Skill-Biased Technical Change, Again? Online Gig Platforms and Local Employment
Xue Guo, Zhi Cheng, Paul A. Pavlou · Information Systems Research · 13 Nov 2024
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Where this sits in the debate
- Will AI destroy more jobs than it creates? · its finding: it depends (why studies differ)
- Will AI widen inequality?
Direction of the finding as read from the abstract by an AI model (AI-written).
Abstract
This study explores the impact of online gig platforms like TaskRabbit on the employment of incumbent service workers, focusing on the housekeeping sector. It highlights how TaskRabbit’s entry correlates with a decrease in middle-skilled roles such as supervisors due to automation, whereas low-skilled jobs like janitors remain stable because of their manual nature. Notably, many middle-skilled workers transition to self-employment within the sector instead of facing layoffs. Amidst competing narratives about the gig economy’s influence on labor markets, this research offers critical insights into how gig platforms redistribute the workforce and create new employment opportunities, suggesting significant implications for policymakers and practitioners. Policymakers should recognize the shift from traditional roles to self-employment facilitated by these platforms, which enhances local entrepreneurship. Meanwhile, it is crucial for them to ensure fair working conditions, wages, and benefits. Practitioners can see that gig platforms not only improve operational efficiency but also enable middle-skilled workers to launch their own businesses, indicating a potential strategy for new platforms looking to increase their service offerings and client base. Traditional companies, in response, need to adapt their job designs, incentive structures, and company culture to align with the changing needs for flexibility and autonomy in the gig economy.
About this publication
Leading field journal. A leading journal in economics or a neighbouring field (on the Tinbergen Institute’s A list or near the top of the RePEc ranking), or a top-rated computer-science venue.
Placed by: Leading field journal. How sources are ranked.
- Published
- 2024 (24 months ago)
- Citations
- 4 (OpenAlex)
Citations in context
4 citations — 9th percentile among the 23 indexed papers from 2024 in this collection. Citation counts favor older papers; this compares only same-year papers here, not the whole literature.
□ added to this collection in 2026.
author affiliation matches seed institutions london school of economics, london school of economics and political science — part of why this paper is in the collection.
Related by theme, not necessarily by method or conclusion.
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AEA Papers and Proceedings · 2025 - New Frontiers: The Origins and Content of New Work, 1940–2018
The Quarterly Journal of Economics · 2024
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