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JRC116076

EUR 29736 EN

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How to cite this report: Larrea Miren, Estensoro Miren, Pertoldi Martina, Multilevel governance for Smart Specialisation: basic pillars for its construction, EUR 29736 EN, Luxembourg: Publications Office of the European Union, 2019, ISBN 978-92-76-02922-9, doi:10.2760/425579, JRC116076.

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Multilevel governance for Smart Specialisation: basic pillars for its construction

Foreword

This JRC Technical Report has been developed under the umbrella of the Knowledge Centre for Territorial Policies (KCTP) of the European Commission, which supports better knowledge management for sound EU policy making. To strengthen the Commission’s overall support to territorial development, the KCTP brings together and provides access to platforms and tools on territorial and regional related issues.

The Smart Specialisation Platform (S3P) of the Joint Research Centre (JRC) supports the overall objectives of the KCTP, with a focus on innovation policy.

The KCTP also hosts the outcomes of the JRC research project “Support knowledge management of EU measures for integrated urban and territorial development (URBADEV)” concerning the analysis of Sustainable Urban Development (SUD) and Integrated Territorial Investment (ITI) strategies currently implemented across Europe within Cohesion Policy 2014-2020. URBADEV has largely contributed to the development of this Technical Report.

Acknowledgements

The authors would like to thank all the participants of the Peer eXchange and Learning (PXL) workshop on Multi-level Governance for Smart Specialisation organised by the Basque Government, Orkestra-Basque Institute of Competitiveness and the European Commission’s Joint Research Centre, which was held in Bilbao on 12 April 2018. During the PXL workshop experiences from the Basque Country, Finland and Flanders were discussed.

Special thanks go to Bilbao Ekintza and the Bilbao City Council, who kindly hosted the workshop.

Miren Larrea and Miren Estensoro (co-authors) gratefully acknowledge financial support from the Basque Government for the drawing up of this Report.

Authors

Miren Larrea, Orkestra-Basque Institute of Competitiveness, University of Deusto

Miren Estensoro, Orkestra-Basque Institute of Competitiveness, University of Deusto

Martina Pertoldi, European Commission, Joint Research Centre (JRC)

Abstract

The aim of this Report is to help policy makers working in different government levels involved in Smart Specialisation (S3) processes to understand how multilevel governance operates in their context and also how they can develop and facilitate its construction in their S3 strategies. The motivation behind this study is the belief that multilevel governance (MLG) can be improved and that S3 can be made more efficient with a win-win approach for different governments involved in the process. In order to begin this reflection, we first define the concept of multilevel governance, connect it to other relevant concepts regarding S3 and explain the place-based and experimental nature of multilevel governance, highlighting its complexity as one of its main characteristics. After describing the government levels that are actually in charge of S3 strategies under the umbrella of the European Commission, the brief focuses on its main contribution: the definition of four pillars for the construction of multilevel governance of place-based S3 strategies. We defined these pillars to help understand how multilevel governance can be built. For each of the pillars, one example linked to the Basque cases is described, together with another example from a different context, i.e. the Six City strategy in Finland, the regions of Flanders in Belgium, Extremadura in Spain, and Baden-Württemberg in Germany.

1 Introduction

The Report targets policy makers willing to better understand how multilevel governance (MLG) can be developed in the context of S3 strategies. Today the governance of S3 strategies, and thus MLG, is both a challenge and an opportunity. It represents a challenge because the lack of adequate structures, the distribution of responsibilities and shared visions can influence the effectiveness of its implementation. But at the same time it is an opportunity because the novel arrangements recently promoted by Smart Specialisation with regards to R&I policies in many regions and countries will be helpful for a wider set of territorial development policies. In short, investing in MLG for S3 strategies will be beneficial not only for S3, but also for a broad range of new-generation policies.

Here, we share conceptual and practical insights into how to efficiently develop MLG for Smart Specialisation, so that it will enhance the impact of the design and implementation efforts made by regional and national governments. This issue affects a wide variety of policy makers in institutions and organisations at different levels which play a role in S3 implementation.

We are aware, however, that the acknowledgement of the relevance of MLG for S3 varies across governments. The diversity of positions multiplies when we consider not only regional and national governments, but also sub-regional governments. Although the framework shared in this Report is most appropriate for the requirements of governments which have previously shown willingness to use a multilevel approach and find it difficult to put this idea into practice, we consider that it could also be useful for governments without such an explicit aim. These governments could, through this document, gain awareness of the potential of MLG for S3.

The proposal of MLG lies at the core of the EU 2020 strategy (2010) which clearly underlines the need to establish "a permanent dialogue between various levels of government" and to extend partnership approaches to "national, local and regional authorities, to social partners and to stakeholders and civil society" (EC, 2010: 29). The contribution of MLG to the effectiveness and legitimacy of EU policymaking has been made explicit within several reports and official documents of European institutions and also within the S3 framework (Metis GmbH and EPRC, 2014; Spatial Foresight, 2015; EP, 2016; Gianelle et al., 2016; van der Brande, 2017; EUA, 2018). This issue has not yet gained the same relevance in the academia as it has in the policy arena, but there is nevertheless an incipient set of literature that focuses on the issue, specifically on the role of sub-regional government levels in S3 processes (Estensoro and Larrea, 2016; van Straalen and Witte, 2018).

Although the main aim of the brief is to help policy makers reflect on this issue, MLG for Smart Specialisation is also an emergent issue from the theoretical perspective. This briefing paper contributes to this field by addressing how R&I policies can be designed and operationalised under the framework of EU Regional Policy, which has become a vehicle for an increasingly spatially targeted form of innovation policy (Morgan, 2017). More specifically, this Report further extends the existing literature by focusing on how MLG can be developed. By doing so, it connects with the question of "What is the right space for the deployment of a smart specialisation strategy?" (Foray, 2014). Our answer is that there are different spaces for S3 which are connected to the re-shaping and restructuring of S3 communities. We propose MLG as a strategy to make different spaces work together.

Finally, in order to help policy makers reflect not only from a theoretical perspective, but also from a practical one, the brief is based on various cases from which different lessons can be learnt. In this brief, MLG is presented as a complex process and the practical examples used here illustrate this complexity.

The structure of the brief is as follows. The next section addresses the "whys" and "wherefores" of MLG when implementing S3, while in section 3 we frame our approach to MLG as place-based and experimental. In section 4 we discuss the different government levels that we analyse in the framework of MLG and the role they play in S3. The fifth section describes the main contribution of the brief, i.e. the pillars that sustain the construction process of multi-level governance for the implementation of S3. We use examples from the Basque Country (Spain), Finland, Flanders (Belgium), Extremadura (Spain) and Baden-Württemberg (Germany) to define these pillars. Finally, section 6 presents the concluding remarks.

2 What is multilevel governance and why can it help implementing S3?

Different authors and organizations have approached and defined MLG from various perspectives but they all share certain common features. Generally, MLG is understood as the participation of many different types of actors (public/private) in the development and implementation of policies through both formal and informal means (Metis and EPRC, 2014).

Schmitter (2004: 72) defines MLG as “an arrangement for making binding decisions which engages a multiplicity of politically independent but otherwise interdependent actors – private and public –at different levels of territorial aggregation in more-or-less continuous negotiation /deliberation/implementation, and that does not assign exclusive policy competence or assert a stable hierarchy of political authority to any of these levels”.

Accordingly, the EU discourse on MLG has also begun to more explicitly use less hierarchical and more network-like structures, with MLG describing "collective decision-making processes where authority and influence are shared between stakeholders operating at multiple levels of governance and in different policy sectors" (Spatial Foresight, 2015: 4).

The new governance of innovation policies boosted by S3 has led to the rethinking of the coordination/collaboration among the EC, national and regional governments. But MLG does not exclusively refer to vertical relationships, as horizontal relationships are at the core of the justification of MLG. In fact, developments in governance studies on the concept of MLG in the EU context distance from the initial focus on nested governments at different territorial tiers (Marks, 1993) and recognise coexistence and overlapping of two types of MLG (Hooghe and Marks, 2001), namely Type 1 MLG (vertical, with hierarchical and geographical defined jurisdictions, limited in number) and Type 2 MLG (horizontal, with task-specific multiple and more fluid jurisdictions). This is even more important for S3 policies since they are based on a Quadruple Helix model and require a horizontal integration of different types of entrepreneurial actors including representatives from firms, technology centres, universities and other organizations which produce potentially useful knowledge for S3 processes.

S3 requires interaction and the capability of national and even regional governments can be limited when it comes to directly interacting with such actors. By involving sub-regional government levels in S3 strategies, the capacity of these strategies to involve entrepreneurial actors is multiplied. Consequently, the main rationale behind this Report is that national or regional governments in charge of S3 strategies can develop them more efficiently when they collaborate with sub-regional governments. National or regional governments might have the competences for S3, but often lack the capacity to be present in many of the spaces where opportunities for Smart Specialisation can be found. This limitation is even more evident when governmental institutions try to involve SMEs or society in S3, as these types of actors do not usually participate in entrepreneurial discovery processes activated within S3. This raises a question about the role of municipalities, which includes city, council, provincial and other government levels in S3. We understand this dimension not as an independent one, but rather as one that is closely intertwined with horizontal networks for S3 as different levels of government can create horizontal relationships in different levels which can be complementary.

Following this argument, we believe that MLG includes a wide variety of actors, but that the S3 policy framework assigns a crucial role to governments. It is for this reason that when presenting the whys and wherefores of MLG, we explicitly focus on the role of governments at different levels of territorial aggregation. It is important first to acknowledge the plural and multi-scalar nature of governance, to be able to then to tackle the interaction of different levels in S3 implementation. Regarding this point, Barca (2009: 41) defines MLG as "a system in which the responsibility for policy design and implementation is distributed between different levels of government and special-purpose local institutions (private associations, joint local authority bodies, cooperation across national borders, public-private partnerships and so on)". Moreover, Serbanica and Constatin (2017: 3) underline that MLG contributes to integrating the different policies, projects and proposals of different government tiers, so that each of them is considered in relation to one another and thus synergies among them can be created.

As a result of the previously described features, MLG can help unlock the growth potential of the territories where it is implemented. The rationale behind this is that, inspired by place-based approaches, S3 strategies can be developed potentially everywhere, but that it is through the collaboration of different government levels that the specific potential of each place can be best known (those governments with contextual knowledge of each area) and enhanced (those governments with better knowledge of programmes and codified knowledge on S3).

In the context of this brief we define MLG as:

a complex process of collaboration among different levels of governments and public bodies with the aim of making Smart Specialisation Strategies available to other actors (explicitly targeting those actors from production and knowledge systems and communities) simultaneously on various levels.

Taking this perspective into account, we consider that MLG can help apply the structuring principles of S3 (Foray and Goenaga, 2013), specifically in respect to:

• Granularity level. MLG arrangements can help capturing the relevant scale for new activities in-between the regional structural logic and individual innovation instead of sectoral support, and at the same time can facilitate linking priority S3 strategies with simultaneous complementary investments (e.g. S3-tailored training schemes or talent attraction programmes promoted by local development agencies).

• Entrepreneurial discovery processes (EDP) require that governments act as platforms to enable, sustain and guide stakeholders’ participation across the different stages of the policy-making process. Local governments could enable such platforms by activating and animating local "catchment areas" for the purpose of obtaining relevant prospects and insights to benefit the wider S3 EDP. In addition, MLG arrangements can help improve the identification of local assets, the integration of knowledge, and the chances of finding potential opportunities for specialisation thanks to more focused goals and proximity.

• The experimental nature of S3 places particular emphasis on monitoring, evaluation and learning. Here, MLG can help to establish meaningful goals and metrics, to extend too aggregated statistical data with empirical data, improve access to information, and foster mutual learning locally and regionally by reaching out to different stakeholders during the different stages of policy implementation thanks to targeted communication.

It does seem clear, however, that nowadays when S3 has to face the challenges of implementation, MLG is emerging strongly. What we propose in this brief is that MLG for S3 should not be interpreted as simply coordinating different government levels but rather as a process of co-creation of strategies. Issues of conflict and power which are inherent in this perspective are addressed by Marques and Morgan (2018: 12) when they state that MLG means “to strike a judicious balance between central control and local ownership of cohesion policy projects”.

3 Characterizing multilevel governance as a placed-based and experimental process

Regarding the experience of S3 implementation, we have learnt two lessons that help to better understand the interpretation of MLG in this brief: the relevance of embracing place-based approaches within smart specialisation, and the opportunity arising in it to develop experimental processes. We discuss both lessons in this section.

There are different perspectives on whether the placed-based dimension was or not at the core of Smart Specialisation and its Strategies in their inception. McCann and Ortega-Argilés (2014) note that when the concept of Smart Specialisation emerged in the Knowledge for Growth expert group, no explicit geographical or territorial dimension was included in the concept. This was taken into consideration later when the implementation process started. Aranguren et al. (2017) reinforce this argument and remind us that traditionally MLG has not been a central concern in debates on S3, resulting in a lack of recognition of its role in the different territorial levels required for a coherent regional strategy (Aranguren et al., 2017: 168). Meanwhile, Morgan (2017) argues that S3 was originally conceived as a multi-scalar endeavour in which supra-national, national and sub-national institutions were required to collaborate for mutually beneficial ends.

Barca (2009) proposes that regions and localities should design place-based policies, which not only target the specific needs of each territory, but also draw on the knowledge and skills concentrated in those places. Under this approach, the responsibility for policy design and implementation is distributed among different levels of government supported by both contractual relations and trust, in which special-purpose institutions, such as agencies and public-private partnerships play a specific role. In this regard, the Barca Report (2009) disentangles the relationship between the concept of subsidiarity, the general principle according to which authorities should only carry out those activities which cannot be performed effectively at a more local level, and MLG, by shifting the discussion from a separation of responsibilities in terms of policy sectors to one in terms of the tasks to be carried out, where the subsidiarity criterion should govern the allocation of tasks.

These two features of MLG which we have underlined characterize MLG as a profoundly complex process. The question that now arises is how to face the complexity inherent in the place-based MLG approach that we present in this Report. Work methods for MLG require significant capacity building (Sotarauta, 2018) and developing an experimentalist culture (Foray, 2017). Radosevic et al. (2017) suggest that S3 is a strategic attempt by the EU to strengthen ‘experimental governance’, thus pushing for a change in the way knowledge is gained for the public management of Smart Specialisation. The experimental approach to governance (or MLG within this Report) describes the emergence of policy as a process based on a recursive learning mechanism and dynamic accountability through peer review (Sabel and Zeitlin, 2012). This means that policy makers recognize their limited knowledge of the implementation context and define policy objectives through an iterative process in cooperation with agents. In parallel to this is the emergence of S3 experiences at a local level, which represents an opportunity for applying more fine-grained practical approaches to local issues (Aranguren et al., 2016).

4 Territorial levels of Smart Specialisation strategies

In this section we focus on the different territorial levels at which S3 strategies are developed. Our aim is to illustrate the great diversity of approaches used by Member States in order to understand the complexity of many different levels interacting with each other. This helps to conceptualize the discussion of MLG and its complexity.

First we present the three categories in Table 1 where we show the government levels which are responsible for the development of S3 in each of the Member States. It should be kept in mind, however, that this classification could change given that S3 is a dynamic process. More information, including the government levels involved in S3 in each of the Member States, are presented in Annex1.

Table1.  Territorial level responsible for the development of S3 in each Member State

Government level responsible for the development of S3 | Member State
Only national | Bulgaria, Croatia, Cyprus, Estonia, Hungary, Ireland, Lithuania, Latvia, Luxembourg, Malta, Slovakia, Slovenia
Only regional | Belgium, Denmark, Finland, France, Netherlands, United Kingdom
Both national and regional | Austria, Czech Republic, Germany, Greece, Italy, Poland, Portugal, Romania, Spain, Sweden

Source: Compiled by authors on the basis of information gathered from the S3Platform (2018).

In total, over 200 Smart Specialisation Strategies have been designed at EU level, both national and regional. Twelve out of the 28 Member States (MS) have exclusively national strategies, where governments at other levels have no formal responsibility for strategies. In contrast, there are six MSs which have decided to develop exclusively regional strategies. This does not mean that there is no interaction with other levels of government, but that the formal responsibility for strategy design lies with the regional governments. The rest of MSs (10) have opted for a shared responsibility, combining national and regional strategies. The analysis of this category shows that there are differences in strategies regarding how they combine responsibility of different government levels. Nevertheless, some patterns can be observed.

The degree of autonomy and competences of regional governments influences the decision as to whether this level will be involved or not in leading the S3 strategy. In this respect, the pattern we observe is that MSs which exclusively rely on their regional governments for the development of S3 strategies (6), or have both national and regional strategies (10), are countries whose regional or other sub-regional governments have more autonomy, power and competences in economic development compared to MSs with only national strategies (see Annex 1). The exceptions are Croatia and Ireland which only count on one national strategy of Smart Specialisation, although Croatian counties and Irish regions do have competence in economic development.

Furthermore, the regions’ size also seems to influence the decision of which government level leads the S3 process. If we use population as an indicator of size to analyse this feature, we realise that in those countries where regions take the lead in S3 strategies, the average population of such regions is higher than that of regions of MSs where the responsibility for S3 is shared between national and regional governments, and similar to countries where the responsibility is only at a national level. This is consistent enough to be considered as a second pattern.

Another dimension that influences the decisions related to multilevel governance is the number of administrative levels inside MSs. On the one hand, those MS that have regions involved in S3 strategies, either alone or collaborating with the national government, often have three levels of sub-national governments, i.e. the regional level, the municipal level and a third one which is between the regional and municipal (see Annex 1). On the other hand, MSs who only develop national S3 strategies have one or two levels of sub-national divisions with the exception of Ireland. This can be considered as a third pattern.

Finally, while national and regional governments assume varying responsibility for S3 strategy development, formal responsibility of these strategies is never shared by sub-regional governments, which is a fourth consistent pattern. This might be due to the fact that these spaces are smaller and, consequently, have less critical mass as well as fewer competences and thus, this finding can be considered natural in a way. However, several experiences in the EU have shown that sub-regional administrations can play a relevant role in S3 strategies. This is especially the case, albeit not exclusively, with cities. And it is precisely for this reason that, in addition to the national and regional levels, we include sub-regional levels as potential actors in S3 multilevel strategies.

The previous reflections help us understand part of the complexity of multilevel approaches. There is no particular recipe for this approach, nor is there one size that fits all as the combination of levels involved in the process depends at least on the size of MS and regions, the number of existing levels and the autonomy of regional governments. The purpose of the rest of the ideas shared in this Report is not to describe an ideal MLG approach which every MS should try to embrace, but quite the opposite. What we propose are four pillars that we consider useful for the rethinking of S3 governance. The exact meaning of each pillar in each case will be defined by the policy makers in charge of the strategy for each context.

5 The four pillars of multi-level governance for place-based Smart Specialisation

This section illustrates the main pillars for the construction of multi-level governance shown in Figure 1 for the implementation of S3¹.

Figure 3. Pillars of MLG for S3

Each of the following sections presents one pillar, shares a reflection on how to construct it and gives two examples. One of the pairs of examples is based on the Basque case while the others refer to Finland’s Six City Strategy, the Integrated Territorial Investment (ITI) strategies developed in Flanders (Belgium), the case of the CLLD Local Action Group TAGUS in Extremadura (Spain) and the S3 strategy of the German region of Baden-Württemberg.

5.1 First pillar: complexity

5.1.1 Understanding complexity

The academic discourse on S3 often focuses on regional governments. But in the previous sections we have shown that the practice of S3 frequently includes sub-regional, national and also, of course, European government bodies. Complexity results from their interactions when developing place-specific strategies.

But what is complexity? There are many different definitions of complexity. In this brief we use a definition of territorial complexity taken from Karlsen and Larrea (2014) and adapt it to MLG. From this perspective, complexity in MLG is described as a situation where there are multiple governments (national and regional governments, city councils, county administrations, etc.) which are autonomous but interdependent, and which might have different perspectives on what the problems of innovation, S3 and MLG are and what the solutions might be; none of them, however, has a hierarchical power to instruct the others on what to do. This is not the only definition of complexity, nor does it consider all its dimensions, but we use it because we consider it underlines the fundamental dimensions of political and policy practices.

Thus, multilevel governance for S3 is complex not only on account of there being many actors. If they all agreed on their interpretation of the situation and all had the same interests, there would be no complexity. MLG is complex because different government levels have different perspectives on S3 related issues, and this makes collaboration more difficult.

5.1.2 Facing complexity

If complexity is a feature of MLG, what can be done to face it? The main argument we share in this section is related to changing the methodological approaches that policy makers use to solve policy problems.

In short, the most widespread method for strategy making is that proposed by the "planning school", which according to Mintzberg et al. (1998) proposes a linear approach to solving problems. This means that first policy makers analyse the problem, gather information about related issues, make decisions and afterwards dedicate their time to implementing what was planned. If different government levels work with this method, and there is complexity, then certain strategies will collide.

In this Report we argue that linear approaches like the planning one are not sufficient and need to be complemented by others. More specifically, we propose to focus on learning and power too. The main difference with respect to the planning approach is that they are emergent processes. When following the planning school policy makers start taking action once they have made the decision on what to do, in emergent strategies this decision will be made along the way. The “learning school” interprets the concept of strategy as a learning process based on practice. Thus, governments start taking action and adapt their strategy through learning mechanisms. The "power school" considers the strategy development process as one of negotiation. The different actors involved in the process use their power to try to influence the process in the direction they consider to be right. The strategy emerges, in this perspective, from negotiation between the different parties regarding what should be done.

One of the main challenges of MLG is that the governments involved have different capacities and willingness. If learning and negotiation are interpreted as processes that take place in the middle and long term then, as suggested by the approach in this brief, these governments can be integrated into the process slowly, i.e. step by step, and adapting each step to their capacities and willingness.

Although learning and negotiation within a place-based approach require the involvement of the participants of each territory, this does not mean there is no role in the process for external agents, which can be useful by bringing new knowledge into the process as well as by mediating between the different governments in a negotiation process.

How can policy makers face the challenge of complexity in MLG? Bearing in mind the previous arguments, we propose that the following could be helpful:

a) Seeing government plans as an important part, but not the whole strategy.

b) Experimenting with processes where different government levels learn together about S3 and guiding shared learning towards shared decision-making.

c) Creating mechanisms for negotiation, based on shared learning processes. Only this way will it be possible to prioritize decisions based on shared learning.

When proposing negotiation, we assume that there is already a shared framework which establishes certain boundaries for negotiation. Without this framework, the negotiation process might serve only the interests of the different parties but not those of the S3 process. Usually, shared approaches to innovation policies which include S3 provide a framework for this type of negotiation. In the absence of a shared framework, it would be important to first take some time to agree on one.

5.1.3 Examples of complexity

In this section we provide two examples of how complexity can arise in MLG of S3 and how efforts can be made to create the shared learning and negotiation spaces and processes.

Example 1: Basque Country

The institutional organization of the Basque Country is constituted by four administrative levels and three government levels: the regional government with core competences in industrial and science, technology and innovation policies; three Provincial Councils with complementary competences focusing on innovation and economic development and collecting taxes; the county level which has no government but has development agencies created by municipalities; and municipalities and cities whose competences for territorial development are recognized, though generally they have a very limited budget for innovation policies.

Each of the sub-regional governments has considered, to a greater or lesser extent, S3 to provide a framework for their economic development policies. One example of the complexity of multilevel strategies is the case of Bilbao. The priorities set by this city in 2014 were different from the ones established by the Basque Government’s strategy. To overcome the complexity an internal debate in the Bilbao City Council took place, where members of the Basque Government occasionally contributed to the process. Thus, the focus was placed on the urban priorities. They established three (out of the initial six) priority areas which had synergies with the strategy of the Basque Government: Cultural and Creative Industries, Advanced Services for Industry 4.0 and Digital Economy.

Example 2: The Finnish Six City Strategy for sustainable urban development

In Finland, the S3 approach is embedded in the regional strategic programmes overseen by Regional Councils, and coordinated at national level by the central government. In addition, Smart Specialisation is implemented also through a specific national city-led scheme called Six City Strategy that combines regional innovation strategies with broader urban development objectives at city level. The Six City Strategy approach is very ambitious and is based on the development of a city network made up of the six largest cities in Finland (Helsinki, Espoo, Vantaa, Tampere, Turku, and Oulu).

Conflict management has been explicitly addressed in the definition of the strategy governance system since its inception. City participation in the strategy is approved by city councils and progress is presented to the city decision-makers and the Regional Management Committees on a regular basis. Moreover, the highest decision-making body is the Six City's joint management group, which consists of the directors of the local development agencies of each city. In addition to the six city representatives, the steering group includes representatives from national and regional bodies with competences in R&I policies.

The Six City Strategy has reinforced cooperation among cities as well as between regions and cities, while an Entrepreneurial Discovery Process (EDP) at local level has strengthened the involvement of local stakeholders.

However, cities still act as competitors amongst themselves, as they have different development cultures and strategic orientations which do not always fit in with the overall national strategy, and are reluctant to become part of it. Current efforts in the implementation phase of the Six City Strategy, and more specifically for the Spearheads projects that must be carried out by at least two cities together, aim to improve communication in order to ensure that all the different organisations involved understand the added value of the cooperative model, and are committed to achieving the S3 objectives at city level while also meeting the overall national objectives.

5.2 Second pillar: emergence

5.2.1 Understanding emergence

The idea of emergence appeared in the previous section when we argued that planning must be complemented with emergent strategies based on learning and negotiation.

Accepting that the process to construct MLG is emergent means accepting that policy makers do not know what the expected outcome of their S3 strategy is. The fact that it is impossible for them to know what the result of the learning and negotiation process will be until they are actually learning and negotiating is not easy for policy makers as they are often pressurised to clearly explain what the expected outcomes of policies are.

S3 policies are good candidates for emergent policies because EDPs, which first require developing such a discovery process, make it difficult to know beforehand exactly what results the process will lead to.

5.2.2 Developing emergent strategies

The key element when developing emergent strategies is to understand that emergence is not a kind of laissez-faire, or a synonym for improvisation. In the case of emergence based on learning and negotiation, as proposed in this Report, spaces and procedures to learn and negotiate must be established in an active and sustainable way, i.e. through facilitation (Costamagna and Larrea, 2018). Those in charge of facilitation are the facilitative actors, who are territorial actors (policy makers, firm managers, researchers, etc.) that create the conditions for other actors to reflect, decide and act. For emergent policies to work properly, they require strong networks of facilitative actors. Taking this into account, we listed below some elements which can help reflect on the pillar of emergence:

a) The development of emergent strategies is difficult because the mainstream tradition for many governments has been that planning and emergent strategies might make governments look “weak”.

b) In order to make emergent strategies feasible, new approaches to inform of these strategies must be developed. In addition to goals and budgets, which are usually communicated, learning and negotiation spaces and procedures are part of these types of strategies.

c) It is important to identify and train facilitators in order to help them ease the processes in a more visible and coordinated way.

5.2.3 Examples of emergent strategies

Example 1: The Territorial Development Laboratory of Etorkizuna Eraikiz, Gipuzkoa, Basque Country

In Gipuzkoa, the Territorial Development Laboratory ‘Etorkizuna Eraikiz’ (TDLab) integrates an action research process initiated in 2009 with the aim of fostering competitiveness and territorial development. The provincial government invited researchers to participate with them in an action research process to construct a new MLG that would create a space for the provincial council (province government) and county development agencies to define and implement territorial development policies in collaboration.

In 2018, the MLG which was constructed through participatory spaces, where the council, county development agencies and researchers met, made it possible to integrate 404 SMEs in a project with the aim of helping them evolve into Industry 4.0. The council recognised its limitations regarding involving SMEs in previous innovation programmes, and decided that county agencies would act as proximity agents in the delivery phases of their new policies. In the first phase, agencies made a diagnosis of the Industry 4.0 transition challenges of the 404 SMEs through a methodology co-constructed together with researchers within the TDLab. In the second phase, based on the results of that diagnosis, the process focused on a group of 42 SMEs whose Industry 4.0 implementation process was overseen by both the provincial council and the agencies.

This process was emergent because the decision to focus on a specific group of SMEs and the rest of the features of the new program were not defined from the beginning, but were the result of a learning process experienced by policy makers and researchers together with firms. What this means is that policy design was taking place throughout the implementation phase, during which policy makers and researchers detected the need to face a conflictive issue: the limitations of the county development agencies when helping SMEs in Industry 4.0 transition. This discussion and the corresponding co-definition of the role of agencies was a key step for the sustainability of the process and was not defined beforehand, but emerged during the process. This is another example of how the construction of MLG can be considered an emergent process.

Example 2: Integrated Territorial Investment strategies addressing R&I in Flanders (Belgium)

Smart Specialisation is managed by the Flanders Innovation & Entrepreneurship agency (VLAIO) and involves a set of dynamic activities dealing with strategic funding, international networking, interregional collaboration in Smart Specialisation areas, and progressive adjustment of the policy mix to contexts through test and demonstration activities and support in the later stages of innovation. Accordingly, S3 in Flanders is defined along the process, bringing together different agendas instead of developing an overall strategic plan. This has given policy makers at sub-regional level a chance to play a role in the process, thanks to the implementation of Integrated Territorial Investment (ITI) strategies for the economic conversion of three specific sub-regions. These strategies have their own S3 agendas that take into account the specific socio-economic and territorial characteristics of these areas, following the Triple Helix approach used by regional innovation clusters but with an explicit territorial focus.

Whereas the specific projects are managed by provincial and local authorities, whose specialisation strategies form the basis of the sub-regional programmes, higher government levels places them in a wider perspective, with different and complementary goals.

At the same time, some tensions can be seen between the opportunity for bottom-up flexibility and the result orientation of the regional programme. Also, the coordination between the ERDF and ESF programmes has proven difficult, requiring extra management and specific capacity.

With regards to the ITI West Flanders, the set-up of a steering group for the management of the sub-regional projects, involving the Flemish Government, the provincial government of West-Flanders, local authorities, universities, employers’ organizations and the ERDF Managing Authority, has provided a first step for the creation of a facilitating space where different instances can be accommodated and worked out thanks to more informal and less codified practices. The ITI has not only contributed to increased cooperation between public actors across government levels, but has also increase coherence between the single projects due to the link with the regional strategy.

5.3 Third pillar: context specificity

5.3.1 Understanding context specificity

The fourth pillar that sustains MLG in S3 is context specificity, which means that S3 strategies and their MLG arrangements have to be carried out differently in every place. Actors in every territory find solutions tailored for the contextual solutions of every place. Some contextual conditions can be relatively easy to detect, such as the size of countries and regions, their central or peripheral position, their classification as advanced or lagging territories or even the density of their regional innovation system. But there are other circumstances which we could describe as “soft” contextual conditions and which are more difficult to detect or diagnose and play a critical role. These conditions are related to capabilities, defined as the power or the ability to do something.

The different soft capabilities can be brought together into one concept: collective knowing (Karlsen and Larrea, 2014), which is a learnt pattern through collective action or to put it more simply, it is the capability of the actors in one place to solve their problems together.

With this concept we want to underline three ideas. First, in MLG, the most relevant factor is not what each government level has the power and ability to do on its own. Although this aspect is important, what is specific of each context in terms of MLG is, in fact, what all the different governments have the power and the ability to do together. Secondly, knowing means knowledge in action. The specificity of each place cannot be found in the stock of knowledge formed by documents, plans, and papers describing, analysing, interpreting, or proposing how to carry out MLG in each place. Specificity in terms of MLG lies in the concrete actions, which do not always correspond with what is written on paper. Last, but not least, this capability is a learnt pattern, i.e., it can be developed through learning together.

5.3.2 Facing context specificity through the construction of collective knowing

Different governments involved in MLG of S3 strategies can decide to facilitate the process of constructing collective knowing on their own. However, they often receive help from consultants or researchers. In these cases it is important to take into account that not any consultancy or research method will do when collective knowing by means of emergent strategies is needed to be able to face complex problems. This means that consultants and universities need to be part of the construction of collective knowing and develop their methodologies in an emergent manner when facing the complexity of each place. In short, there is no “one size fits all” methodology to support S3 strategies.

In these cases governments should consider the following principles:

a) The construction of collective knowing in each context requires the participation of members of all government levels involved in MLG, and those who do not participate do not share the capability, no matter how well others can “inform” them about it.

b) Consequently, researchers and consultants can help construct collective knowing, but only through participatory methodologies where they are part of the process as another actor who can learn. Methodologies which aim to first create knowledge outside the context of application and then transfer it to the context of application do not work. For this reason, researchers and consultants cannot construct collective knowing for different governments involved in MLG but can only construct it with them.

c) The type of facilitation to construct collective knowing is also context specific, with no general formula for how governmental actors should learn and negotiate.

5.3.3 Examples where collective knowing has been constructed

Example 1: Peer eXchange and Learning in the Basque Country

The second objective of this brief is to provide insights for policy makers into how to use research conducted in their regions to reinforce MLG in S3 strategies. This is seldom a central issue in policy agendas and it remains implicit in most reports: through this example, however, we address it in an explicit way. The Basque S3 strategy provides an example of how governments can integrate researchers in the construction of collective knowing for MLG in ways that address context specificity. The role played by researchers in this example differs from the mainstream role played by researchers in innovation and S3 policies. Researchers in the case were part of a project fostered by various stakeholders– among which were the regional government of the Basque Country, the provincial council of Gipuzkoa and the City Council of Bilbao– to create an institute specialised in transformative research. This means that policies themselves can be a relevant process to develop research capabilities as shown in the case.

In 2018, an opportunity arose for the Basque Government to collaborate with the S3 Platform in the organisation of a Peer eXchange and Learning (PXL) workshop on Multi-Level Governance. The Basque Government was in dialogue with Orkestra on this issue and the research institute was integrated into the organisation process.

Orkestra had already reflected on the fact that the institute undertook S3 related research projects with most of the government levels in the region (the Basque Government, the provincial councils of Bizkaia and Gipuzkoa, which were working on S3 with county development agencies, and the city councils of Bilbao and Vitoria-Gasteiz). Based on the relationships built because of these projects, representatives of all government levels were invited to participate in a preparatory meeting, which was held at a university, for the PXL workshop. The meeting was a dialogue space for different governments concerning their S3 strategies.

In the meeting a shared discourse regarding MLG of S3 in the Basque Country was constructed by all participants. We argue that this process became part of collective knowing (a learnt pattern of collective action) when the participants made the decision to continue meeting and learning together in this university context.

The role of researchers in constructing collective knowing was to provide concepts that helped to reflect rather than to propose how MLG should be. The shared perspective on what MLG should be was constructed in the dialogue among government representatives and facilitated by researchers. Through the learning and negotiation implicit in the construction of the shared discourse, the framework of MLG defined in the workshop included contextual conditions specific to the Basque Country. Not only the visible ones, which researchers could have incorporated on their own, but also those that we defined as “soft” and that are related to the specificities of power and capacities.

Example 2: Rural Development and Innovation in Extremadura (ES)

Researchers are, however, not the only actors who can facilitate collective knowing. Relevant lessons can be learned from cases where Smart Specialisation has been approached in the scope of community-led local development in rural areas, bringing together different policy frameworks, cultures and communities of professionals.

Although S3 is a favourable framework for innovation in rural areas (Da Rosa Pires et al., 2014), its application has proven difficult. One of the reasons for this is the need for policy makers active in both rural development and innovation policy to learn how to work together, and often to simultaneously learn how to approach challenges in different ways.

The Spanish Local Action Group (LAG) TAGUS has applied EDP to guide and support their Community-Led Local Development (CLLD) LEADER strategy, while at the same time connecting to the regional S3 strategy priorities. TAGUS initially approached Smart Specialisation independently within their local development strategy, aiming to incorporate knowledge agents into it as well as to attract new funding mainly from the ERDF and H2020 in addition to granted EARDF support. Nevertheless, the full inclusion of TAGUS in the regional S3 process was only possible once a reciprocal recognition between TAGUS and the regional R&I agency was reached, and a clear move towards coordination of actions was made. More specifically, a common space for dialogue and learning through rural development and innovation policies was facilitated by the adoption of the EDP method as part of the strategic planning of TAGUS. EDP has provided the framework to experience new collaborations, e.g. between regional research institutes and local cooperatives, and new ways of adding value to specific territorial resources, e.g. optimization of sheep management systems has become part of collective knowing. The role of TAGUS was to bring specific knowledge to the actors in the S3 process, while adding value to the existing although not yet full valorised resources, thus unlocking the growth potential of their territory through R&I activities.

Actors engaged in the process had to leave their comfort zone and adapt to something that was different for all of them. Here, learning and willingness to learn were necessary conditions of the process.

5.4 Fourth pillar: Reciprocity

5.4.1 Understanding reciprocity

The fourth pillar of MLG for S3 is reciprocity, which means that among the different governments mutual recognition of each other is necessary as a significant factor in S3 processes.

On the one hand, mutual recognition depends on the role attributed to the different types of governments. Although the literature has mostly emphasized the role of regional governments, in many countries national governments are in charge of designing and implementing S3, as we saw previously. And when it comes to the first round of design and implementation of S3 strategies, usually sub-regional governments have not been recognized as relevant actors (Estensoro and Larrea, 2016). Nonetheless, some of them have still considered S3 to provide a useful framework for their policy making and have implemented it with their own resources and without the direct guidance of the European Commission. Amid these sub-regional governments are provincial governments and agencies, inter-municipal associations and also municipalities, among which cities are starting to receive plenty of attention (Rivas, 2018).

On the other hand, mutual recognition and thus reciprocity depends on trust and, consequently, the process to attain reciprocity is basically a process where roles are defined and trust is built.

MLG is about integrating all these efforts so that the overall results in the territory in terms of EDP will benefit all. The key issue in order to achieve this is that the different levels mutually recognize each other as relevant actors. This can be especially complex in the case of regional and national governments that have already been recognized as managing authorities and see MLG as a menace to their centrality in the strategy.

5.4.2 Building on reciprocity

The main idea when aiming for reciprocity is to avoid an interpretation of MLG as a superposition of replicas of regional or national governments on a smaller scale. This means that it is important that everyone finds their own unique role in the system, without creating autarkic S3 strategies at different levels which collide instead of reinforcing each other. Reciprocity must be based on complementarity.

We have found two assumptions that can hinder complementarity. On the side of regional and national governments that are recognized as managing authorities, it is often understood that if other levels of government participate in the S3 strategy, it will be so they can help implement what the higher governments levels have already designed. That is, strategic thinking concentrates on the side of the managing authorities while the other governments are executing agents. It is important to comprehend that there is a capacity for strategic thinking at every scale.

On the side of sub-regional governments, they can easily be tempted to replicate the whole structure and procedures that the national or regional government use on a smaller scale, e.g. province, county or municipality. This would lead to the creation of multiple S3 strategies like many islands but no connections to make them work as a system.

The following are some useful ideas to achieve reciprocity:

a) Dialogue should start with an exercise of developing empathy aimed at understanding that each government has its own objective regarding strategic thinking, no matter how small their territory might be. MLG that ignores strategic thinking in any of the levels can hardly be sustainable.

b) Any government can be part of the operationalization of strategies other than their own. Sub-regional governments can often contribute with capillarity towards firms in the strategies of regional and national governments. Regional and national governments can often support sub-regional initiatives by framing them within their formal competences or through funding.

c) Going beyond reciprocity in terms of supporting each other’s strategies, as described in a) and b), by recognizing the other as the right partner to think and implement S3 together, which is the most sophisticated level of reciprocity.

5.4.3 Examples of how to build on reciprocity

Example 1: MLG based on reciprocity in the Basque Country

For this example, we return to the example described in the previous section when Orkestra participated in a meeting with different government levels about their S3 strategies. When preparing a shared narrative of MLG of S3 in the Basque Country for the PXL workshop with the S3 Platform, one of the representatives of a sub-regional government stated that they did not like the terms top and down to represent the relationships between different levels. There was a general agreement on this.

But the question was then posed by one of the researchers on how to name the strategy of the Basque Government, which was the managing authority and thus seemed to have a qualitatively different status compared to the rest. The researcher suggested it could be called the central strategy or the formal strategy. The representative of the Basque Government himself proposed the term “umbrella strategy”, which was accepted by all. In what seemed to be a simple session to prepare the presentation for the peer review and learning session, we can interpret from this example that reciprocity and mutual recognition were built on by agreeing on the terms and figures that would be used to name the MLG of S3 in the Basque Country.

Another example of reciprocity within the S3 policy making in the Basque Country is the Inter-Institutional Plan of Entrepreneurship launched by the Basque Government and the three Provincial Councils. The plan includes different topics such as culture and values for entrepreneurship, policy instruments or an ecosystem and territorial conditions that facilitate entrepreneurial activity in the territory. Reciprocity is visible in the case of the Inter-Institutional Table of Entrepreneurship composed of the four governments (regional and provincial ones) that meets twice a year in order to follow up and redefine the strategical objectives of the plan. Likewise, an operational team made up of the Basque Government and the Business Innovation Centres (BICs) belonging mainly to Provincial Councils meets every three months.

Example 2: The RegioWIN competition mechanism in Baden-Württemberg (DE)

The regional government of Baden-Württemberg (DE) initiated a two-stage competition process called RegioWIN with the aim of encouraging new stakeholders at the sub-regional level in the Smart Specialisation process to develop integrated strategic approaches in regional policy and select projects for the deployment of the regional R&I agenda.

Through this instrument, all areas in Baden-Württemberg – irrespective of how structurally strong they are – were given the opportunity to benefit from EU investments in R&I and enter the regional policy debate. Districts, cities and municipalities were motivated to bring in the relevant players from industry, science, innovation, society and administration to find innovative solutions for sustainable development. RegioWIN gave sub-regional territories extended access to instruments which are usually only available for specialists, and helped to establish strategic thinking in territories with little or scattered strategic awareness or limited collaborative spirit. All the selected lighthouse projects are already being implemented with around EUR 107 million from the ERDF and state funds earmarked at the end of 2017. The impact of the lighthouse projects, and even more importantly of the RegioWIN process itself, is considered to be crucial for the region in terms of boosting and managing regional development, following the implementation and start-up of the projects.

The policy question beneath explicitly refers to what contribution sub-regional governments can make to enhance capabilities for innovation in their respective territories, and thus improve it at the regional scale.

The starting point was the recognition that both local and sub-regional authorities have their own rights and powers, sharing responsibilities with the regional government in shaping regional development, and that they are therefore relevant for S3 strategies. We find this to be a good example for building on reciprocity.

At the beginning of the competition, there were concerns that smaller regions might find themselves facing a competitive disadvantage compared to larger regions but they eventually proved to be unfounded. On the contrary, the smaller and more homogeneous sub-regions clearly had a strategic advantage as they were able to quickly focus their goals and interests (Haberle, 2016). What this shows is that the concept of Smart Specialisation where bottom-up approaches are used can be easier for smaller spatial units to apply. It also shows the advantages in articulating those contributions within a larger policy framework, i.e. the regional S3 strategy of Baden-Württemberg.

(¹) The four pillars are based on the lessons learnt in the Basque Country through action research, a feasible method to experiment in the construction of multilevel governance (Karlsen and Larrea, 2014; Estensoro, 2015). The method focuses on continuous processes of reflection and action between policy makers and researchers.

6 Concluding remarks

The aim of this brief is to help policy makers in their endeavour to develop MLG in S3 strategies. In the initial sections of the brief we have argued that this is not something new, as multiple documents framing the development of S3 have recognised the relevance of this issue. Then why do we need this brief? Because there are few reports or briefing papers that focus specifically on how to develop MLG and there are still fewer experiences that openly present S3 as a multilevel endeavour. Thus, what we wanted to share with policy makers through this brief is reflections on how to construct MLG and examples of governments that are undertaking this endeavour.

Although we have written this brief with policy makers in mind, our objective is also to complement the existing literature on S3 and contribute to strengthening policy analysis on S3 as a place-based strategy and on MLG as a place-based concept. The relationships among different government levels which impact on a specific area vary from one place to another and MLG must be built on this specificity.

The main idea we wanted to share with policy makers is that the place-based nature of MLG means that experimentation is a necessary process for its construction, as there are no ready-made formulas or replicable recipes. Each place must learn and negotiate the specific governance that will make collaboration among different government levels possible. Nevertheless, not having any formula does not mean that there are no methodological principles that can be followed in these processes. One experimental approach that has been presented through the examples in the brief is action research. We consider it valuable because it helps develop experimental, emergent and participatory processes. The challenge is now to find other approaches that can complement this method and provide methodological learnings for the development of MLG rather than recipes. One contribution to start this reflection is from da Rosa Pires (2017) when he argues that “two quite different types of researchers can be identified schematically: those with highly specialised knowledge, and scientists with transversal knowledge and a broader perspective on the scope and the reach of a collective action at local level. Moreover, unlike traditional research projects, with which academics are well acquainted, in the case of local development projects it is not sufficient to be able to “understand” and “explain” a specific reality when, in fact, what is expected is actually to “change” reality”.

Being coherent with the place-based nature of MLG and the need for experimentation in each place, the brief does not give policy makers recommendations on what to do. However, we can transform the lessons learnt from the cases (the four pillars) into four recommendations on how to approach the process of collaboration with other government levels. These are the following:

• Face complexity in an explicit way. Remember that different governments have different interests in S3. But that does not mean anything is failing, it simply means that these differences must not be ignored but rather incorporated into the strategy.

• Do not attempt to know what the result of the process will be before you start the process. Make sure you agree on the role of every government and on the procedures for collaboration in S3. Follow these agreed rules of the game and be open minded about what you learn together and what you negotiate.

• Learn from other experiences, but do not try to replicate them. Pay special attention to the specific collective capabilities built in the relationship with other governments which have an impact on your place and contribute to S3. A good question to become aware of collective capabilities is: what type of problems did we learn to solve together?

• Make sure that the other governments you interact with recognize a place for your government and your role in S3 strategies. But do not forget to empathize and recognize a place for the other governments as well.

Reflecting on how to construct MLG for S3 requires also taking into consideration other EU policy instruments that are available at city or sub-regional level, as in the case of the Sustainable Urban Development framework applied in Finland for implementing S3 (Six City strategy) and the Integrated Territorial Investment tool used in Flanders for three territorial strategies with R&I investments. Although these EU instruments were not specifically developed under the S3 framework, they do share the same integrated and place-based approach (van der Zwet at al., 2017). Moreover, they can cover a variety of activities that could help implementing innovation policies at local level, directly including R&I in their portfolio or investing in complementary policy areas such as education, training, infrastructures and entrepreneurship.

This is the case of Bilbao, for example, where an Urban Innovative Action (UIA) for Jobs and Skills is being carried out under EU Regional Policy as a S3 project led by the Bilbao City Council. The UIA tool has provided the opportunity to explore MLG between local and regional levels with a proactive role of the city administration where other actors are also involved (leading businesses, universities, service providers, Basque industry) in this public-private strategic alliance.

EU instruments that can help develop S3 are also available in the rural development area, as is illustrated by the example of the Spanish Community-Led Local Development (CLLD) Leader strategy.

Policy makers in charge of S3 strategies need more practical examples of MLG. We hope that this brief inspires other people or institutions who have had experiences of this type to systematize and share them. For those who have not yet experimented with MLG, we hope that this Report triggers a reflection process regarding this possibility.

Annex. The role of government levels in Smart Specialisation Strategies, according to the EU legal framework

Country
Government level responsible for the development of S3 strategies
Number of S3 strategies
(Nat/Reg/Tot)
Sub-national government levels

Austria
Both national and regional
1
9
10

• Municipalities (2100)

• States/Regions (9)

Belgium
Only regional
0
3
3

• Municipalities (589)

• Provinces (10)

• Regions (3)

Bulgaria
Only national
1
0
1

• Municipalities (265)

Croatia
Only national
1
0
1

• Municipalities, towns and cities (555)

• Counties (21), including the capital city of Zagreb, which has a special dual status (municipality and county)

Cyprus
Only national
1
0
1

• Municipalities and communities (380)

Czech Republic*
Both national and regional
1
1
2

• Municipalities (6258)

• Regions (14)

Denmark
Only regional
0
3
3

• Municipalities (98)

• Regions (5)

Estonia
Only national
1
0
1

• Rural municipalities and cities (213)

Finland
Both national and regional
0
18
18

• Municipalities (313)

• Regions (18)

France**
Only regional
0
27
27

• Municipalities (36658)

• Departments (99)

• Regions (16)

Germany
Only regional
1
16
17

• Municipalities (11313)

• Counties (295)

• States/Regions (16), including three City-states

Greece
Both national and regional
1
13
14

• Municipalities (325)

• Regions (13)

Hungary
Only national
1
0
1

• Municipalities (3178)

• Counties (19)

Ireland
Only national
1
0
1

• Local authorities (126), including 31 cities and counties and 95 municipal districts

• Regions (3)

Italy
Both national and regional
1
21
22

• Municipalities (8006)

• Provinces (107), including 2 Autonomous provinces and 14 Metropolitan cities

• Regions (20)

Latvia
Only national
1
0
1

• Municipalities (119), comprising 110 Districts and 9 “Republican cities”

Lithuania
Only national
1
0
1

• Municipalities (60)

Luxembourg
Only national
1
0
1

• Municipalities (105)

Malta
Only national
1
0
1

• Local Councils (68)

Netherlands
Only regional
0
4
4

• Municipalities (390)

• Provinces (12)

Poland
Both national and regional
1
16
17

• Municipalities (2479)

• Counties (380), including 66 Urban municipalities which function as counties. The capital city of Warsaw has a special dual status (municipality and county)

• Regions (16)

Portugal
Both national and regional
1
7
8

• Municipalities (308)

• Autonomous regions (2)

Romania
Both national and regional
1
7
8

• Municipalities, towns and cities (3181)

• Counties (42), including the capital city of Bucharest, which has a special dual status (municipality and county)

Slovak Republic
Only national
1
0
1

• Municipalities (2,930), including cities, rural municipalities, city districts in Bratislava and Košice, as well as three military districts

• Regions (8)

Slovenia
Only national
1
0
1

• Municipalities (212)

Spain
Both national and regional
1
17
18

• Municipalities (8119)

• Provinces (50)

• Regions (19), including Autonomous communities (19), and Autonomous cities (2)

Sweden
Both national and regional
1
20
21

• Municipalities (290)

• Counties (21)

United Kingdom
Only regional
0
4
4

• Local authorities (389)

• Countries (4)

The territorial organisation is highly complex and differs greatly between the different countries (England, Northern Ireland, Scotland and Wales)

Total

22
186
208

* In the Czech Republic, regional strategies other than the one for Prague do not count for the fulfilment of the ex-ante conditionality.

** In France, the number of regional strategies reflects the regional structure prior to the national administrative reform introduced in 2016.

Sources: Compiled by authors on the basis of information gathered from the S3Platform (2018), CEMR (2016) and OECD (2016).

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Notes

(¹) The four pillars are based on the lessons learnt in the Basque Country through action research, a feasible method to experiment in the construction of multilevel governance (Karlsen and Larrea, 2014; Estensoro, 2015). The method focuses on continuous processes of reflection and action between policy makers and researchers.