Chapter 8Territorial adaptation mechanisms in AskingCities

There are not mandatory, but highly valuable and at times essential, elements that a city can deploy when local conditions require and allow them. These elements, which we will call options, do not alter the core of the model, but allow its impact to be adapted according to what each city needs or can sustain.

Options serve three key functions. First, they customize and expand the operational landscape: they allow the incorporation of additional practices that add value without being mandatory to the core of the model. Secondly, they facilitate cultural adaptation, allowing AskingCities to breathe the local air and adopt the languages, sensibilities and styles of each city. And thirdly, they allow for a gradual deployment through which, in early phases, they can be omitted to maintain focus, and in advanced phases they can become levers of sophistication, growth, or specialization.

8.1Optional Action Types #

Although the options can take very different forms, they are usually grouped into four large families (see Table 3). Leadership and legitimacy options are useful for cities that require recognizable figures capable of connecting different worlds or providing initial trust—for example, identifying a AskingCities champion or create a small group of ambassadors aligned with the model's narrative. Options for narrative deepening, typical of cities with a strong communicative culture, can include the development of documentary series, podcasts on Quick wins, periodic columns, collaborations with communication schools or student-driven narrative clubs.

In some university contexts, professionalisation and knowledge options appear, such as areas of applied research and urban observatories, graduate or master theses linked to the model or advanced qualitative reports that generate academic legitimacy and sustainability. Finally, some cities activate operational structure options: light technological platforms, qualitative analysis systems, coworking microspaces, rotating teams of AskAuthors or pedagogical artifacts that systematize learning and allow AskingCities to gain depth without losing lightness.

To activate an option, AskingCities uses clear criteria. The first is local relevance: if an option does not respond to a real need of the territory, it should not be activated. The second is installed capacity: it only makes sense to implement an option when there are people or institutions capable of sustaining it over time. The third is the effort-benefit ratio, since an option must generate real impact without overcomplication. The fourth is consistency with the dominant strategy of the moment, given that the options must reinforce, not dilute. And the fifth is timing: an option can be excellent in itself, but be out of time; at AskingCities, getting the timing right is just as important as getting the idea right.

8.2Impact and risks of options#

The options scale with the city through four phases of maturity. On boot (MVAC, see Chapter 10), the options are used very sparingly because the focus is on doing, not complicating. In consolidation, tactical options are activated that reinforce strategies already underway. In the growth phase, the options allow expansion of the network, deepening the model and diversifying and strengthening connections. In the systemic maturity phase, the options become laboratories of innovation: tools to experiment, refine and contribute to the global movement with new proposals.

However, options also come with a risk: confusing a powerful option with a mandatory element. Not all cities need advanced research, visible champions or university supply chain, and forcing them to activate these elements only introduces unnecessary complexity. AskingCities equilibrium demands that strategies remain stable, actions are teachable, and options remain optional.

Finally, options play a crucial role that often goes unnoticed: they are the global laboratory of movement. Every city that activates an option is experimenting; Each successful experiment becomes learning, replicable practice, or an input that helps evolve the model's architecture. AskingCities is not only replicated, but evolves, and it does so in a distributed way, because each AskingCity contributes something valuable to the future of the movement.