Abstract
This chapter concludes the book by addressing the scope and limitations of the epigenetic analogy (i.e. EED) introduced in it. The chapter discusses in depth how economic analysis falls somewhat short of offering explanations and predictability of the digital ecosystem, concluding that an ecology-biology analogy may be appropriate as a body of knowledge to offer explanations and predictability. One of the problems encountered in any analysis undertaken within the Internet ecosystem is the definition of the borders. Setting topological markers proves difficult due to the dynamic nature of the ecosystem concerned, its powerful permeability and penetration in other production sectors and its eagerness to radically transform these. The book has partially included the analysis of the consequences of epigenetic dynamics. However, since consequences are only observed ex-post, the undertaken analysis of this is still rather partial, remaining as a matter of further work. There are new analytical challenges for the biological analogy in general, upon which the field of evolutionary economics is based, and for the EED approach introduced in this book in particular, that require the construction of models with explanatory and predictability potential so that they can orient policy makers’ and business management’s decision-making. This last aspect is an even more sensitive subject and calls for further research, which we aim, as a community, to be able to accomplish in the following years to come.
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- 1.
The software industry in general, and the Internet ecosystem in particular, can be regarded as sectors where the main share of the total cost of the firms operating in them is a fixed cost. Accordingly, as the size of the companies becomes larger, the costs continue dwindling. In fact, since the marginal cost is almost zero, if there were perfect competition, the equilibrium price would also be zero.
- 2.
This model and the following one are used in the field of Organizational Ecology to establish the competitive atmosphere and explain the mortality rate of organizations (Hannan and Freeman 1977; Hannan et al. 1995; Baum and Shipilov 2006). Organizational ecology is a valuable addition to the repertoire of theories that guide digital innovation policy when extended to community and ecosystem levels (Su 2011). Given the nature of the subject of this book, part of its findings and development may be applied to the EED approach introduced in it.
- 3.
As discussed in Chapter “Epigenetic Economics Dynamics in the Internet Ecosystem”, an additional value of a device (e.g. tablet, Smartphone, etc.) increases the value of the previous device, insomuch as a general service is offered, at the same time, it works to increase the business ecosystem, which provides a substantial value in the product or service being offered. This is what Kelly (1998) labelled as the “fax effect”.
- 4.
In relation to the density dependence model, a mass dependency model can also be found (Barnett and Amburgery 1990). From this point of view, the size or the organizational dimension is understood as the main variable explaining the competitive behavior, so that firm competitiveness is positively related to size. However, far from density and mass being alternative explanations, they may be compatible and can improve our understanding of the sector’s behaviour. Along these lines, there are very interesting developments in Moyano and Nuñez (2002, 2004) applied to sectors different to the digital one, which make the two models compatible.
- 5.
As far as the present study is concerned, the most appropriate focus may be synthetic, in which the external approach (i.e. the environment induces change) can be made compatible with the internal one (i.e. internal capacity determines evolution). Given its complexity, formed by its own cross-cutting dynamics, the digital world creates fields to test the two approaches simultaneously. However, it is more difficult to track the endogenous or internal approach in comparison with the external one. The latter has some quantitative indicators such as density and mass that make it possible to run reasonably accurate analyses.
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Barrutia, J., Gómez-Uranga, M., Zabala-Iturriagagoitia, J.M. (2016). Scope and Limitations of the Epigenetic Analogy: An Application to the Digital World. In: Gómez-Uranga, M., Zabala-Iturriagagoitia, J., Barrutia, J. (eds) Dynamics of Big Internet Industry Groups and Future Trends. Springer, Cham. https://doi.org/10.1007/978-3-319-31147-0_8
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