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Record: oai:ARNO:617580

AuthorJeroen De Vos
TitleTracing the Social: A Mixed-Method Approach to Startup Ecosystems
SupervisorsT. Poell, B. Rieder
Year2016
Pages82
FacultyFaculty of Humanities
ProgrammeFGw RMA - Media Studies (research) - 425725
KeywordsEntrepreneurial ecosystem; mixed-methods; network-driven methodology; social startup entrepreneurs; The Netherlands
AbstractHow can something as complex as a local startup ecosystem be understood, captured and reproduced? Research addressing this question is mostly focussed on the United States, most notably Silicon Valley. Consequently, many models produced by this research presuppose an American sociopolitical system. The current body of literature on entrepreneurial ecosystems portrays the effort to understand such a complex phenomenon as one diagram-like system, existing of enumerated assets such as attributes, principles, pillars or components. Overall, these studies fail to acknowledge or incorporate the networked nature of such an entrepreneurial ecosystem.

This research project proposes a new approach to entrepreneurial ecosystems by making the ‘networkedness’ of these ecosystems central to the methodology. Building on digital methods, this investigation repurposes Twitter to unveil the affiliation network of Dutch social startups. Moreover, it employs bottom-up interview techniques as an alternative approach to understanding an ecosystem. Drawing from this material, the organisational mechanisms at work in the Dutch startup ecosystem will be scrutinised by tracing the networks in which a selection of five social startup entrepreneurs is entangled. These networks include a variety of actors: besides the startups themselves, organisations that facilitate integration and cross-community communication are also present within the ecosystem.

The aim of this thesis is to evaluate the added value of a network-driven methodology to entrepreneurial ecosystems. Collaborative readings of the network graphs produced from the collected Twitter data shows both the validity of network analysis, but it also demonstrates the limitations of digital methods research and static network graphs. An entrepreneurial ecosystem is a messy network of contributors, which can be depicted in a network graph. Such a graph is useful for exploratory purposes, but to interpret, understand and explain the complexities behind the colourful figures, qualitative field research is needed. This project shows how such a mix methods approach can be operationalized.
LanguageEngels
Document type scriptie master
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