FROM INCUBATORS TO ECOSYSTEMS: EVALUATING THE STARTUP DIGITAL ECONOMY CLUSTER OF HULL CITY

LITERATURE GAPS

Through the review of the literature, several research gaps have been located. A few recommended lines of inquiring leads to interrogate the nature of the dimensional interaction between value, transaction, and resources within the business model narratives. In the present research, networks are being considered as resources. According to George and Block, (2010:6) “understanding the nature of dimensional interaction represents a potentially informative area of study, and processual studies of business model change could describe how dimensional dynamics interact with underlying changes in the opportunity landscape”. This sort of description may, in turn, result helpful to understand how the complexity of business culture is enhanced by the network activities of start-ups, which are indeed one of the most relevant changes in the opportunity landscape.

There is also a few literature interrogating issues surrounding the business model concept in a networked world or linking business models to complexity management in strategy research. Zott and Amit (in Kleindorfer et al., 2009), in their paper ‘The role of business models as the engine of a network-based strategies’ describe the role of business models in creating value through networks, paying special attention to the central design task of entrepreneurs and managers.

In that sense, also Ormerod argues the need for a less mechanistic approach to the study of economic phenomena: “Economies and societies are not machines. They are more like living organisms. Individuals do not act in isolation but affect each other in complex ways” (Ormerod, 1998 in Comunian 2010:18) hence the use of the ecosystem metaphor to describe network value within the digital economy. Other problems arise in the distributed responsibility and evolution that characterize complex systems. It is being reported that, while data analysis and representation is improving over time, especially in terms of visualization methods, the challenge remains in the interpretation of data regarding human systems, and complexity theory can serve as the bridge between disciplines in order to make sense of the problem. On the other hand, according to Roberta Comunian, “the challenge of applying CT to social systems is the fact that change is an intrinsic system function—where even small changes at the grassroots level affect how the system is, and how it will subsequently change. This should be the new challenge for researchers wanting to investigate the role of culture in urban environments”  (2010:17-18).

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