Conclusions: Towards an Evolutionary Perspective of Smart City Planning
This smart city strategy and action plan formation process challenges not only the concept of top-down planning, but also the capacity for smart city plans being formulated exclusively by state authorities. Smart city planning as a complex process was discussed by Leydesdorff and Deakin (2011) and Deakin (2015). The authors link smart city planning to the rise of triple helix governance and attribute its neo-evolutionary character to three functions that shape the selection environments of the smart city knowledge economy: organized knowledge production, economics of wealth creation, and reflexive control. Reflexivity is not a given, but socially constructed by evolving communication systems and cultural settings.
No doubt, the triple helix is a driver of complexity. All the more so is quadruple helix governance with the wide participation of users and multi-actor decision-making. The evolution of technologies and the case study discussed earlier reveal that strong drivers of complexity are also the innovation push created by initiatives launched by global organizations, bottom-up innovation introducing applications and e-services, and the changing urban behavior of users due to real-time information and participation through social media. Cities take advantage of initiatives, partnerships, and policy frameworks at regional and national levels also, which evolve over time, appear as windows of opportunity, and disappear after a while to give way to other opportunities. At a regional level, for instance, the search for investment opportunities is expressed by the concept of “entrepreneurial discovery” in the context of smart specialization strategies, which is to define a policy mix and actions through a process of discovery and innovation driven by the engagement of companies, closer to “choosing races and placing bets” rather than “picking the winners” (Landabaso, 2014; McCann, 2015).