Understanding the Careers of IT Freelancers on Digital Labor Platforms

Online freelancing as an alternative working form increasingly gains prominence in research and practice. Here, independent workers offer services on digital labor platforms. While the general understanding of this form of work increases, IT work performed in this form is not fully understood. Especially the collaborative nature of IT work and the high, rapidly changing skill level required, affects the career development of IT freelancers. Therefore, this study aims to understand how the careers of IT freelancers evolve. To answer our research question, we conduct an exploratory analysis of twelve IT freelancers on a digital labor platform. We develop an IT freelancing career process model. Furthermore, we outline advancement and decline mechanisms and different exit options from the digital labor platform. We also illustrate the role of IT freelancer teams. Our findings thus contribute to the body of knowledge on IT work and alternative work forms on digital labor platforms

Essays on platform work: freelancers on digital labor platforms

More and more people are working independently as online freelancers on digital labor platforms and the number of different projects mediated and coordinated on these online markets is increasing. We argue that the current understanding of platform work is incomplete. A mixed-method research strategy was used in this thesis. First, we collected and linked previous research findings to capture the status quo and derive avenues for future research. Based on this, we conducted four qualitative and quantitative empirical studies. First, we combined a latent-dirichlet allocation analysis of almost 3,000 forum posts from IT freelancers with an additional qualitative analysis. This was followed by two qualitative exploratory analyses using a total of 35 interviews with freelancers and clients on digital labor platforms and secondary data in the form of the personal online profiles and archival documents downloaded from the platforms. Finally, we analyzed a dataset of about 7,000 IT freelancer profiles using a negative binomial regression. Therefore, we develop a framework on digital labor platform research. By synthesizing findings from the literature, we develop a classification of forms of platform work and identify research gaps. Second, we synthesize and extend the challenges and identify discussion topics of online IT freelancers. We also illustrate specifics of IT freelancing. Third, we systematize the advancement, decline, and exit dynamics within a career model of online freelancing. We also define four underlying factors that alter freelancers' relationship with the platform. The probability of exit and the dependence and benefit of the platform change over time. Fourth, we illustrate the positive relationship between the use of signals and the success of IT freelancers. We develop a new signaling typology on digital labor platforms that includes three types of signals: activating, pointing, and supporting signals. Finally, we identify concrete IT-specific success factors. This work makes several contributions to theory and practice. We contribute to research on digital platforms by characterizing the forms of platform work, structuring and add-ing new aspects to the challenges of online freelancing, identifying success factors, and devel-oping a long-term and dynamic freelance career model. We also contribute to the platform literature that addresses specific platform mechanisms by explaining lock-in effects and switching costs related to platform power. We also contribute to the career literature by illustrating that the careers of online freelancers do not fit traditional career theories or perceptions of bounda-ryless or protean careers. We contribute to signaling theory by proposing a typology of signals and analyzing the signaling environment as an under-researched aspect. Moreover, we provide empirical evidence on the specifics of IT work on digital labor platforms. We also contribute to research dealing with skill obsolescence or IT teams. Finally, our results on the platform exit dynamics contribute to research on IT turnover. For practice, our results provide insights for online freelancers, organizations or individuals as clients and the platform owners