji, X., & Fu, H. (2024). Algorithmic discrimination: examining its types and regulatory measures with emphasis on US legal practices. Frontiers in Artificial Intelligence, 7. https://doi.org/10.3389/frai.2024.1320277 DOI: https://doi.org/10.3389/frai.2024.1320277
Wójcik, M. (2022). Algorithmic Discrimination in Health Care. Health and Human Rights, 24, 93 - 103.
Wójcik, M. (2024). Algorithmic discrimination in the era of artificial intelligence: challenges of sustainable human resource management. Edukacja Ekonomistów i Menedżerów. https://doi.org/10.33119/eeim.2024.69.6 DOI: https://doi.org/10.33119/EEIM.2024.69.6
Žliobaitė, I. (2017). Measuring discrimination in algorithmic decision making. Data Mining and Knowledge Discovery, 31, 1060 - 1089. https://doi.org/10.1007/s10618-017-0506-1 DOI: https://doi.org/10.1007/s10618-017-0506-1
Downloads
Published
Versions
- 2025-09-02 (2)
- 2025-05-31 (1)
Issue
Section
License
Copyright (c) 2025 The Author(s). Published by the Colorado Social Science Research Academy, Denver, Colorado, USA.

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

