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The purpose of this paper is to show that the approaches to smart specialisation being adopted in different European Union (EU) regions are likely to be heavily shaped by the institutional and governance context, as well as the regional economic specifics. Along with the specific regional economic characteristics, these institutional variations mean that there is no single smart specialisation template or blueprint which can be transplanted onto every region. Rather, regions have to work within their own governance frameworks to find their best solutions.

As evidence of this, the authors analyse the possibilities and challenges faced by four different sets of regional examples in the UK, the Netherlands, Belgium and Spain. Using OECD, EU and other official national documents and publications, the authors are able to explain the ways in which the governance set-ups vary enormously across these different arenas although they do share some certain common features with the other examples on a case-by-case basis.

The policy architecture within which the smart specialisation agenda will be operating is very different in each national or regional case. As such, in addition to the regional economic specifics, the smart specialisation challenges faced by different regions are likely to differ significantly due to governance issues as well as variations in the regional economic conditions. This is because the possibilities for different regional actions depend heavily on the governance relationship between the regional and the local governance remits.

The argument presented here are necessarily in part speculative in that while they are based on a regional systems-of-innovation conceptual framework which links institutions, innovation and regional development, the actual smart specialisation implementation processes are still in their infancy, so that the actual outcomes remain to be seen in the long run.

The analysis here helps to situate smart specialisation discussions in the national-regional institutional and governance context. This also serves to frame how smart specialisation priority-setting processes are likely to be undertaken and helps to consider how such activities may play out in other regions with different institutional settings.

This is one of the few papers that explicitly examine specialisation issues in a governance and institutional setting. In reality, the success or otherwise of smart specialisation agenda will be heavily shaped by how the governance and institutional issues are addressed. Good analysis and data gathering is essential, but good governance for policy design, monitoring and evaluation can potentially also provide a crucial advantage to smart specialisation actions. In contrast, poor governance may undermine good smart specialisation intentions and analyses.

The purpose of this paper is to focus on the distinction between smart specialisation and smart specialisation policy and it studies under what conditions a smart specialisation policy is necessary.

A conceptual framework is built based on historical evidence of successful dynamics of structural changes at regional level qualified as “smart specialisation”. The identification of market and coordination failures that are likely to impede the occurrence of spontaneous process of smart specialisation makes a good case for a smart specialisation policy.

The paper highlights important design principles for the policy process that should help to minimise potential risks of policy failures and policy capture.

The paper does assess the effect of smart specialisation on innovation and growth at regional level because it is too early to observe and measure effects. The paper confines itself to conjectures about the effects of such a policy.

The paper makes recommendations and explains some of the practicalities about the implementation of the policy at regional level.

The paper is one of the first dealing with the topic of smart specialisation policy.

The purpose of this paper is to assess how national and regional authorities in south-east Europe in a period of crisis perceive and set in motion research and innovation strategies for smart specialisation (RIS3) and the options that these strategies offer to overcome the current fiscal and development crisis.

The paper starts with a literature review on the guiding principles of smart specialisation strategies and the differences from previous rounds of regional innovation strategies. Evidence on smart specialisation efforts is provided by cases studies in Greece, Slovenia, and Cyprus, focusing on the elaboration of such strategies in three countries with precarious innovation systems under severe conditions of crisis. The case studies are organised around key aspects of the smart specialisation logic, such as the selection of specialisation priorities, bottom-up governance, private sector leadership, and engines of innovation and competitiveness.

The paper explores the obstacles encountered in running effective RIS strategies under crisis conditions. The paper highlights the main challenges to address, such as the readiness and credibility of public authorities to design and implement sound RIS3 strategies, the willingness of companies to be involved in strategic planning, the availability of private investment funds, innovation and diversification during a crisis, and the drivers of specialisation that could lead to competitiveness and growth. In the conclusions the paper identifies three routes towards smarter productive diversification and five critical stages in the entrepreneurial discovery process.

The paper has both practical and theoretical significance. It focuses on the main challenges of smart specialisation and offers guidance in the elaboration of RIS3 in peripheral EU economies. On the other hand, it proposes a model for the entrepreneurial discovery process, based on the assessment of areas and futures of productivity and added-value increase, as productive diversification and crisis exit route.

This paper aims to understand how the different stakeholders assess the adequacy of smart specialization policies defined for their regions.

This paper has followed a quantitative methodology through the application of questionnaire surveys to stakeholders of the various territorial regions in Portugal.

As a result, from the “resource-based view” approach applied to the various regions, the attained results highlight that the suitability of smart specialization policies defined for the Portuguese regions is not unanimous among its stakeholders.

The research can be used as a tool to assist regional policymakers in strategic reflection when defining and adjusting smart specialization strategies in their territories.

The purpose of this paper is to set out the process by which a smart specialisation strategy was developed for a small, peripheral economy in the European Union, the Republic of Malta. It assesses the applicability of the approach in the context of a micro-economy with an industrial structure based on a small number of foreign direct investments and a predominance of micro-enterprises.

The paper follows an action research approach by presenting as a case study the process by which the strategy for Malta was assessed and developed through successive rounds of engagement with business and other actors with the application of scenarios and other prioritisation approaches to facilitate its development. An initial consultation with 20 public sector and representative organisations was followed by a general business workshop and 21 sectoral focus groups.

Lack of critical mass can be mitigated by maximising the generic use of available skills and competences. Given the higher vulnerability to external shock in micro-economies, strategies need to have a high degree of flexibility and adaptability. Greater internationalisation provides the main response to peripherality.

The approach can be applied more generally for micro-economies and in some aspects to other countries or regions lacking critical mass in research and innovation assets or facing peripherality.

The smart specialisation approach had not been applied in these circumstances and hence the findings allowed the concept to be extended and adapted to deal with the issues raised.

Higher education institutions (HEIs) have multiple roles including teaching, research and more recently projects for the benefit of local communities. From a management and leadership perspective, the formation and implementation of strategic plans and the collaboration with stakeholders have traditionally been based on formal agreements based on existing operational organizations and structures. Their strategic plans and collaborations with stakeholders are now evolving to become more organic and collaborative. They have become essential participants of the innovation and learning ecosystems and knowledge intensive communities as shown here in the case of Finland and Australia. New businesses and regions, especially in Europe and non-European Union countries such as Australia, are encouraged to identify and develop their own competitive advantages by analyzing their strengths and strategic potential growth areas.

This so-called Smart Specialization (RIS3) strategy brings HEIs together with the local authorities, business companies and civil society to co-operate in order to prioritize research and development (R&D) investment in the region. The need for Smart Specialization also challenges HEIs to rethink their visions and renew the present siloed and closed-ended practices.

This chapter examines and compares the management and leadership of the HEIs as actions are undertaken to effectively lead the Finnish and Australian HEIs toward their visions. These case studies demonstrate approaches which influence good institutional governance and management. It describes how LAB-ammattikorkeakoulu (LAB University of Applied Sciences) in Finland, and Royal Melbourne Institute of Technology in Australia have implemented a RIS3 strategy, notably in health and well-being and agricultural (R&D) projects. These enhance the scope of accountability and participation of stakeholders. The chapter provides practice-based evidence to policy makers in higher education regarding HEIs’ responsible contribution to society.

The purpose of this paper is to present a new methodology to assess the outward connectivity among regional economies in the European Union (EU) and derives policy lessons for the design of regional innovation and competitiveness-enhancing strategic frameworks, with particular reference to research and innovation strategies for smart specialisation (RIS3).

The authors study the network of inter-regional trade flows in the EU25 in the year 2007. Trade data are taken from the PBL Netherlands Environmental Assessment Agency database and mapped onto weighted directed networks in which the nodes represent regions and the links are flows of goods. The authors measure several structural characteristics of the networks, both global properties and centrality indicators describing the position of individual regions within the system.

European regions appear to be mostly integrated in the European single market. Strengths and weaknesses of individual regions are discussed based on rankings obtained from network centrality indicators. Specific policy implications in the context of RIS3 are derived in the case of the Spanish region of Andalusia.

The authors show the potential of the methodology for providing a new family of indicators of the external connectivity of regional economies that can be used by regions wishing to develop their own RIS3 for 2014-2020, as required by the EU in the context of the new cohesion policy framework.

The characteristics of a EU-wide inter-regional network of trade flows are obtained and thoroughly discussed for the first time. A unique and original instrument suitable for inter-regional comparison is developed and tested.

This paper aims to evaluate whether the integration of smart specialization strategies (S3) into clusters significantly impacts their efficiency for countries that still do not implement this policy. This study tests three effects: whether the kind of policies envisaged through an S3 strategy impacts cluster’s efficiency; whether this impact changes with the technological intensity of the clusters; to determine which S3 is more suitable for sub-clusters at different levels of technological intensity.

The Mexican economy is taken as case of study because it has a proper classification of its industries intro Porter’s cluster’s definition but still does not adopt the S3 policy. Through data envelopment analysis (DEA), this study evaluates the cluster’s efficiency increment when variables representing the S3 elements are included.

The results show that strategies following the S3 had a significant impact in all clusters, but when clusters were classified by technological intensity, the impact on efficiency is higher in clusters in the medium low-tech group.

According to the results in the DEA, it can be concluded that these S3 strategies have the potential to increase the clusters’ productivity significantly. These results make convenient the adoption of the S3 policy by countries that already count with a properly cluster definition.

These findings contribute to the lack of studies that analyze the join implementation of S3 on clusters.

This paper aims to investigate the smart economic development (SED) patterns in Europe in relation to competitiveness. Motivational focus corresponds to global events: the fourth industrial revolution, transition to a low-carbon economy, economic shocks (such as the 2008 financial crisis, Brexit or the coronavirus pandemic), which requires rethinking development policies, targeting competitiveness increase and reducing imbalances in economic development.

The analysis includes self-organising neural networks cluster analysis and correlations, comparative analysis of SED indicators structure and cumulative index estimation with World Economic Forum (WEF) global competitiveness index. The panel data set of 19 years from 2000 to 2018 for 30 European countries.

Overall, cross-country examination suggests that European countries of higher competitiveness illustrate higher estimates in SED. The key determinants are juridical fairness, social responsibility, competence building, intelligence and welfare employment to develop smart patterns for reaching higher competitiveness.

The limitations relate to the particular sample of European countries and gathering statistical data and a methodology of the SED index calculation. In addition, the paper contains a macroeconomic environment focus on competitiveness estimation. Further research may be improved with micro and mezzo environment incorporation at a cross-country analysis level.

By linking well-known terms of competitiveness and economic development with a concept of smartness, new approaches to policymaking emerged. The methodology presented in this paper has implications for territorial cohesion policies, competitiveness and branching strategies. The combination of SED sub-indexes and WEF GCI might aid a more accurate ex ante measurement.

The findings are essential for fostering a smart approach in economic development for long-term competitiveness.

This paper provides original empirical evidence about the relationship between SED and competitiveness and adds new knowledge that smartness becomes a way for building countries’ competitiveness by identified two profiles of SED patterns by development stages, namely, integrated to economic development and institutional-based which is divided to focus and balanced.