Please use this identifier to cite or link to this item:
Facts vs. Stories - Assessment and Conventional Signals as Predictors of Freelancers’ Performance in Online Labor Markets
|Title:||Facts vs. Stories - Assessment and Conventional Signals as Predictors of Freelancers’ Performance in Online Labor Markets|
Stock, Ruth Maria
Online Labor Markets, Freelancer, Conventional Signals, Assessment Signals, Signaling Theory
|Issue Date:||03 Jan 2018|
|Abstract:||This paper investigates how freelancers’ use of signals predicts earnings in online labor markets. Extant literature has questioned the usefulness of some assessment signals to evaluate a freelancer’s quality. We find that conventional signals - signals based on non-verifiable information - can be predictors of higher revenue, when they are based on anecdotes of positive past events (self-promotion). However, mere kindness and flattery towards the customer (ingratiation) is negatively associated with a freelancers’ earnings in OLM. Moreover, we find evidence that the number of tests performed on the platform is significantly associated with higher earnings - with each test that is added to the profile a freelancer-˜s revenue increases by 4.1 %. We base our analysis on a sample of 1065 freelancers using objective financial earnings data, independent codings and survey data.|
|Rights:||Attribution-NonCommercial-NoDerivatives 4.0 International|
|Appears in Collections:||Crowd-based Platforms|
Please contact firstname.lastname@example.org if you need this content in an alternative format.
Items in ScholarSpace are protected by copyright, with all rights reserved, unless otherwise indicated.