How Mobile-Friendly is Crowdwork? Mobile Affordances, Perpetual Contact and Inequalities in the Gig Economy
Christoph Lutz Nordic Centre for Internet and Society BI Norwegian Business School Nydalsveien 37 0484 Oslo, Norway email@example.com
Gemma Newlands Nordic Centre for Internet and Society BI Norwegian Business School Nydalsveien 37 0484 Oslo, Norway firstname.lastname@example.org
Submission track: Sociology and Humanities
Gig economy platforms, such as Amazon Mechanical Turk, Uber, and Deliveroo, have contributed to the global economy by opening up previously un-tapped sources of income (Alkhatib, Bernstein, & Levi, 2017). As opportunities for micro-entrepreneurship, such new forms of self-employment have been welcomed due to their promised flexibility and autonomy. However, qualitative studies across different gig economy sectors suggest that such flexibility is lowered because workers should be constantly available to get the most profitable ‘gigs’ (e.g., Lehdonvirta, 2018). In the gig economy, worker management is enabled, not least, through the widespread availability of powerful mobile devices; many gig economy platforms require constant availability – or ‘perpetual contact’ (Katz & Aakhus, 2002) – with the platform. In that sense, the affordances of mobile media, such as portability, availability, locatability, and multimediality (Schrock, 2015), facilitate all types of gig economy work but particularly “asset-based services” (Howcroft & Bergvall-Kåreborn, 2018), where a large part of the actual work is carried out offline (e.g., Deliveroo, Foodora, TaskRabbit).
Through the portability and availability affordances, gig work apps or websites can be in perpetual contact with their workers, sending reminders and notifications in the manner of a supervisor. Workers can be notified any time about well-paying gigs and surge prices. Thus, constant availability, permanence, or vigilance become important success factors (Klimmt, Hefner, Reinecke, Rieger, & Vorderer, 2017). These affordances also mean that gig work can be sought for and undertaken at any moment, raising the possibility of multi-tasking, gamified engagement, casual browsing, and blurred boundaries between work and spare time. The locatability and multimediality affordances of mobile devices are similarly crucial for gig
work, as many gig workers rely on GPS-navigation as well as on the multimediality of the app to offer the varied services required to carry out the task. However, for online forms of gig work, or “online task crowdwork” (Howcroft & Bergvall-Kåreborn, 2018), such as Amazon Mechanical Turk, mobile devices may become a suboptimal interface due to their limited functionality (Napoli & Obar, 2014). Particularly, mobile devices might restrict the types or quantity of tasks which can be undertaken. For example, transcription or extended writing tasks, as well as data intensive tasks, may be incompatible with mobile-based participation. As such, workers may face a cognitive tension between a pressure or opportunity to work and the ability to work effectively and optimally.
We are currently conducting a study on mobile affordances in the gig economy. In a first step, our research focuses on online task crowdwork (e.g., Amazon Mechanical Turk and Prolific), whereby workers are queried about the roles mobile devices play in facilitating, encouraging, or restricting work – both during and outside their self-determined working time. To do so, we use an online survey with at least 500 participants, recruited through Amazon Mechanical Turk and Prolific. The survey includes a range of standardized and closed questions, with a maximum of two text box type questions. Respondents are recruited in the United States (Amazon Mechanical Turk) and the United Kingdom (Prolific). Particular emphasis is on the experience of nudging through automated messages and notifications. In case of acceptance, we will be able to present findings from this study. After this initial study, we plan to extend the research to asset-based services by investigating mobile practices among ride hailing and food delivery drivers. Beyond quantitative studies, additional research on this topic using qualitative and ethnographic research would help to contextualize the role of mobile devices in organizing work in the gig economy, including the close observation of actual practices. Studies from a STS angle or from a human-computer- interaction perspective could study the design of apps and the political economy of the companies behind them. Here, walkthroughs of apps across different gig economy sectors would be a suitable approach (Light, Burgess, & Duguay, 2018).
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