Entrepreneurial ecosystems (EE) have become a prominent concept for researchers and policy-makers for regional economic development (Stam & Spigel, 2018). There is a widely held belief in practice and policy discourse – and an assumption in most research writings – that vibrant EEs are the ‘secret sauce’ to fostering entrepreneurship, and, in particular, high-growth companies (scale-ups). The success of vibrant ecosystems such as Silicon Valley is often attributed to the fact that “there is something in the air” that leads to innovation, despite recent evidence pointing towards strategic search processes as opposed to as serendipity and random encounters (Fitjar & Rodríguez-Pose, 2017).
At the individual/firm-level, these search processes and experimentations are key entrepreneurial activities (Kerr et al., 2014). Established practical blueprints that advocate learning through minimum viable products and other feedback-based mechanisms, include the entrepreneurship heuristic (Ries, 2011) and ‘disciplined entrepreneurship’ (Aulet, 2013). These approaches have become mainstream in the pursuit of building start-ups and scale-ups, but this ‘important empirical reality’ has been largely decoupled from academic discourse (Contigiani & Levinthal, 2019). Experimenting manifests itself in two related, yet distinct ways: business model innovation and modularity.
Through experimentation, entrepreneurs and firms create an emergent stock of ‘ecosystem knowledge’. However, the impact of EEs on supporting entrepreneurs and entrepreneurial ventures through providing access to this knowledge is under-researched and under-theorised. What kind of knowledge emerges at the ecosystem level and how this is, in turn, transformed into firm-level competitive advantage (Tallman et al., 2004) is not well understood.
This research projects aims to conceptualise ‘ecosystem knowledge’ and understand how this emergent stock of knowledge is created, accessed, and translated into competitive advantage. In particular, this study draws on research on entrepreneurial capital (Smith et al., 2016, Shaw et al., 2016) and the theoretical lens of social network theory (Scott, 1988) to devise a new methodological approach for empirical research. This will allow for a unique way of measuring the influence and effectiveness of ecosystems through business model innovation and modularity of the constituent firms.
These issues will be addressed using an innovative research approach through the Ethno-Visio Insight (EVI) app. The app is based on ecological momentary assessment, which “involves repeated sampling of subjects’ current behaviours and experiences in real time, in subjects’ natural environments [and] aims to minimize recall bias, maximize ecological validity, and allow study of the microprocesses that influence behaviours in real-world contexts” (Shiffman et al., 2008, p. 1). With the EVI app, it is possible to collect a rich dataset at the individual level in real time, from data about: geographical movements; participants' networking behaviours; their work agendas; and, their assessment of their actions and interactions. People use smartphones frequently during the day, which is why this method leads to a more contextually rich dataset compared to participants keeping a diary of their actions and interactions.
Set within this context, we invite applicants to submit a research proposal of up to 1,000 words, describing the proposed focus of their work including a background and potential contributions.
Due to the nature of this research, there will be plenty of opportunity to engage with external stakeholders, particularly in Glasgow and the newly formed Glasgow City Innovation District (GCID) as well as engaging with support programmes such as incubators and accelerators possibly beyond Glasgow.
The successful applicant will join a vibrant research community within the Hunter Centre for Entrepreneurship and the Centre for Doctoral Training in Innovation and Entrepreneurship. The will also become part of the Strathclyde Doctoral School. The Hunter Centre is now one of the largest university-based centres of entrepreneurship in the UK and is home to a team of recognised entrepreneurial experts. It's committed to engaging in, and drawing from, world class research to inform the design and delivery of a growing portfolio of useful learning experiences offered to 'Strathclyders' (students, staff and alumni) and also the wider entrepreneurial ecosystem.
Aulet, B. (2013). Disciplined Entrepreneurship: 24 Steps to a Successful Startup. Hoboken, NJ: John Wiley & Sons, Inc.
Contigiani, A., & Levinthal, D. A. (2019). Situating the construct of lean start-up: adjacent conversations and possible future directions. Industrial and Corporate Change. doi:10.1093/icc/dtz013
Fitjar, R. D., & Rodríguez-Pose, A. (2017). Nothing is in the Air. Growth and Change, 48(1), 22-39.
Kerr, W. R., Nanda, R., & Rhodes-Kropf, M. (2014). Entrepreneurship as Experimentation. Journal of Economic Perspectives, 28(3), 25-48.
Ries, E. (2011). The lean startup: How today's entrepreneurs use continuous innovation to create radically successful businesses. New York, NY: Random House, Inc.
Scott, J. (1988). Social network analysis. Sociology, 22(1), 109-127.
Shaw, E., Wilson, J. and Pret, T. (2016). ‘The process pf embedding a small firm in its industrial context’. International Small Business Journal. P. 1-25.
Shiffman, S., Stone, A. A., & Hufford, M. R. (2008). Ecological Momentary Assessment. Annual Review of Clinical Psychology, 4, 1-32.
Smith, B., Smith, C., and Shaw, E. (2016). ‘Embracing digital networks: entrepreneurs’ social capital online’. Journal of Business Venturing. P1-44.
Stam, E., & Spigel, B. (2018). Entrepreneurial Ecosystems. In R. Blackburn, D. De Clercq, J. Heinonen, & Z. Wang (Eds.), Handbook for Entrepreneurship and Small Business. London, UK: Sage.
Tallman, S., Jenkins, M., Henry, N., & Pinch, S. (2004). Knowledge, Clusters, and Competitive Advantage. Academy of Management Review, 29(2), 258-271.