Background

As mentioned in the introduction, the stage of REPLICATE & SCALE UP shapes the right environment for repeating the project(s) or action plan(s) at other locations, both within and outside the city’s jurisdiction, and for applying the demonstrated solutions on a wider scale through bundling of the demand in the market. Sharing of experiences and best practices is key to a further uptake and acceleration of the market for smart city solutions, as success stories build trust and help to move from consultation to agreement.  How can an environment be shaped that leads to further innovations beyond the smart city or low energy district project itself, creating a pipeline of projects? How can the uptake of successful smart city solutions be fostered, and the market for these solutions accelerated? The stage of REPLICATE & SCALE UP plays a central role in this. 

Planning for replication and scaling up

Many smart city projects demonstrate novel and innovative approaches and might be of an experimental nature. Urban living labs, testbeds, pilots, demonstration and lighthouse projects may use different methods, but all have in common that they deploy an evidence-based approach for developing results, processes, solutions and insights within a specific territorial context. These contexts are highly different from each other, as historical, spatial, political, social and economic characteristics of urban areas vary greatly, not only between cities, but also between districts and even neighbourhoods. If outcomes of such a demonstration or pilot are largely transferable to other locations and situations, the project will have a wider and more profound impact and will foster urban transitions towards sustainability and resilience. 

Thinking about replication and upscaling actions already during preparation of the plan, is very important for several reasons:

• Including specific actions preparing the ground for scaling up and replication after the project’s life into the implementation plan, can help to generate more impact beyond the project’s current scope, and facilitate urban transitions. ‘Simple’, traditional market roll-outs, aiming at widening the scale of distribution of certain technical products or solutions, do not suffice here due to the complexity of bringing about urban change. 
• Territorial characteristics and specific contexts of demonstrations or pilots, make it so that the results, solutions, experiences, processes and knowledge generated in these projects, cannot simply be “copy-and-pasted” into another place as the characteristics and contexts are different there. For that reason, the influence of territorial and context differences on the outcomes of the demonstration or pilot has to be understood, and special attention has to be paid to them, when solutions are implemented in other places and in other situations (Akrich et al., 2002);
• By analysing very early in the process which situations and solutions have a high potential for replication and upscaling, vital information becomes available that might lead to different choices made when planning the project(s) in detail. Areas where intended demonstrations can be repeated, should be identified beforehand;
• It gives the chance to anticipate specific local constraints on upscaling before the project is implemented, for example based on experiences with previous innovation projects. The question of how these constraints may be overcome can be made a part of the learning environment of the project (Dijk et al., 2018);
• Specific results of demonstrations might have significant repercussions for value chains in current business models, for example those of some participating stakeholders.

Different ways of increasing impact after the end of the demonstration or pilot

The stage of REPLICATE & SCALE UP covers various actions and processes. Often certain terms are used when talking about enhancing the impact of experiments after they are finished, and the differences between them is in many cases not entirely clear. Below these terms are briefly explained, using the report ‘Organising Smart City Projects – Lessons from Amsterdam’ (Winden, 2016) and the experiences in JPI UE project SmarterLabs, which developed and tested a novel approach to scaling up in smart mobility living lab experiments. 

Roll-Out: This term describes a rather simple commercialisation and market entry of a product, solution or technology after the demonstration or pilot. This can be a market roll-out, when an experimental solution is brought to the market, a city roll-out when the experimental solution is implementation across the city; or an organisational roll-out. The technology or solution developed in the demonstration or pilot is not context-sensitive and does not need to be adapted before rolling out. In most cases, the roll-out is managed by the organisation that initiated the experiment. 

Expansion or growth: In this case, the demonstration or pilot is being extended in the geographical area covered, or by adding more partners and possibly more capabilities. Simple roll-out is not an option here as there is limited control over the process and the involved organisations are independent.

Scaling up: The key difference between scaling-up and roll-out is that in the case of roll-out the societal context does not change, whereas in the case of upscaling wider application of the innovation also requires or goes hand-in-hand with changes in the societal (or ‘socio-institutional’) context. Hence, scaling up is not just about wider adoption of an innovation, but entails changes in various other components such as stakeholder perspectives, capabilities, business models (i.e. informal institutions), and regulation (i.e. formal institutions), in addition to the technological hardware (i.e. artefacts or infrastructure etc.). To give an example, for a case such as sustainable choices for transport modes in the city, scaling up in an urban context requires all these different components to achieve innovation. It concerns not only the technological component (vehicles, smart apps, chip cards etc.), but also social practices (e.g., travel routines) and governance practices (e.g. local mobility policies and parking regulations, contract with current mobility and parking operators, and so forth). This means that scaling up of (successful) mobility innovations from urban experiments is not a matter of simply ‘rolling out’ across the city but is tied up with processes of institutional change: new ways of doing things in existing institutions that are transformed by this. Scaling up is also related to knowledge transfer in the sense that through knowledge exchange between different experiments, new knowledge developed in a Living Lab can benefit both from local learning processes and from experiments in other places, provided they are close in terms of content and topic. Effective living labs anticipate beforehand how to scale up their impact beyond their specific location and group of participants in the experiment. 

Replication: Replicating demonstrations or pilots means that the same projects are done elsewhere. This implies that different organisations, other territories and/or other cities are involved. Replication requires taking into account the complexity of the new context in terms of geographical, legal, and organisational aspects. Therefore, the solution, technology or process needs to be adapted. Replication is complicated mainly because anchoring the original project in a new context requires active translation to this new context which supports the knowledge transfer mechanisms.