Flexibility in the gig economy: managing time on three online piecework platforms
Open accessAbstract
Gig economy platforms seem to provide extreme temporal flexibility to workers, giving them full control over how to spend each hour and minute of the day. What constraints do workers face when attempting to exercise this flexibility? We use 30 worker interviews and other data to compare three online piecework platforms with different histories and worker demographics: Mechanical Turk, MobileWorks, and CloudFactory. We find that structural constraints (availability of work and degree of worker dependence on the work) as well as cultural‐cognitive constraints (procrastination and presenteeism) limit worker control over scheduling in practice. The severity of these constraints varies significantly between platforms, the formally freest platform presenting the greatest structural and cultural‐cognitive constraints. We also find that workers have developed informal practices, tools, and communities to address these constraints. We conclude that focusing on outcomes rather than on worker control is a more fruitful way to assess flexible working arrangements.
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Researchers found that the flexibility of gig work could result in an erosion of work-life boundaries, as seen in some gig workers' unhealthy behaviors, such as eating and sleeping near a computer, to keep track of future gig work.
“In contrast, researchers also found that the flexibility of gig work could result in an erosion of work-life boundaries, as seen in some gig workers' unhealthy behaviors, such as eating and sleeping near a computer, to keep track of future gig work (Lehdonvirta, 2018).”
From Gig work and gig workers: An integrative review and agenda for future research (2024) · cites this paper as Lehdonvirta, 2018
Previous studies among gig workers have reported that algorithmic task allocation often results in job insecurity.
“Previous studies among gig workers have further reported that algorithmic task allocation also often results in job insecurity, (Griesbach et al., 2019;Lehdonvirta, 2018;Veen et al., 2019;Wood, Graham, Lehdonvirta, & Hjorth, 2019)”
From Algorithms as work designers: How algorithmic management influences the design of jobs (2022) · cites this paper as Lehdonvirta, 2018
Scheduling nudges tend to systematically orient workers toward certain schedules due to the high cost of overriding the nudges.
“The actual evidence regarding scheduling nudges, automated incentives displayed to workers to encourage them to work in specific times, shows that these incentives tends to systematically orient workers toward certain schedules due to the high cost of overriding the nudges (Griesbach et al., 2019;Lehdonvirta, 2018;Mateescu & Nguyen, 2019a;Rani & Furrer, 2020;Rosenblat, 2018;Rosenblat & Stark, 2016”
From Algorithms as work designers: How algorithmic management influences the design of jobs (2022) · cites this paper as Lehdonvirta, 2018
Algorithmic scheduling activities may limit workers' voice and active role in determining their schedule, reducing their autonomy.
“Researchers have found that algorithmic scheduling activities may limit workers' voice and the active role in the determination of their schedule, reducing their level of autonomy (Jabagi et al., 2019;Lehdonvirta, 2018;Moore & Hayes, 2018).”
From Algorithms as work designers: How algorithmic management influences the design of jobs (2022) · cites this paper as Lehdonvirta, 2018
Algorithmic goal setting is positively associated with job insecurity.
“Job insecurity (+)”
From Algorithms as work designers: How algorithmic management influences the design of jobs (2022) · cites this paper as Lehdonvirta (2018)
Algorithmic scheduling is positively associated with workload.
“Workload (+)”
From Algorithms as work designers: How algorithmic management influences the design of jobs (2022) · cites this paper as Lehdonvirta (2018)
Algorithmic scheduling is negatively associated with job autonomy.
“Autonomy (-)”
From Algorithms as work designers: How algorithmic management influences the design of jobs (2022) · cites this paper as Lehdonvirta (2018)
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References 70 · Cited by 550
- Authors
- Lehdonvirta, V.
- Affiliations
- University of Oxford (GB)
- Corresponding author
- Lehdonvirta, Vili
- ORCID
- Lehdonvirta, Vili
- Venue
- New Technology, Work and Employment
- Publisher
- Wiley
- Published
- 2018-02-05
- Volume
- 33
- Issue
- 1
- Pages
- 13-29
- ISSN
- 0268-1072 (ISSN-L)
- 1468-005X
- OpenAlex
- W2784059491
- Cited by
- 550
- References
- 70
- Citations by year
- 2026: 77 · 2025: 78 · 2024: 76 · 2023: 94 · 2022: 76 · 2021: 70 · 2020: 40 · 2019: 29 · 2018: 10
- FWCI
- 84.75
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- New Technology Work and Employment (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- SocArXiv (OSF Preprints) (submittedVersion)
- SocArXiv (OSF Preprints) (submittedVersion, cc-by-nd)
- Zenodo (CERN European Organization for Nuclear Research) (submittedVersion, other-oa)
- Funders
- Liikesivistysrahasto (31850)
- H2020 European Research Council (639652)
- Topics
- Social Sciences › Sociology and Political Science › Digital Economy and Work Transformation
- Social Sciences › Safety Research › Employment, Labor, and Gender Studies
- Social Sciences › Sociology and Political Science › Work-Family Balance Challenges
- Keywords
- gig economy, temporal flexibility, procrastination, presenteeism, structural constraints, cognitive limitations, Mechanical Turk, worker communities, flexible work arrangements
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