Information Systems Research on Digital Platforms for Knowledge Work: A Scoping Review

Digital platforms for knowledge work, such as Upwork, Freelancer.com and Amazon Mechanical Turk connect clients with millions of workers for a range of tasks, including software development, virtual assistance, and micro-tasks. Information systems research on this emergent phenomenon has gained traction in recent years regarding publication volume and research diversity. To identify relevant papers, to distinguish them from related types of digital platforms, and to guide future research, we conducted a scoping review, focusing on the information systems literature. Results are structured according to a theoretical framework of the knowledge work process, covering three phases: Worker-client matching, committing for future action, and executing commitments. While the first phase has been analyzed extensively, we contend that the main phases of the knowledge work process have received scant attention. In this emergent stage of extant research, our review identifies promising research directions to guide prospective studies

Role of Communication in Online Platforms

Online labor markets facilitate matching of workers and employers in a borderless virtual environment. Much of the attraction of these markets for employers derives from access to a large, geographically dispersed pool of workers. However, recent literature highlights that these markets are subject to issues such as employer biases against hiring distant workers and against new workers who lack reputation information. We examine the often-ignored role of pre-contract communication between workers and employers (via the platform-hosted private messaging system), which holds the potential to enhance workers\u27 probability of being hired while mitigating these biases. Based on private messaging activities between workers and employers from nearly half a million job applications on Freelancer.com, we quantify the causal impact on hiring outcomes from workers\u27 outreach to employers via private messaging, in addition to exploring the effects of message content. We find that initiating private messaging with a potential employer lifts a worker\u27s probability of being hired by roughly 29% over baseline. Moreover, these beneficial effects are amplified when workers reside at a distance, lack reputation, or bear negative reputation, demonstrating that private messaging can in fact attenuate the aforementioned hiring biases. The effects are also magnified when employers lack platform hiring experience, likely because such employers bear higher uncertainty and are more risk-averse