Reputation and trust on online labour markets: the reputation economy of Elance

Abstract

This article examines profile data about 9,593 freelancers from 121 countries active in the Design and Multimedia section of Elance, a major online labour market existing up until 2015. Using statistical analysis, the article evidences that the earnings a contractor obtains from working through Elance positively correlates with higher reputation scores and suggests that the conception of trust among actors operating on an online labour market resembles that which characterises e-commerce platforms like eBay or Amazon, where trust relations among ‘strangers’ are guaranteed by an algorithmic-based third party that translates feedbacks and rankings into a numerical reputation proxy.

A Relational Work Perspective on the Gig Economy: Doing Creative Work on Digital Labour Platforms

“…Accordingly, algorithmic management has often been found to exercise ‘softer’ forms of control than traditional management, including ‘reputational control’ via the imposition of ‘information asymmetries’ in which client-generated discretionary feedback, reviews and ratings (stars, likes) are calculated, interpreted and rendered actionable by largely inscrutable and opaque processes of automation and computation. These factors all directly affect the standing and visibility of gig workers on the platform and hence their ability to earn a living (Rosenblat and Stark, 2016; Shapiro, 2018), since higher reputation scores correlate strongly with higher earnings on labour platforms (Gandini et al, 2016).…”

Reputation systems and recruitment in online labor markets: insights from an agent-based model

“…The work of Pallais [44] illustrates this with experimental evidence: Freelancers with no prior work experience who received the experimental treatment-being hired for a project and obtaining positive feedback-almost tripled their relative income in comparison to the control group (not hired for a project). One of the coping strategies that freelancers use to accrue an initial reputation is selling labor at a substantially lower cost to attract the first clients [22]. Furthermore, empirical research has shown that poor reputation leads to lower bid amounts in auctions on the side of workers, to compensate for the perceived disadvantage due to a low reputation score [15].…”

“…This means that there is a mix of employees in terms of the jobs that they have received in the past and the reputations that they have developed based on this. To model the distribution of the number of jobs that employees have received before, the number of previously received jobs comes from a random exponential distribution (with = 1∕2 ; rounded down to the nearest integer) where the majority of users received small number of jobs and a minority of users received a large number of jobs (see [22]). Earnings are initially set to zero, to track how much a given freelancer was able to earn since the start of the simulation.…”

“…Trying to alleviate this problem, the existing OLM platforms have implemented various reputation systems that aim at aggregating information about freelancers' talents and previous conduct on the platform [22,57]. At first glance, the use of reputation systems in an OLM context appears attractive, as such systems may make it easier for employers to assess the abilities and trustworthiness of potential employees.…”

Role of Reputation in Sustainable Performance of Online Crowdsourcing Vendors: An Explanation From Transaction Cost Theory

“…A few studies have done some related research. Evidence have been found that the earnings a contractor obtains from working through crowdsourcing market positively correlates with higher reputation scores ( Gandini et al, 2016 ). In more detail, reputation has a significant impact on the transaction type of fixed-price contracts, but no obvious impact for time-material contracts ( Lin et al, 2018 ).…”