The role of contextual and contentual signals for online trust: Evidence from a crowd work experiment

Rense Corten (), Judith Kas (), Timm Teubner () and Martijn Arets ()
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Rense Corten: Utrecht University
Timm Teubner: Einstein Center Digital Future, TU Berlin

Electronic Markets, 2023, vol. 33, issue 1, No 41, 17 pages

Abstract: Abstract Platform workers can typically not take their ratings from one platform to another. This creates lock-in as building up reputation anew can come at prohibitively high cost. A system of portable reputation may mitigate this problem but poses several new challenges and questions. This study reports the results of an online experiment among 180 actual clients of five gig economy platforms to disentangle the importance of two dimensions of worker reputation: (1) contextual fit (i.e., the ratings’ origin from the same or another platform) and (2) contentual fit (i.e., the ratings’ origin from the same or a different job type). By and large, previous work has demonstrated the potential of imported ratings for trust-building but usually confounded these two dimensions. Our results provide a more nuanced picture and suggest that there exist two important boundary conditions for reputation portability: While imported ratings can have an effect on trust, they may only do so for matching job types and in the absence of within-platform ratings.

Keywords: Gig economy; Crowd work; Platform economy; Reputation portability; Trust; Signaling theory; Lock-in effects (search for similar items in EconPapers)
JEL-codes: D81 D82 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s12525-023-00655-2

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