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

Rense Corten, Judith Kas, Timm Teubner*, Martijn Arets

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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.

Original languageEnglish
Article number41
Pages (from-to)1-17
Number of pages17
JournalElectronic Markets
Volume33
Issue number1
DOIs
Publication statusPublished - 14 Aug 2023

Keywords

  • Crowd work
  • Gig economy
  • Lock-in effects
  • Platform economy
  • Reputation portability
  • Signaling theory
  • Trust

Fingerprint

Dive into the research topics of 'The role of contextual and contentual signals for online trust: Evidence from a crowd work experiment'. Together they form a unique fingerprint.

Cite this