The ‘gig economy’ presents a contested new work arrangement where freelancers find work on digital platforms. Subsequently, previous research has investigated how gig workers develop solidarity and take collective action against the exploitative practices of the platforms. However, this research is limited by mostly focusing on solidarity in contexts of local gig worker communities. We investigate whether freelancers who work on a global platform, Upwork, which hires people for diverse and complex jobs, can build up solidarity in a global online community. Applying a mixed-methods research design, we analysed how gig workers responded to a policy change by Upwork that affected their working conditions negatively. In doing so, we outline how solidarity breaks down in an online community of gig workers, due to them realising different interests and identities. We contribute to recent discussions on solidarity in the gig economy, and online communities as tools for organising.
Jones, Marius & Schou, Peter Kalum (2022)
Structuring the Start-up: How Coordination Emerges in Start-ups through Learning Sequencing
To succeed in growing and scaling their organization, start-ups must establish roles, routines, rules, and plans that coordinate organizational activities. However, early-stage start-ups often lack such coordination mechanisms. Through a longitudinal qualitative multiple-case study of five start-ups, we develop an emergent theoretical framework for how start-ups develop and improve coordination over time. We find that start-ups establish coordination through a learning sequence consisting of four distinct learning styles. To develop coordination successfully, start-ups anticipate coordination problems before they escalate, steal ideas and frameworks from others, experimentally implement coordination, and combine and simplify coordination mechanisms. By providing a processual understanding of how start-ups develop coordination, we contribute to the literature on coordination in start-ups, which has tended towards static explanations. We also add to the literatures on emergent coordination and organizational learning, as we highlight the role of deliberate learning in developing coordination, and how different learning styles link together to create learning sequences.
Bucher, Eliane; Schou, Peter Kalum, Waldkirch, Matthias, Grünwald, Eduard & Antons, David (2021)
Structuring the Haystack: Studying Online Communities with Dictionary-Based Supervised Text Analysis and Network Visualization
Symon, Gillian; Pritchard, Katrina & Hine, Christine (red.). Research Methods for Digital Work and Organization: Investigating Distributed, Multi-Modal, and Mobile Work
Meurer, Madeleine; Waldkirch, Matthias, Schou, Peter Kalum, Bucher, Eliane & Burmeister-Lamp, Katrin (2021)
Digital affordances: how entrepreneurs access support in online communities during the COVID-19 pandemic
COVID-19 has caused significant and unforeseen problems for entrepreneurs. While entrepreneurs would normally seek social support to help deal with these issues, due to social distancing, physical networks are often not available. Consequently, entrepreneurs must turn to alternative support sources, such as online communities, raising the question of how support is created in such spaces. Drawing on an affordance perspective, we investigate how entrepreneurs interact with online communities and base our qualitative analysis on conversation data (76,365 posts) from an online community of entrepreneurs on Reddit during the COVID-19 pandemic. Our findings draw out four affordances that online communities offer to entrepreneurs (resolving problems, reframing problems, reflecting on situations, refocusing thinking and efforts), resulting in a framework of entrepreneurial support creation in online communities. Thus, our study contributes to debates around (1) entrepreneurs’ support during COVID-19 and (2) digital affordances in the entrepreneurship context.
Waldkirch, Matthias; Bucher, Eliane, Schou, Peter Kalum & Grünwald, Eduard (2021)
Controlled by the algorithm, coached by the crowd–how HRM activities take shape on digital work platforms in the gig economy
An increasing number of workers turn to digital platforms – such as Fiverr, Freelancer, and Upwork – as an alternative to traditional work arrangements. Digital platforms govern how gig workers join, move through, and leave platforms – often with the help of self-learning algorithms. While digital platforms and algorithms take on HRM practices, we know little about how HRM activities unfold on digital work platforms in the gig economy. The study therefore aims to understand how HRM activities apply to and take shape on digital platforms by studying worker perceptions. We combine supervised text analysis with an in-depth qualitative content analysis, relying on 12’924 scraped comments from an online forum of workers on Upwork. We outline five conversations on HRM practices that pertain to access and mobility, training and development, scoring and feedback, appraisal and control and platform literacy and support. Based on these findings, we build five propositions about how digital work platforms employ HRM activities. Our paper contributes to recent work on HRM on digital platforms by (1) developing a new mixed-methods approach that illustrates how the content of HRM practices may differ from traditional organizations, (2) highlighting the changing role of actors in creating HRM practices by introducing the concept of ‘crowd-created’ HRM practices, and (3) conceptualizing how digital platforms employ a ‘hybrid HRM approach’.
Schou, Peter Kalum; Bucher, Eliane & Waldkirch, Matthias (2021)
New digital technologies possess the potential to transform entrepreneurial processes, such as how entrepreneurs pursue opportunities and access funding and how they learn. How entrepreneurs learn may be transformed as digital technologies provide new spaces for learning, such as online communities. Online communities can gather thousands of participants and provide entrepreneurs with new opportunities for learning that are not limited by time, space, or social class. Yet, we know little about how entrepreneurs take advantage of the new digital opportunities of learning. To remedy this, we studied a large online community of entrepreneurs on Reddit (r/startups), where we qualitatively analyzed the top-voted 100 threads from 2018 to 2019 (10,277 comments in total). By drawing on coactive vicarious learning, a theory that describes how learning is socially constructed through discursive interactions, we outline how entrepreneurial learning is socially constructed through conversations, which are taking place in different micro-learning contexts. Through identifying distinct entrepreneurial learning conversations, we build new theory on entrepreneurial learning in online communities. Our theorizing contributes to (1) the growing research on how entrepreneurial learning is socially constructed in communities, (2) the current debate on knowledge creation in online communities, and (3) the knowledge on how coactive vicarious learning unfolds in communities.
Schou, Peter Kalum (2020)
Towards a contingency theory of how network structures influence the entrepreneurial process
Algorithmic management is used to govern digital work platforms such as Upwork or Fiverr. However, algorithmic decision-making is often non-transparent and rapidly evolving, forcing workers to constantly adapt their behavior. Extant research focuses on how workers experience algorithmic management, while often disregarding the agency that workers exert in dealing with algorithmic management. Following a sociomateriality perspective, we investigate the practices that workers develop to comply with (assumed) mechanisms of algorithmic management on digital work platforms. Based on a systematic content analysis of 12,294 scraped comments from an online community of digital freelancers, we show how workers adopt direct and indirect “anticipatory compliance practices”, such as undervaluing their own work, staying under the radar, curtailing their outreach to clients and keeping emotions in check, in order to ensure their continued participation on the platform, which takes on the role of a shadow employer. Our study contributes to research on algorithmic management by (1) showing how workers adopt practices aimed at “pacifying” the platform algorithm; (2) outlining how workers engage in extra work; (3) showing how workers co-construct the power of algorithms through their anticipatory compliance practices.