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Publication of “The Future of Work in the ‘Sharing Economy’. Market Efficiency and Equitable Opportunities or Unfair Precarisation?”

May 31, 2016

We are glad to announce that the review essay “The Future of Work in the ‘Sharing Economy’. Market Efficiency and Equitable Opportunities or Unfair Precarisation?” written by Cristiano Codagnone, Fabienne Abadie and Federico Biagi has been published and is ready for download in the European Commission’s JRC Publications Repository.

This critical and scoping review essay analyses digital labour markets where labour-intensive services are traded by matching requesters and providers. It focuses on digital labour markets which allow the remote delivery of electronically transmittable services (i.e. Amazon Mechanical Turk, Upwork, Freelancers, etc.) and those where the matching and administration processes are digital but the delivery of the services is physical and requires direct interaction. The essay defines and conceptualises digital labour markets proposing a typology which proves to be empirically valid and heuristically useful. It describes their functioning and the socio-demographic profiles of the participants, reviews their economic and social effects, discusses the possible policy implications, and concludes with a research agenda to support European level policy making. It alternates the discussion of ‘hard’ findings from experimental and quasi-experimental studies with analysis of ‘softer’ issues such as rhetorical discourses and media ‘hyped’ accounts.

The findings of this essay show, among other things, that: a) individuals engage in these activities primarily for money, for a large segment of them this work is their primary source of income, and most are under-employed and self-employed and fewer are unemployed and inactive; b) matching frictions and hiring inefficiencies are widespread and even the OLMs are far from being globalised online meritocracies; and c) a behavioural approach to big data exploration should be further applied because there is emerging evidence of heuristic and biases contributing to hiring inefficiencies.