The DOI matches its Crossref record; 36 of the 37 references it cites were found in a registry or an index.
Inferring Supplier Quality in the Gig Economy: The Effectiveness of Signals in Freelance Job Markets
Open accessAbstract
Inferring quality of labor suppliers is a challenge in the gig economy. Many online freelance job markets address this challenge by incorporating signals. We test effectiveness of two kinds of information signals as indicators of supplier quality: skill signal (which reflects suppliers’ skill and potential), and achievement signal (which reflects suppliers’ past achievement). We theorize that two job characteristics in cross-national labor demand settings strengthen effectiveness of these signals: job duration, and cultural distance. Econometric analysis on a dataset from a leading online freelance job marketplace containing information on jobs posted by buyers and completed by suppliers located across several countries supports our hypotheses. We find that both skill and achievement signals are more effective at inferring supplier quality in jobs involving longer duration, and in jobs involving greater cultural distance between buyers and suppliers.
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Online freelance job markets provide skill signals to endorse gig workers' higher expertise levels and work quality.
“Similar to ranking, online freelance job markets also provide skill signals to endorse gig workers' higher expertise levels and work quality (Kathuria et al., 2021).”
From Socio‐technical issues in the platform‐mediated gig economy: A systematic literature review: An Annual Review of Information Science and Technology (ARIST) paper (2024) · cites this paper as Kathuria et al., 2021
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Metadata
- Authors
- Kathuria, A., Saldanha, T., Khuntia, J., Andrade Rojas, M., Mithas, S., & Hah, H.
- Affiliations
- Indian School of Business (IN)
- University of Georgia (US)
- University of Colorado Denver (US)
- University of South Florida (US)
- Florida International University (US)
- Venue
- Proceedings of the Annual Hawaii International Conference on System Sciences
- Published
- 2021
- ISSN
- 1530-1605 (ISSN-L)
- 2572-6862
- OpenAlex
- W3126400892
- Cited by
- 18
- References
- 37
- Citations by year
- 2025: 2 · 2024: 4 · 2023: 5 · 2022: 5 · 2021: 2
- FWCI
- 10.66
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Hawaii International Conference on System Sciences (HICSS) (publishedVersion)
- ScholarSpace (University of Hawaii at Manoa) (submittedVersion, cc-by-nc-nd)
- Journal of the Association for Information Systems (submittedVersion)
- Digital Eprints Services at ISB (DESI) (Indian School of Business) (submittedVersion, cc-by-nc-nd)
- Figshare (submittedVersion)
- Topics
- Social Sciences › Sociology and Political Science › Digital Economy and Work Transformation
- Physical Sciences › Computer Science › Computer Science Applications › Mobile Crowdsensing and Crowdsourcing
- Social Sciences › Decision Sciences › Management Science and Operations Research › Auction Theory and Applications
- Keywords
- gig economy, information signals, job tenure, cultural distance, online job boards, labor demand
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