**Riikka Kangas \* and Timo Aarrevaara**

Faculty of Social Sciences, ProSoc, University of Lapland, FIN-96400 Rovaniemi, Finland; timo.aarrevaara@ulapland.fi

**\*** Correspondence: riikka.kangas@ulapland.fi

Received: 28 February 2020; Accepted: 8 April 2020; Published: 10 April 2020

**Abstract:** The effectiveness of societal interaction has become a key aspect in evaluating the success of higher education institutions (HEIs) in performing their duties. These factors have been built into institutional funding models, and the funding of research follows a similar approach. External stakeholders are now having to share in undertaking some of the functions that will define higher education institutions' external activities, societal interaction and impact on society. The European Union's smart specialisation strategy is such a factor. This initiative allows higher education institutions to implement policies by building regional clusters. The counterparts of higher education institutions in these clusters of smart specialisation are knowledge-intensive enterprises, high-tech service providers, educational institutions, the Arctic Smartness Specialisation Platform and other centers of expertise for smart specialisation. In this paper, we have analysed the role of higher education institutions as knowledge brokers in smart specialisation though a qualitative analysis of 20 interviews conducted during the implementation of the smart specialisation project. Our findings show that the knowledge broker role can be promoted from four perspectives: the social dimension of networks; decision-making and control; cluster building; and exchange elements. The clarification and legitimation of the role of higher education institutions as knowledge brokers in these areas would give smart specialisation more impetus to reach its goals.

**Keywords:** higher education; knowledge brokers; knowledge intensive policies; smart specialisation; innovation ecosystems

### **1. Introduction**

The European Commission is aiming to boost economic growth and jobs with the European Cohesion Policy and the Strategies for Smart Specialisation (S3) initiative, as a part of the Europe 2020 Strategy for smart, sustainable and inclusive growth. A total of €330 billion has been applied to the task of increasing European economic competitiveness and social welfare through research and innovation during the 2014–2020 funding period. All member states have research and innovation strategies for smart specialisation, and the regions are integrating development efforts and seeking financial support from the European Regional Development Fund (ERDF).

The objective of S3 is economic development through regionally driven priorities that correspond to the efficiency, research and innovation-related demands of the knowledge economy and knowledge society. It is about allocating the resources of research and innovation to enhance priority areas of regional funding, governance and regulation, forming a regional policy mix. It emphasises the importance of relationships between various institutions and stakeholders and encourages institutions to change by diversifying their position and goals in a global context [1,2]. A notable aspect of smart specialisation is whether or not it is the most ambiguous regional innovation policy in the world: there have been no pilot projects, nor was empirical evidence produced before it was launched. Implementation occurred without any direct rules or guidelines for the actors or institutions to find their position in the changing environment [3,4].

Smart specialisation emphasises a place-based approach and the central role of the relational infrastructure of public institutions, as well as public and private sector cooperation, as a source of promoting regional growth [4]. However, even if public institutions including HEIs are embedded into the regional innovation system, there might also be also a gap in understanding among university management personnel about what the regional challenges are [5]. In this regard, public investment is the main source of the production of regional innovation systems, and transparent higher education institutions (HEIs) and other public institutions directly complement the support of innovation measures [1,6].

Actions to support the regional innovation system are developed through two main functions. First, the public HEIs and other research organisations have a role as a generator of new knowledge sub-systems. Second, companies and industries have a role as exploiters of knowledge sub-systems [7,8]. Earlier studies of the role of universities in smart specialisation redefined the classification of the two sub-systems mentioned above. The direction of research findings shows that, not only there are two separate roles for public and private institutions and organisations, but these roles are more diversified in the regions. Especially in small and less-developed regions, the role of public research organisations, like universities, is to have a more central role in generating and exploiting knowledge for firms and industries [4,8,9]. Previous studies have also shown that public institutions and other public resources have a significant role in regional development as institutions that connect and produce organisations and competence [1].

The roles of HEIs in processes based on smart specialisation implementation are diverse. There have been few case examples about HEIs' participation in S3 processes in regional areas, but it has been recognised that, especially in sparsely populated areas and less developed regions, HEIs tend to have had a minor role in knowledge production [10,11]. Changing practices guide the regions in coping with a changing operating environment [12]. HEIs can increase building infrastructure and administrative mechanisms to deal with knowledge absorption and new connections via institutional management [5,10]. The core missions of smart specialisation is to increase the competitiveness and sustainability of regions through specialisation activities. Internationalisation and linkages outside regional borders are significant when discussing sustainability and innovation potential. With the knowledge broker activities of HEIs, it is possible to improve at least the capacity of regional information management, exchange and linkage of knowledge, as well as the capacity building of actors in innovation systems [13].

Our aim with this paper is to analyse the role of higher education institutions as knowledge brokers in the European Union's smart specialisation program. How do knowledge brokers increase the competitiveness and internationalisation of regions? In this regard, HEIs can take a role that influences the effectiveness, interaction or renewal of the actors' work.

#### **2. Increasing the Competitiveness of the Regions with Knowledge**

HEIs as knowledge brokers in smart specialisation refers to their ability to achieve political goals, but also to the task of HEIs to increase the effective use of knowledge in regional and international networks and develop the knowledge society. Competitiveness and sustainability through responsible actions in the regions are leading goals to pursue, especially in sparsely populated areas. Responsibility that leads to sustainability forces research to be conducted about the changing role of universities in society. Understanding the development of society provides a basis for the changes needed.

#### *2.1. Knowledge Brokers in Smart Specialisation*

In regional development and innovation networks, the knowledge broker's role is to act as a gatekeeper, and to provide multiple overlapping groups with similar explanations as gatekeepers to multiple overlapping groups when knowledge brokering makes knowledge sharing possible for other actors in the innovation system. In the literature, few academics seem to have a direct impact on companies or have contributed to technological development in their regions [14]. Since few academics are working in this field, their importance to institutions' embeddedness in the regions is crucial. These actors are described in this paper as "knowledge brokers". Our aim in this paper is to describe the knowledge brokers as individuals in HEIs. Individuals facilitate the transfer of knowledge between various groups based on institutional strategies and mandates [15–17].

The concept of the knowledge broker refers to the literature of boundary work between science, industry and policy, and communication, translation and mediation work within those boundaries [18, 19]. The knowledge brokers can be defined as organisations such as firms, public authorities or associations, and acquire and exchange knowledge to foster competitiveness [19]. In this case, they can be defined as collective actors and as individuals working in HEIs [20] providing knowledge-brokering goals and strategies from different organisational perspectives [19]. Knowledge brokering can be seen as processes, organisations, or individuals that increase or connect relationships, co-evolution and knowledge production between academic actors and other actors in policy processes [21]. Institutions and individuals as knowledge brokers analyse the impact and use of datasets and classify the roles of networks and levels of knowledge and knowledge transfer [21]. The actions of knowledge brokers in the communicational decision-making process must increase effective communication. The literature identifies brokers as third-party members; that is, they are trusted, and they facilitate the knowledge brokerage activity [22]. However, HEIs are still key actors in the transfer of knowledge and enhancing innovation as a part of the knowledge-brokering process [4,23]. In this regard, we will define the knowledge broker's role in the concluding section. There are many alternative frameworks to define knowledge brokers in publicly funded organisations, but knowledge brokers have often been undefined or unrecognised [17].

The knowledge broker's role includes a broad range of activity, and they are seen as actors in the system framework, focusing on knowledge production, management and passive communication. The knowledge broker's most important role seems to be being in charge of the knowledge production and valorisation process, in which knowledge is not transferred but is valorised (redefined and valued) into a format to be utilised in another context [16]. The result of a knowledge broker's efforts might be financial, but in the case of a HEI it can also be an operational model that strengthens the institution's role in society and its service practices. A result of knowledge brokering can be support for evidence-based decision-making or other utilisation of knowledge. Thus, the main product of a knowledge broker may be the legitimacy of the HEI. Indeed, knowledge brokers can be described as knowledge exchange professionals, often associated with work conditions, casualisation and performance management demands [15].

In the knowledge broker position, HEIs would be able to develop smart specialisation actions that support the program objectives, but also enhance the development of the knowledge society. HEIs have access to global knowledge sources, as well as national and regional sources, so they can recombine and enhance knowledge diffusion for multiple needs. In networks, knowledge brokers acquire knowledge from partners in their network more often than from partners without knowledge broker positions [16,24]. Smart specialisation activities are embedded in a fundamental role of HEIs, but with particular emphases. University—industry linkages and the HEI's core role are naturally formulated in the S3 process, but with the knowledge broker role it is possible to add impetus for HEIs to promote future policies, and to increase the use of the knowledge which has been embedded in regions and largely in public and privately funded institutions [25].

There is growing evidence that HEIs have adopted the role of knowledge broker [26]. This role is even defined as a sign of a postmodern profession which has links and embedded institutional connections to platforms in the innovation process. Especially in the regions, with the absence of large firms, there is a growing need for public knowledge brokers [11,13,16,26,27]. The Smart Specialisation strategy will provide empirical evidence of the manner in which these phenomena can become more collaborative and more visible.

In regions with major industries, entrepreneurs are often found in the role of knowledge broker. In smart specialisation programs, HEIs have a role that can be defined as being a knowledge broker for regional, national and international actors. These roles are crucial, mostly because other organisations, including industry, are not in direct contact with each other. The HEI's role is based on collaborative actions, the trust of society, and the engagement of stakeholders for cluster building [28]. As research has shown [29], currently it is important for HEIs to increase the emphasis on the wider usefulness and uptake of research, which will increase the mobilisation of knowledge and enable the emergence of innovation.

#### *2.2. Creating a Sustainable Knowledge Society*

In contrast to the industrial economy and competitiveness, the knowledge society focuses more on the production, valorisation and the usability of knowledge in different contexts [12]. Knowledge enhances actors' understanding of drivers for the future, in which knowledge, research and education, as well as human capital and new technologies, are the components shaping the knowledge society [30].

Integration policy in the EU can be accomplished by reforms and implementation projects which also enhance the functions of the knowledge society. From the perspective of European higher education policies, the European-level integration policy and knowledge society policy have enabled new development conditions. The underlying idea was to increase the competitiveness of Europe by building an innovation-sensitive society with common rules for the welfare society [31] (p. xxxvi).

A key level of analysis in this paper is the HEI as a knowledge-based organisation. Individuals working in HEIs are engaged in their own institutional structure, and HEIs are embedded in broader systems such as national innovation strategies and networks [32]. In this way, HEIs also strengthen the legitimacy of their activities by supporting companies and knowledge-using organisations both regionally and locally [14]. A key element for implementing the embeddedness of HEIs in their urban and regional surroundings is achieving mutual benefits [33]. In this regard, the Smart Specialisation Program highlights the roles of individuals and institutions as knowledge brokers. Competitiveness and internationalisation are the policy goals of smart specialisation and goals for HEIs. Regional collaboration and cluster strategies are also important for HEIs, because they embed HEIs tightly into the regional structure, leading to significant investment [34].

In this paper, we find universities and universities of applied sciences to be actors in national innovation systems. The system of universities of applied sciences was being formulated in the early 1990s, and, since then, their foci have been on teaching and regional impact. The Polytechnics Act (2013) in Finland strengthened their role in research, and several mergers with universities have legitimised their role in the innovation system. The Universities Act (2009) emphasises universities' role in national and international research systems, and their role in teaching and societal impact. The third key actor in the research sector in the Smart Specialisation Program comprises research institutes, and they have a key role in sector research and a major regional impact [35,36]. In the Finnish case, their regional role and contributions to the regional economy are the driving force behind innovation. From this angle, HEIs have a special regional mandate, referring to legitimacy which is based on factors related to economic growth and well-being. The strong regional impact also provides a possible role for influential individuals as academic entrepreneurs [9,28]. In Section 4, our analysis recognises the role of knowledge brokers in particular in this context.

Strategies to increase universities' competitiveness have changed their focus to emphasise the creation, transfer and application of knowledge. R&D actions, the application of knowledge and the ability of higher education to create and transfer knowledge have especially been a central focus for the development of ideal institutional profiles [37,38]. Competitiveness-related institutional strategies have changed the nature of the knowledge required. Stronger emphasis on R&D actions based on scientific grounds is seen as a key factor accelerating economic growth and persistence.

HEIs are key actors in developing wealth in society and the knowledge economy. The role of HEIs is as key players in knowledge production, and their entrepreneurial mission as players in the Quadruple Helix for science and knowledge [39]. HEIs are strategising their activities to fulfill wealth creation demands in society by co-creating activities. In general, the role of HEIs in the regional innovation system is necessary because of the longstanding experience and embeddedness of funding systems and international research systems, as well as the experience of developing framework programs [40].

The importance of HEIs can also be seen from other perspectives. Firstly, their role as active knowledge brokers encourages institutions to change their structures and networks to be more innovative in a way that increase innovativeness and long-term relationships in national innovation systems as well as in global innovation networks [7]. Secondly, the mission-oriented universities face many demands from society. The development of a knowledge society requires the fulfillment of certain expectations, such as funding models when regional and international networks are seen as a requirement for effective action from universities. This connects universities more closely to society [29].

The literature on the role of HEIs in innovation systems points out the importance of knowledge-brokering actions. Without these actions, there is a risk that innovation activities will not be based on scientific knowledge. The academic knowledge produced is used for other purpose and not for local networks [16]. From the regional perspective, the absence of university knowledge brokers refers to the lock-in discussion of the need for knowledge transfer, management and linkages across borders as a mix of specialised regional knowledge and globally dispersed knowledge. These are crucial for solving the problems of inflexibility in the innovation system and enhancing the potential for innovation. In the end, all these problems reflect the political achievements and the evolution of smart specialisation, as well as increasing the use of knowledge and the absorptive capacity of enterprises. These activities reduce the sectoral differences between industry and HEIs and can create a more common regional future based on shared visions and the in-betweenness of sectors; they can also create sustainability [5,13,24].

#### **3. Materials and Methods**

The data in this paper were collected from the implementation project of Smart Specialisation strategy- Arctic Smartness Excellence project (ASE) in the Lapland region of Finland. Smart specialisationin Lapland is based on the Arctic Smart Specialisation strategy that was published in 2013 [41]. Smart specialisation is based on cluster activities, strengths, value chains and new forms of cooperation in the Lapland region. The analysis of multiple projects and the strengths of the industries are the basis of the construction of five clusters. The construction of clusters is mostly made by regional authorities, research organisations and HEIs, and actions are based mostly on public projects.

For this paper, documentation on smart specialisation and interviews have been examined. The data include 20 interviews with key actors in regional smart specialisation, including cluster managers, members of the program board, management of the participating organisations, officials of the funding organisation and representatives of the enterprises. Actor groups in Arctic Smart Specialisation are clearly identifiable, and for this reason the organisation has not been named, but the interviewees' gender and status in the organisation have. The topics for the semi-structured interviews were knowledge, collaboration, leadership and the role of companies in Arctic specialisation.

Interviewees were selected according to the structure of the ASE project. Partner organisations had their key actors in project roles in the clusters or work packages of the project. Also, some interviewees were selected from outside the project in order to provide more holistic perspective of regional development and innovative actions based on funding instruments. Because the clustering is at an early stage in Lapland, only three participants from companies belonging to the cluster were selected. The core parameter for selection was that interviewees were leaders of the program or clusters, members of clusters or work packages, funding agencies or companies related to cluster activities. The organisations, their roles and the contribution of the interviewees' are presented in Table 1.


**Table 1.** Organisation and role and contribution of Interviewees'.

The data were collected between December 2016 and February 2018 and include an estimation of the regional actors' investments in the realisation of smart specialisation objectives. The data for this paper were based on the program documentation and interviews with representatives of Research and Innovation Strategies for Smart Specialisation (RIS3) implementation in Lapland. The document analysis also included the perspective of the ERDF funding instrument for the ASE program and definitions of the smart specialisation clusters. The data from the ERDF funding instrument shows the number of projects funded by the ERDF in Lapland in 2016, and therefore complemented the interviews and constructed the basis for understanding the capacity building and other needs of the region.

The analysis was carried out using NVivo software, using qualitative content analysis to have a flexible but systematic analysis of the role of universities in smart specialisation. The analysis was based on analytical concepts (nodes) of network cooperation, knowledge capacity, the role of actors and project management. Nodes were combined into the main nodes and subnodes were created under each main node previously introduced. Subnodes were decision-making, control and roles in decision-making bodies, prerequisites for continuity, the role of companies, the needs of the companies, the roles of public organisations and subgroups, competence and knowledge, the growth of competence and effectiveness, as well as change with cooperative network actions. NVivo subnodes are categorised between those having something in common [42] (pp. 105–106). Four key themes of defining knowledge brokers were created by generalising the subnodes and they are cluster building, decision-making and control, the social dimension of networks and exchange elements. Themes have been introduced in the conclusion section, and those themes introduce the four dimensions of knowledge brokers in the case networks.

Even though the analysis for this paper was based on concept-driven content analysis, the data had the most important role in creating the subcategories, and the coding frame itself provides a comprehensive description of the data collection [43] (pp. 170–173). The analysis of the networks revealed the functional opportunities that could be provided by the clusters, and the results of the program have been verified by the concepts of external effectiveness, reflexivity and societal interaction and the interpretation of knowledge brokers.

The data provided information on building knowledge as capacity for the key actors, and the support of the program in terms of funding, competitiveness, digitalisation and sustainable development of the environment. The purpose of these perspectives is to make the strategic priorities and effectiveness visible. Regarding external effectiveness, the criteria should be clarified for openness and locality. Transparency refers to changes in work practices that improve the ability to achieve goals. Locality refers to activities that support the construction of clusters that are linked to the capacity-building functions of the regional actors. The criterion of external effectiveness is based on the smart specialisation monitoring definition, which emphasises learning, trust and accountability [3].
