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Since the summer of 2020, researchers from ten projects pertaining to the Horizon2020 Science with and for Society (SwafS) call have been meeting virtually as the SwafS14 Monitoring and Evaluation ecosystem. Topics of discussion were the trials and tribulations of their regional Responsible Research and Innovation (RRI) projects as well as their strategies for monitoring and evaluation. In this paper we make a first attempt at presenting these issues as problems of translation between different kinds of stakeholders. After an exploration of the diversity of stakeholders and the process of translation in regional RRI, we suggest evaluative conversations as a way of improving regional RRI. We intend to develop this idea in the future and that these conversations will facilitate more responsible and engaged monitoring and evaluation and contribute to better R&I policies.

The European Commission’s attempts to reconcile science (‘in here’) with society (‘out there’) have created a ground swell of democratisation in European research policymaking. Accompanying this evolution is the reformulation of the action plan ‘Science and Society’ to ‘Science in Society’ in 2007, which later became ‘Science with and for Society’ (SwafS) under Horizon 2020, where participation and inclusion assume central stage as mechanisms for aligning scientific practice with ‘the needs of the real world out there’. The underlying assumption is that involving diverse sets of actors in research processes automatically ensures societal relevance and desirability of research outcomes. However, as participatory practices in research become further grounded, there are loud signals from the SwafS ecosystem network of Super_MoRRI that projects experience difficulties with regards to involving diverse stakeholders. This gives rise to an introspective question: how can participation and inclusion be achieved in the context of such diverse stakeholders?

The study “New technologies and digitisation: opportunities and challenges for the social economy and social enterprises” sets out to explore how the rising importance of the social economy in Europe is facing the challenges of digital transformation. It focuses on whether, why, how, and to what extent the integration of digital platforms and advanced technologies (i.e. Open-Source, Artificial Intelligence, Internet of Things, Big Data, Distributed Ledger Technologies) may affect the design and delivery of new/better social and societal impact by the social economy. This study shows that digital platforms and advanced technologies’ capabilities of automating and simplifying operations are opening up opportunities for the social economy in terms of increased reach and enhanced effectiveness. Digitalisation also underpins the creation of new and innovative social services and working conditions helping to tackle existing and emerging social and societal problems. Whilst these trends are set to continue in the near future, European Institutions, Member States policymakers and social entrepreneurs should commit to promote and support the digital transformation of the social economy and encourage the uptake, scale-up/scale-out and duplication of innovative digitally-enabled initiatives. Areas of intervention have been identified. Resources for Research and Innovation as well as traditional sources of revenues play an important role for the development and take-up of digital technologies for and by the social economy. Likewise, the development of entrepreneurial and digital skills of social economy actors are needed to foster the vision of the European digital social economy. Collaborations between various stakeholders in nurturing environments (social clusters, creative spaces or incubators) may effectively promote the modernisation of the social economy by strengthening and growing digital native cohorts of social economy organisations. Finally, in order to promote cross-Member State growth of the social economy, it is advisable to harmonise the legal forms and statutes regulating the various actors of the social economy. This way, digital platforms and advanced technologies may truly contribute to the establishment of the European digital social economy fit for the societal challenges of the 21st century.

This Smart Guide is addressed to policy makers and cluster managers engaged in cluster policy making who are interested in monitoring and evaluating the impact of their policies. The objective is to provide them with easy access to knowledge material of high practical value and sound methodological underpinnings, available in a concise and easy to read manner. It thus complements the Smart Guide Cluster Policy published by the European Commission (2016)1 that had already advocated monitoring and evaluation as a strategic tool for the implementation of cluster policies and programmes.

The ongoing digital transformation is crucial for the social economy as it presents both enormous opportunities and challenges. Digital technologies, such as online platforms, software applications (apps), distributed ledger technologies, the Internet of Things (IoT), cloud computing and Artificial Intelligence (AI), offer a wide variety of tools to support the creation of social values and the development and further expansion of the social economy. Budget constraints, digital skills shortages and technological gaps are clear barriers for the social economy to uptake new technologies. We selected 26 social economy organisations using innovative digital technologies effectively across Greece, Italy, The Netherlands and the UK. Our objective is to understand how they are working through the digitalisation process. The study, based on primary information and insights collected via personal interviews, workshops and on relevant literature, sheds light on the key questions stated above. Here we present highlights of the study.

This report provides an overview of national and regional cluster support in Europe as well as a selection of non-European countries, based on information on cluster policies and cluster programmes or other interventions to support cluster activities. With this horizontal overview, it complements the Smart Guide to Cluster Policy that identified good practices.

The aim of the work in Slovenia is to support the national authority and stakeholders in defining actions that facilitate the industrial transformation of Slovenia through clusters. In the case of Slovenia, the Slovenia S3 strategy (also referred to as S4) with the nine SRIPs (Strategic Research and Innovation Partnerships) is currently being implemented as the strategy for industrial transformation. SRIPs are at the core of the S3 strategy, and as national clusters and cluster policy they are instrumental in the country's industrial transformation. As identified in the assessment report implementation of strategies can be seen as a weakness of the past. New strategies and policy measures have been developed replacing old ones, before these previous strategies and measures had been properly implemented and evaluated. The SRIP policy is deliberately addressing this vulnerability, since it is not a short-term support. It is investing in SRIPs as institutional and governance structures and it emphasises the importance of learning with, for instance, actions on cluster management skills development and monitoring of SRIPs. As relatively young clusters, SRIPs (established in 2017) will also serve to steer the transformation process, and initiate and implement new strategies and actions after the support or programming period. The needs expressed by Slovenia in its application as a pilot region therefore did not refer to the development of a new strategy, but rather to more concrete actions supporting the implementation of the current strategy and structures. The EOCIC work was carried out in cooperation with the AMI expert who was also funded by the European Commission. This policy brief provides input into a "managed industrial transition" (Zuleeg et al, 2018) through clusters, based on the insight that different clusters, regions and Member States across Europe are characterised by different assets, strengths and weaknesses, and that they face different obstacles and threats that need to be overcome. We therefore adopt a tailored approach that builds on existing resources and we place considerable emphasis on co-design and commitment from the variety of relevant stakeholders in the transition concerned. This document builds on the assessment report to summarise the challenges, barriers and drivers to industrial modernisation in Slovenia, before outlining a set of actions to support the managed industrial transformation. The report is based on extensive desk research, a number of face-to-face interviews, a study visit in Ljubljana (June 2018), a policy review meeting (November 2018) and insights from participating in a capacity building workshop for Slovenian Clusters/SRIPs (November 2018)

Key Enabling Technologies as defined by the European Commission include: photonics, nanotechnology, advanced materials, micro/nano-electronics, biotechnology and advanced manufacturing technology.  The up-take of KETs enables to advance manufacturing, productivity and growth; Without using KETs in manufacturing, inventing KETs does not generate growth, nor productivity, nor solves societal challenges.  Technologies and policies which are ‘key’ and ‘enabling’ at EU level, may not be ‘key’ and ‘enabling’ for the actors, sectors and regions of Croatia.  KETs research and policy practices developed at EU level might however be adapted to innovation research and policy making in Croatia.  Sweden and Slovenia are leading in using sustainable and ICT-enabled manufacturing technologies. The position of Germany and Croatia is more modest. Policy lessons from Slovenia are likely to be more relevant.  Challenges on the user-side of enabling technologies typically include: lack of understanding; conservatism of users; skills; fear for disruption in a systemic way; scale of investment/risks.  Centres across Europe promote the up-take of KETs in manufacturing; activities include: Access to technology expertise and facilities; Demonstration; Proof of concept; Prototype development and testing; Pilot production and demonstration; Product validation & certification.  Innovation researchers and policy makers can contribute to interactive learning among stakeholders in the (policy) innovation processes. Moreover, they can get empowered by orchestrating this discovery process

Key Enabling Technologies as defined by the European Commission include: photonics, nanotechnology, advanced materials, micro/nano-electronics, biotechnology and advanced manufacturing technology. • The up-take of KETs enables to advance manufacturing, productivity and growth ; Without using KETs in manufacturing, inventing KETs does not generate growth, nor productivity, nor solves societal challenges. • Technologies and policies which are ‘key’ and ‘enabling’ at EU level, may not be ‘key’ and‘enabling’ for the actors, sectors and regions of Croatia. • KETs research and policy practices developed at EU level might however be adapted to innovation research and policy making in Croatia. • Sweden and Slovenia are leading in using sustainable and ICT-enabled manufacturing technologies. The position of Germany and Croatia is more modest. Policy lessons from Slovenia are likely to be more relevant. • Challenges on the user-side of enabling technologies typically include: lack of understanding ; conservatism of users ; skills ; fear for disruption in a systemic way ; scale of investment/risks. • Centres across Europe promote the up-take of KETs in manufacturing ; activities include:Access to technology expertise and facilities ; Demonstration ; Proof of concept ; Prototypedevelopment and testing ; Pilot production and demonstration ; Product validation &certification. • Innovation researchers and policy makers can contribute to interactive learning amongstakeholders in the (policy) innovation processes. Moreover, they can get empowered byorchestrating this discovery process.

Three policy challenges explained: Need to create public accelerator programs, which boost supply and demand for optimal recycling in a co-evolving, systemic way; Shaping long-term vision of space Big Data policy; Developing regulation and standards to support blockchain application.

We evaluate the effect of innovation support programs on output innovation by small and medium enterprises in traditional manufacturing industry. This focus is motivated by a definition of traditional manufacturing industry that includes capacity for innovation, and by evidence of its continued importance in European Union employment. We conducted a survey in seven European Union regions to generate the data needed to estimate pre-published switching models by means of the copula approach, from which we derived treatment effects on a wide range of innovation outputs. We find that for participants the estimated effects of innovation support programs are positive, typically increasing the probability of innovation and of its commercial success by around 15%. Yet, we also find that a greater return on public investment could have been secured by supporting firms chosen at random from the population of innovating traditional sector small and medium enterprises. These findings indicate the effectiveness of innovation support programs while suggesting reform of their selection procedures.

This report focuses on modes of ICT innovation at the meso level of systems and the micro level of firms. After a summary of the literature on national innovation systems, and it’s sectoral and regional applications, we discuss how the concept of innovation systems can be applied to the case of ICT innovation. A framework for indicators is proposed to characterize the performance of ICT innovation systems. Due to the multi-purpose and pervasive nature of ICT, it is relevant to extend the innovation systems concept to the societal level. The resource-based view of the innovative firm fits very well with the innovation systems perspective. Patterns in the firm-level sets (combinations, or mix) of resources and capabilities can be identified with factor-analysis and they give rise to the main types or modes of innovative behaviour. Monitoring ICT innovation systems is important as it allows us to learn how to improve the policy and performance of current and future systems. It allows us to design and improve an ICT innovation policy mix, which is tailored to the specific ICT modes of innovation, and also tailored to the prioritized mix of challenges (e.g. economic, social, environmental, health, or other impacts). Since ICT innovations emerge and diffuse fast, timing in institutional change is crucial. Setting new standards, and updating regulations can create a competitive edge. ICT innovation policy has become (and should be addressed as) a horizontal policy field which maintains systemic linkages with other policy fields. At both the system and firm level, there are several modes of ICT innovation. Policy makers should not reduce diversity by favouring only one mode. As an extension to Lundvalls’ theory on interactive learning between producers and users of knowledge, we add that policy for ICT innovation should be produced in interaction with its users., JRC.B.4-Human Capital and Employment

Facilitating the creation of co-working spaces and virtual collaborative platforms is crucial for the maker movement. Co-working spaces, Fab Labs and makerspaces allow people with common interests to come together, increasing access to manufacturing infrastructure which was previously confined to manufacturing companies. Digital platforms also enable individuals to more easily connect and share ideas and resources fuelling the maker movement. These networks in turn influence others to become makers themselves. But to fully take of more infrastructure, both physical and virtual, is needed. The policy challenge of promoting new protein sources lies on both the supply and the demand side. This new protein sources industry is today being held back by a restrictive and unclear EU regulatory environment. The lack of clear position at the EU level on the classification of insects and algae as Novel Foods results in a legislative ambiguity across Member States. Most particularly, the use of insect proteins in feed is being hindered by the lack of precision in defining the scope of the regulations. On the other hand marketing and persuading customers and consumers to shift to these new sources of protein remains a challenge. Boosting the civil UAV market could lead to job creation and new innovative applications in various sectors. The EU established the main principles that should govern UAVs development in Europe as from 2016 onwards within the Riga Declaration. Moreover, in recent years, some 10 Member States have issued partial regulation allowing limited civil UAVs operations. But more can be done do help this sector to grow.

Through the three trends of service innovation, traceability, and the Internet of Things, smart industries get connected in smart value chains. Industrie 4.0 in Germanyis an example of a national policy programme to enhance this development towards smart value chains. The Internet of Things and Services enables traceability and value creation by Smart Factories in smart value chains, which in turn serve other domains such as smart mobility and Smart Health. Hyper connectivity leads to a major shift from the linear value chain, to a non-linear ‘value network.’ Cyber-Physical Systems (CPS) are at the heart of this transformation to a network-based economy. Also human-robot collaboration, digital education and traceability contribute to this change, which includes legal and cultural aspects. For all stakeholders in the systems and value networks concerned this implies a drastic transformation in how consumers (and others) are reached, connected with, and engaged.

Several recent studies report on the recent up-take of demand-side innovationpolicies, but they merely focus on the national policy level. Moreover, these studiesfocus on specific types of demand-side measures, such as regulation andstandardisation, which may not be the most relevant policies to increase the demandfor innovations at the regional level. This thematic paper of the Regional InnovationMonitor addresses demand-side innovation policies at regional level.In the literature many authors have emphasised the importance of the demand-side ofinnovation. Involving users and interaction with public and or private users isessential for the dynamics in innovation systems. However, the implementation oftargeted demand-side innovation policies is a rather recent trend (4) (PDF) Demand-side innovation policies at regional level. Available from: https://www.researchgate.net/publication/283498363_Demand-side_innovation_policies_at_regional_level?channel=doi&linkId=563b3be508ae337ef299457d&showFulltext=true [accessed Feb 14 2023].

This study provides an in-depth examination of the publications and patents reported through the yearly survey waves undertaken by DG CONNECT for the Framework Programme 7. It represents an analysis of the productivity and quality of the research output of projects funded under FP7 ICT

This policy brief responds to the initial challenge to diversify its tourism sector identified by the Canary Islands in its application to participate in this initiative. The policy brief is based on a regional summary assessment prepared by a team from ESIC that analysed the potential role that service innovation could play for the region. It also follows a peer review meeting that took place on 18-19 February 2014 in Tenerife, where the regional stakeholders and the peer review panel reviewed the findings of the summary assessment and outlined the potential ways forward.

This paper highlights the great diversity in development pathways and trajectories of innovation across European regions. A regional knowledge-based economy has multi-dimensional aspects. It includes a variety of knowledge activities and multiple interactions among a range of actors including universities, research institutes, enterprises, knowledge workers and institutions. The spatial patterns and trends for the different aspects of the knowledge-based economy vary significantly across Europe. Most aspects show convergence and generate catching-up processes, while some show divergence between European regions. Overall, absorption capacity has increased in importance and education is an important challenge for future regional development. Place-based innovation policy is essential to enhance synergies among co-evolving knowledge capabilities and encourage smart specialisation.

Innovation has climbed higher on policy agendas everywhere, not only in developed countries but also in emerging economies. As a relatively young policy area, it is designed mainly as a trial and error process, with no simple and universal model to follow. Moreover, innovation not only serves economic purposes, but has invaded other policy agendas. As a possible solution to a diversity of problems it has been included in the missions of almost any traditional policy field, including science policy, competition policy, environmental policy, foreign policy, regional development policy, education policy, etc. Hence, the need for new conceptual frameworks and policy intelligence tools to feed policy-making is expanding dramatically. This book is about how to increase policy intelligence by combining quantitative and qualitative assessments of Innovation Systems, and by taking a forward-looking perspective on the conditions for an innovative Europe of tomorrow. A number of new developments and new challenges have been identified throughout the chapters, which, together, help pave the way towards future innovation policies for Europe.

This book increases our knowledge of innovation policy by combining quantitative and qualitative assessments of innovation systems, and by adopting a progressive outlook on the conditions for an innovative Europe of tomorrow. Based on the latest developments in innovation research, the authors aim to draw practical and workable conclusions for policymakers.

This case study provides insight into how a particular transformation of the innovation process affects individual companies and the regional Mechatronics system as a whole in the Eindhoven-Venlo region (The Netherlands). The transformation involves out-sourcing engineering activities by Océ, one of the major high-tech companies in the region. Océ wanted to upgrade regional suppliers from jobbers into main-suppliers so that most of the engineering could be done by suppliers while Océ played the role of system integrator. Local suppliers saw an opportunity to reduce the extent of (production) cost competition by increasing their own innovative competences. Under the Knowledge-intensive Industrial Clustering (KIC) policy programme the collective goal is to build up internal knowledge resources and increase the use of external knowledge resources in the local area. The case study shows that the change in allocation between internal and external knowledge resources is not an easy (costless) change. The restructuring of a codification process requires intensive communicative interaction between heterogeneous knowledge resources and this is favoured by proximity.

Based on the empirical findings achieved in a comparative research,involving 40 innovation policy instruments in 11 European regions, thispaper exposes the claim for a new innovation policy paradigm andproposes a shift in rationale and in broad orientations for innovationpolicy, addressing SMEs in their regional context. The main role forinnovation policy, which aims to increase the capacity of a region andthe capabilities of its SMEs to innovate, is to foster interactive learningwithin the firms and within the region. This calls for an interactivemode of policy intervention.The paper also deals with the question of how to build a coherentportfolio of policy instruments, taking into account both regionalsituations and specific SMEs needs in terms of innovation. The keymessage delivered is that there is no "one-size-fits-all" policy portfolio.Regional differences in innovation capabilities call for a tailored mix ofpolicy instruments. One salient element of the conclusion is the need formore "policy intelligence" in this complex field.

This case study questions how Flanders Language Valley developed as a cluster of localized technological change. Through licensing the attracted small, mostly foreign firms use the research lab of L&H Speech Products as a common source of codified knowledge and with their fast entrepreneurial reaction they complement it by developing a broad range of applications. Subsequently, the created favorable communication conditions induced innovative linkages between the attracted SMEs. Like the Silicon Valley role-model, a strong pilot firm, venture capital, education and most of all the informal networking were critical to the development of FLV. Companies ''find'' each other at FLV to their mutual advantage. They learn from each other and benefit from developing and using common pools of resources in proximity, e.g., companies find employees in the ''collective pool of labour'' created by several education and training programmes.

The thesis enquiries into our understanding of how, as technological conditions change from nascence to maturity, firms change their innovation behaviour. As technologies mature, firms strategize from less committal forms of partnership to more committal forms of partnerships such as mergers and acquisitions (M&As). It has also been deduced that changes in renewable energy systems occur as a result of changes in the maturity of the technologies, and which in turn influences how firms strategize and compete with other firms.

When discussing innovation dynamics in western economies during the age of globalisation, innovation and manufacturing are often perceived as two geographically distinct spheres of activity: The former tends to be located close to home, while the latter is foot-loose and can be re-located based primarily on cost considerations. The analysis presented in this thesis offers evidence that this is not always the case. Location still matters and this is demonstrated all across Europe, as high-performing clusters are identified not only where they are expected (e.g. auto manufacturing in Germany) but also in regions with centuries of history in specialization that have since evolved, such as the textile sector in Flanders and the wood and metal sector in Sweden. These clusters appeared to be linked to unexpected aspects of economic performance, since, for instance, the more ‘traditional’ cluster seems connected to less unemployment.