Cited by 41Digital Economy and Work TransformationLegal and Labor StudiesMobile Crowdsensing and Crowdsourcing

Justice expectations in crowd and platform-mediated work

Open access
Pfeiffer, Sabine, Kawalec, Sandra·2020·The Economic and Labour Relations Review

Published version of a preprint

Abstract

Crowdwork conducted via digital platforms is a young form of work, but a growing part of the gig economy. Typical for crowdwork is low pay, volatile income streams and no social security benefits. Also, crowdworkers have few possibilities for social comparison or negotiation because they work outside of company organisations. This article examines the question of whether these conditions mean that crowdworkers’ expectations about justice in crowdwork arrangements differ in comparison to their expectations regarding justice in conventional employment relationships. This question is addressed empirically on the basis of 36 qualitative interviews and a survey of 230 crowdworkers. The justice expectations of crowdworkers involved in different types of crowdworking platforms in German-speaking countries were examined. In our sample, crowd work typically serves to supplement – not replace – conventional employment. This explorative research shows that crowdworkers use similar standards of justice regarding work performance in their evaluations of work mediated via crowdwork platforms and conventional employment. It shows that crowdworkers perceive injustices in four specific areas: planning insecurity, lack of transparency in performance evaluation, lack of clarity in task briefings and low remuneration. These areas correspond to the theoretical dimensions of distributive and procedural justice on Colquitt’s (2001) organisational justice scale. These findings have implications for future efforts to regulate crowdwork.

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Registry

Crossref · 10.1177/1035304620959750

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  • Compared with human agents, algorithmic agents resulted in perceptions of lower employer commitment when delivering the organization's socio-emotional support for employees' growth and well-being.

    “Compared with human agents, algorithmic agents (i.e., recruiting software) resulted in perceptions of lower employer commitment when delivering the organization's socio-emotional support for employees' growth and well-being.”

    From Gig work and gig workers: An integrative review and agenda for future research (2024) · cites this paper as Pfeiffer and Kawalec (2020)

  • Algorithmic management had an impact on workers' psychological contract.

    “Pfeiffer and Kawalec (2020) and Lee (2022)found that algorithmic management had an impact on workers' psychological contract.”

    From Gig work and gig workers: An integrative review and agenda for future research (2024) · cites this paper as Pfeiffer and Kawalec (2020)

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Authors
Pfeiffer, S., & Kawalec, S.
Affiliations
  • Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
  • Institut für Arbeitsmarkt und Berufsforschung (DE)
Corresponding author
Pfeiffer, Sabine
Venue
The Economic and Labour Relations Review
Published
2020-12
Volume
31
Issue
4
Pages
483-501
ISSN
  • 1035-3046 (ISSN-L)
  • 1838-2673
OpenAlex
W3081677874
Cited by
41
References
2
Citations by year
2026: 7 · 2025: 8 · 2024: 12 · 2023: 7 · 2022: 5 · 2021: 2
FWCI
4.68
Type
journal article
Language
en
Open access
Locations
  • The Economic and Labour Relations Review (publishedVersion, cc-by-nc)
  • OPUS Repository (Kooperativer Bibliotheksverbund Berlin-Brandenburg) (submittedVersion, cc-by-nc)
  • RePEc: Research Papers in Economics (submittedVersion)
  • Figshare (submittedVersion, cc-by)
Funders
  • Deutsche Forschungsgemeinschaft (Priority Programme “The Digitalisation of Workin)
  • FAU Emerging Fields Initiative (“Discourses and Practices of a ‘Digital Sovereignt)
Topics
  • Social Sciences › Sociology and Political Science › Digital Economy and Work Transformation
  • Social Sciences › Business, Management and Accounting › Industrial relations › Legal and Labor Studies
  • Physical Sciences › Computer Science › Computer Science Applications › Mobile Crowdsensing and Crowdsourcing
Keywords
crowdwork, gig economy, distributive justice, procedural justice, online labour platforms, work performance evaluation, transparency, low wages, gig economy regulation

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