Define the relevant cross-border area for innovation support

Cross-border collaboration differs from other forms of international innovation collaboration

Several forms of interactions among regions take place on an international basis. There are three basic forms of collaboration across borders, but with different spatial scales (examples in Table 1.2):14

  • • Cross-border co-operation (contiguous areas) involves a limited set of neighbouring regions from at least two countries, with adjacent borders, covering a restricted space (typically smaller than an average country). Those cross-border areas often have a long history, and sometimes represent historical regional definitions. For example, the Swedish part of the Oresund was part of Denmark until the end of the 17th century, and Danish remained an official language for two centuries. Due to their proximity or historical ties, such areas may show similarities in economic development and culture, or perhaps share the need to overcome peripherality with respect to economic and political centres in their respective countries.
  • • Transnational co-operation (macro-regions), including a large continuous set of regions from different countries, as well as entire countries, covering a wide territorial area. Transnational approaches for such macro-regions have been the subject of trade arrangements around the world. They have also been considered in Asian co-operation approaches. They have received increased political interest at EU level, with the development of transnational programmes in macro-regions as well as macro-regional strategies, thus far for two areas that share a common water basin.15,16 Two cross-border initiatives in the United States (with Canada and Mexico) resemble macro-regions given their scale.
  • • Interregional co-operation (international, non-contiguous) refers to networks of regions that do not share physical common borders but do share common characteristics or goals. Many such networks, with various degrees of depth and stability, exist. For example, several programmes within the European Union support such exchanges of experiences and joint projects among regions.17

The contiguous cross-border areas are the most relevant for developing joint, or at least co-ordinated, regional innovation policies. First, such configurations are more likely to focus on innovation-driven economic development opportunities than broader geostrategic or infrastructure considerations. Second, with geographic proximity, the economic exchanges and flows of people, capital and knowledge may be more intense within such cross-border regions than in the other types. Third, such forms of co-operation are likely to have greater longevity, as opposed to specific regional networks formed on a temporary basis for a time-bound financed project. Finally, there may be a more favourable environment for the development of a shared vision, which in many cases may be supported by greater cultural proximity than in macro-regions that group many countries.18 In other words, contiguous cross-border regions are closest to a functional region for the purposes of innovation policy.

Table 1.2. Different spatial scales for cross-border collaboration: International examples

Type of cross-border area


Cross-border co-operation (contiguous areas)

  • — Top Technology Region/ Eindhoven-Leuven-Aachen Triangle (TTR-ELAt) across the Netherlands, Belgium and Germany
  • — Centrope region at the intersection of Austria, Czech Republic, Hungary and Slovak Republic
  • — Danish-Swedish Oresund Region
  • — Paso del Norte region including Ciudad Juarez, Chihuahua (Mexico), El Paso, Texas (United States) and Las Cruces, New Mexico (United States)


Transnational approaches and programmes in macro-regions



  • — North Atlantic Cooperation Network (Faroe Islands, Greenland, Iceland and Norwegian coastal regions)
  • — IPA Adriatic Cross-border Cooperation Program (Italy, Slovenia, Greece, Croatia, Montenegro, Bosnia and Herzegovina, and Albania)
  • — Pan Yellow Sea region of cities (People’s Republic of China, Japan and Korea)
  • — Asian growth triangles (such as one with regions in Singapore, Malaysia and Indonesia)
  • — Pacific Northwest Economic Region (Canada and United States)
  • — Border Governors Conference (Mexico and United States)

Macro-regional strategies (European Union)

  • — Danube region
  • — Baltic Sea region

Inter-regional co-operation

— “Four motors of Europe”: Lombardy, Catalonia, Rhone-Alpes, Baden- Wurttemberg

(international, noncontiguous)

— “District of Creativity” Network of 13 regions in 3 continents (Europe, America and Asia)

Cross-border efforts should target “functional” regions for innovation, but data are often lacking

The definition of a functional cross-border area depends, of course, on the function. Several attempts have been made to quantify what makes a functional region (Box 1.5). A functional cross-border area with respect to innovation activities may, however, be different from a functional area defined mainly by commuting patterns. It is an area where there is a high density of innovation-relevant internal interactions among actors of the cross-border area. Such actors include workers, firms (both SMEs and multinationals, firm associations or clusters), public agencies and government bodies, universities and other higher education institutions. A high level of engagement of the civil society in cross-border initiatives is a further indicator for the potential to be a functional area for innovation activities. Different innovation functional spaces can be defined according to the intensity of cross-border linkages with respect to specific sectors or among certain types of actors. The functional area for research institutions may be different from the functional area for firms, for example. In addition to cross-border linkages, an assessment of the degree of innovation capacity in general has been used to assess the potential functionality from an innovation perspective.

The definition of a functional region calls for data; however, such data are often not generated or analysed. These indicators are above and beyond the traditional indicators related to administrative areas focusing on commuting patterns. Data for innovation-related flows, or even basic cross-border commuting flows, is generally lacking. National statistical offices collect data related to administrative regions in their respective countries only. However, they typically do not focus on collecting data or tracking indicators on innovation linkages and flows both within and across administrative borders. Furthermore, tight budgets at national statistics agencies make it difficult to request information for cross-border areas. The regions themselves are generally not able to devote the resources to developing such cross-national data harmonisation. Nevertheless, there are some interesting examples of cross-border statistical agencies or task forces such as Orestat (for the Oresund area), or the All-Island Research Observatory (AIRO) in Ireland and Northern Ireland (United Kingdom).19

Box 1.5. Defining and measuring functional areas: Implications for innovation policy

A functional region is a territory sharing commonalities and linkages that create interdependencies and thus cohesiveness, making it distinctly different from other regions. Functional regions are frequently defined as territories organised around a central node, while the rest of the territory displays linkages to that node through different types of relationships, associations and activities. Other types of functional regions do not display such a centre-periphery profile and may have a multi-hub configuration. The boundaries of a functional region frequently differ from those of a formal region, defined as political entity by laws and institutions. Contrary to formal regions, which tend to have stable definitions, the definition of a functional region is contingent on the type of function taken into consideration.

Typical functional regions are metropolitan areas, i.e. areas dominated by the attraction power of a main city. The OECD has developed a methodology to identify urban areas as functional economic units using density and travel-to-work flows as indicators (OECD, 2012a). In this case, the “workers catchment” power of the city is the main function taken into consideration to define the functional metropolitan region, but that region may have one or more cores with associated hinterlands. This new definition is wider than the earlier OECD definition of functional regions, meant to simply correspond to local labour market areas, where labour supply matches labour demand (OECD, 2002).

Functional regions from an innovation perspective are regions which show a high density of internal interactions in innovation-related activities. Two approaches have been used to assess the reality of such innovation-oriented functional areas:

  • • Cross-border interactions: those interactions can be measured, data permitting, with indicators such as: co-patents; co-publications; co-operations in innovation; flows of technology transfer; flows of venture capital for innovative start-ups; mobility of highly qualified knowledge workers, etc. calculated as shares of these interactions occurring within the cross-border area, on total interactions.
  • • Cross-border critical mass: the critical mass can be measured by calculating the total weight of innovative sectors in the cross-border area, in a comparative way. This is the approach taken by BAK Basel Economics, calculating a competitiveness index as the non-weighted average of four indicators: the nominal gross value added (GVA) share of the technology sectors; their GVA growth; the number of patents; and the number of publications in the cross-border area. This index is calculated for different technology-based sectors and compared to those in other knowledge-based areas.

Sources: OECD (2002), Redefining Territories: The Functional Regions, OECD Publishing, Paris,; OECD (2012), Redefining "Urban ”: A New Way to Measure Metropolitan Areas, OECD Publishing, Paris,; BAK Basel Economics (2008), Technological Top Region Benchmarking Report 2008, BAK Basel Economics, Basel, Switzerland.

A thorough analysis for the measurement of innovation functional areas requires indicators capturing knowledge and innovation flows as well as more basic indicators of integration. Flow indicators could refer to different areas of economic and innovation activities: R&D investments, research, innovation, tertiary education, skilled and R&D personnel as well as participation in research projects. Other than indicators capturing the thickness of flows and connections, measurement of proximity, balance and complementarities in industrial and scientific specialisation may be identified. Cultural and language linkages should also be considered and measured as factors enabling a favourable cross-border innovation environment. An example of a list of possible indicators is found in Table 1.3. Different statistics can be combined and used to develop indexes and composite variables measuring the stage of cross-border integration and co-operation, as in the case of the Oresund Integration Index (Figure 1.5, Annex 1.A2).

Table 1.3. Cross-border regional innovation system integration: Menu of possible indicators



Commuting linkages

Intensity and direction of commuting flows

Capturing the thickness of labour market connections and the directions towards the main centres of economic activity in the cross-border area

Transport and infrastructure connections

Measuring the type (roads, railways, airports) and the time/cost necessary to connect to different places

Residents from the neighbouring cross-border region

Measuring the degree of integration in the area as well as the degree of mobility of the workforce and the population in the area

Skills linkages

Student flows

Measuring the degree of integration of education and higher education systems

R&D personnel flows

Capturing the intensity of exchanges of innovation-related human capital

Employment specialisation by sector or scientific domain

Mapping the areas of employment specialisation of different sub-regions to highlight similarities, complementarities or differences

Science and technology linkages

Co-publications (total and by scientific domain)

Measuring the level of scientific collaboration among research institutions

Co-patents (total and by sector)

Measuring the level of technological collaboration among R&D centres, private organisations, etc.

Joint participation in EU FP7 or other international scientific projects

Measuring the intensity of collaboration among research organisations

Joint participation in R&D projects

Measuring the intensity of collaboration among research organisations

Business linkages

Firm specialisation in similar or different sectors by sub-region

Similar, different or complementary characteristics of the firm base in the different sub-regions of the cross-border area, capturing either ongoing or potential opportunities for collaborations

Linkages in the value chain

Type of relations along the business value chain in the cross-border area

Business co-operation linkages

Types and kinds of collaboration among firms in the area

Industry-science co-operation

Nature and intensity of co-operation between universities or research centres, on the one hand, and companies on the other, spanning over the area

Export linkages

Directions and intensity of export flows within the cross-border area

Cultural linkages

Percentage of people speaking and/or understanding languages in the cross-border area

Measuring the level of language integration

Number of joint cultural and entertainment events

Proxy for cultural integration across different areas

Tourism flows

Measuring both internal (cross-border tourism flows) and external attractiveness of the area (in-coming flow of tourists from outside the cross-border area)

Co-patents, which represent collaboration for inventive activity, are one of the innovation-related indicators used for assessing functionality for innovation. For example, analysis of co-patent data in Switzerland reveal the existence of a large functional area in northern Switzerland, spanning several cantons and extending over national borders to the north. 20 The three northern Grandes Regions in Switzerland (Espace Mittelland, North West Switzerland and Zurich) are all linked through co-patents to the same nearby foreign regions: Baden-Wurttemberg and Bavaria (Germany) and Alsace (France), accounting for 30-60% of foreign co-patents in those areas (OECD 2011d).21 Other examples of possible functional regions are observed in sectoral co-patenting trends, such as between Ontario, Canada and neighbouring US states or Alsace (France) with German regions (Ajmone Marsan and Primi, 2011).22 Such evidence was also found in the area of the TTR-ELAt, where much of co-patenting across borders was due to the multinational Philips that has branches and relationships in different parts of the cross-border area.

The Oresund Integration Index is an interesting example of a measurement for functionality in the cross-border area, albeit not specific to innovation activities only. The index was originally developed at the beginning of 2000s by the Oresund Chamber of Commerce. A new version of the index has been recently released by the Oresund Committee. Five groups of variables comprise the index addressing: i) labour market; ii) transport and communications; iii) housing market; iv) business; and v) culture (Figure 1.5, Annex 1.A2). The general index (a composite of these five sub-indices) shows a steep increase in integration until the year 2007, from 100 (for the base year) to 180; whereas, between 2007 and 2012, the index declined to 169. The lack of dynamism as reported by the integration indices is perhaps one of the reasons the region is looking for renewed political interest in cross-border support.

Figure 1.5. The Oresund Integration Index: Measuring cross-border functionality

Source: Oresund Committee (2013), Oresund Integration Index 2012.

Definitions of a cross-border area need to recognise variable geometry and avoid new borders

Definitions of an area may change over time. In some examples, the definition of the cross-border area may have been defined decades ago. However, industrial restructuring and the emergence of new technologies has radically changed the industrial landscape.

The creation of a new university may be an asset not considered before. Municipal reforms may change the political landscape. While not all changes are quick, the path dependency associated with such cross-border definitions can be strong, in part due to the significant time for building relationships and trust.

The need for variable geometry is also due to differences in specialisations. There are instances where, for particular projects, some parts of the cross-border area may have more or less of an incentive to engage. For example, a detailed study of the TTR-ELAt regions indicates the degree of specialisation by sub-region, illustrating why sub-regions may be more or less interested in collaboration depending on the topic (Figure 1.6).

Figure 1.6. Strengths in common sectors differ by sub-region across the TTR-ELAt

Competitive Index 2011 at NUTS 3 Level

Note: The index is standardised for 17 Western European countries (WE17) = 100. These maps are for illustrative purposes and are without prejudice to the status of or sovereignty over any territory covered by these maps.

Source: BAKBASEL, IBD (2012).

Variable geometry can also be necessary to allow flexibility in the application of the area definition, such as to involve an institution or firm not located in the defined area. The regions of Hedmark (Norway) and Dalarna (Sweden) have defined a cross-border functional area related to the tourism sector. However, for more general and broader innovation co-operation, it would appear more relevant for both regions to establish linkages with other domestic neighbouring regions, especially in the fields of ICT and biotech. In some other cases, innovation actors may establish relevant connections with organisations located further away, based on the nature and the excellence of actors rather than physical proximity, as it often happens in the case of higher education institutions (HEIs) and science and research centres. Some studies question if Centrope’s borders are adequately drawn given that the current definition excludes the scientific hotspots of the Czech Republic (Prague) and Hungary (Budapest) (Trippl, 2013). While most of the innovation-related flows between Estonia and Finland are between Tallinn and Helsinki, the University of Tartu is located outside of Tallinn but has many strong ties with Finland, particularly actors in Helsinki.

As a consequence, policies target different functional areas depending on the subject, the aim and the means of intervention, resulting in additional complexity. The same cross-border area may be the target of more than one policy programme, implemented by different authorities (local, regional, national and supra-national), and with different footprints. In the Bothnian Arc cross-border area, there are several small and large-scale cross-border efforts which overlap geographically in part or in whole with that definition (Box 1.6). The definition of the TTR-ELAt is similar to that of the Euregio Meuse-Rhine, but extends further to include more innovation-intensive cities and is therefore not identical. In Ireland and Northern Ireland, there are three border organisations managing European Territorial Co-operation cross-border programmes corresponding to three different segments along the border. This collaboration is further nested in the broader all-island cross-border area definition used by InterTradelreland - the bi-national agency for promoting trade and innovation (Figure 1.7).

Figure 1.7. Two definitions of the Ireland-Northern Ireland (United Kingdom) cross-border area

Note: These maps are for illustrative purposes and are without prejudice to the status of or sovereignty over any territory covered by these maps.

Sources: (left) Special EU Programmes Body; (right) Irish Academy of Engineering & InterTradeIreland (2010), Infrastructure for an Island Population of 8 Million, Engineers Ireland, Dublin.

Even within a cross-border area designated for innovation support, those administrative boundaries do not always correspond to the relevant areas for innovation activities. They may be either too big (when the activity is concentrated in only a part of the cross-border area), or too small (when the intensity of linkages is observed outside the defined perimeter of the cross-border area). In the Bothnian Arc cross-border area, the potential for innovation collaboration is mainly between the two cross-border hubs of

Oulu (Finland) and Lulea (Sweden), a subset of the area. The border towns also promote joint business development. In some cases different geometries for the relevant innovation area may co-exist: not all jurisdictions in the Oresund Committee are as equally engaged in the cross-border activities. For example, after a sub-national reform, the Danish part of the Oresund was split into two administrative regions. Interactions are strongest in the Capital Region of Denmark, but the much less innovation-intensive Zealand region remains part of the cross-border definition.

Box 1.6. The Bothnian Arc: Nested in several cross-border collaborations

There are several smaller scale cross-border initiatives that overlap in part or in whole with the Bothnian Arc’s efforts to support cross-border collaboration along the coast of the northern tip of the Bothnian Bay (Finland-Sweden):

  • Haparanda-Tornio: Co-operation takes place between two municipalities, Tornio (Finland) and Haparanda (Sweden) at the Finnish-Swedish border along the gulf. It focuses on physical planning, joint infrastructure and services (schools, fire and rescue services, district heating, etc.). This area is fully included in the Bothnian Arc space.
  • Torne Valley: This cross-border area gathers the 21 border municipalities and 80 000 inhabitants at the intersection of the Finnish-Swedish border to the north of the Bothnian Gulf. The focus of the co-operation is on cross-border labour mobility and business interactions. It overlaps with a small part of the Bothnian Arc.
  • North Calotte Council: The area includes the northernmost regions of Finland, Norway and Sweden. This area overlaps with the Bothnian Arc, mainly on the Swedish side, but excludes Oulu on the Finnish side.

In addition, three large EU-supported macro-regions are relevant for the Bothnian Arc actors. These regions, falling under the European Territorial Co-operation objective, address geo-strategic, transport infrastructure and environmental objectives. They include:

  • The Barents Euro-Arctic Region: This area includes the following regions: in Finland: Kainuu, Lapland and Oulu Region (North Karelia was granted an observer status in 2008); in Norway: Finnmark, Nordland and Troms; in the Russian Federation: Arkhangelsk, Karelia, Komi, Murmansk and Nenets; and in Sweden: Norrbotten and Vasterbotten. The majority (75%) of the population of the cross-border area lives in the Russian Federation.
  • Baltic Sea region: This macro-region covers Denmark, Estonia, Finland, Germany, Latvia, Lithuania, Norway, Poland, Sweden, North Western Russia and Belarus. The co-operation concerns spatial planning, infrastructure and environment.
  • Northern Periphery area: This very large area includes parts of Finland, Ireland, Sweden and the United Kingdom (Scotland and Northern Ireland) - in co-operation with the Faroe Islands, Iceland, Greenland and Norway. The whole of the Bothnian Arc is contained in this initiative. The Northern Periphery is part of the European Territorial Co-operation efforts aimed at supporting transnational co-operation among regions in Northern Europe.

Sources'. Nauwelaers, C., K. Maguire and G. Ajmone Marsan (2013), “The case of the Bothnian Arc (Finland-Sweden) - Regions and Innovation: Collaborating Across Borders”, OECD Regional Development Working Papers, No. 2013/17, OECD Publishing, Paris,; Hornstrom, L. and A. Tepecik Di§ (2013), “Crossing borders: Linkages between EU policy for territorial cooperation and Nordic cross-border cooperation”, Nordregio Working Paper, No. 2:2013.

The definition of a functional cross-border area for innovation therefore needs to avoid building unhelpful new borders. Rendering the definition of the area rigid is a way to create a new border. The goal is therefore to minimise the potential for relevant missed opportunities for co-operation on innovation. Multiple definitions of relevant functional areas targeted by policy intervention may apply to the same region. Programmes and instruments can refer to larger or smaller cross-border areas depending on different goals, topics and industrial sectors. Some form of flexibility with respect to openness of funding to include partners outside of the area can help overcome this inevitable, but hopefully more relevant, new border.

The type of functionality for innovation therefore depends on a wide range of “proximities”

Even when focusing only on a small contiguous cross-border area, many different situations of functionality are possible. These conditions depend on those factors driven by different forms of proximity (Box 1.2). The in-depth case studies illustrate variations along these factors that represent the different degrees of integration within the crossborder area influencing the innovation system (Table 1.4). In general, the degree of integration is easiest with the highest level specification noted in each category.

Table 1.4. Characteristics of innovation functionality for case study regions



Case study examples

Region settlement patterns (geographic proximity)

Metropolitan area

Network of small and medium-sized cities

Sparsely populated with small cites/towns

Helsinki - Tallinn; Oresund

TTR-ELAt (densely populated); Dublin and Belfast (within Ireland and Northern Ireland)

Hedmark-Dalarna; non-metropolitan Ireland-Northern Ireland; Bothnian Arc

Internal accessibility and flows (geographic proximity)




Oresund; TTR-ELAt

Helsinki-Tallinn; Ireland-Northern Ireland Bothnian Arc; Hedmark-Dalarna

Industrial and knowledge specialisations (cognitive proximity)

Similar with complementarities



TTR-ELAt; Oresund Bothnian Arc

Hedmark-Dalarna (tourism in common); Ireland-Northern Ireland (some common sectors such as agri-food); Helsinki-Tallinn (ICT, e-services in common)

Socio-cultural context (institutional proximity)

Very similar Somewhat similar


Ireland-Northern Ireland; Hedmark-Dalarna

Bothnian Arc; Oresund; Helsinki-Tallinn; TTR-ELAt (most subregions)

Innovation system interactions (multiple forms of proximity)

Pervasive Hub-to-hub On the border

TTR-ELAt; Ireland-Northern Ireland Bothnian Arc; Helsinki-Tallinn; Oresund Hedmark-Dalarna

Level of innovation development across border (cognitive proximity)

Balanced, strong Balanced, weak Unbalanced

Bothnian Arc; Oresund; TTR-ELAt Hedmark-Dalarna

Helsinki-Tallinn; Ireland-Northern Ireland

Region settlement patterns influence not only the dynamics of functional flows within the cross-border area, but also social and political considerations. The cross-border area can include big metropolitan areas, like in the case of two capital cities, a network of small and medium-sized cities, or perhaps be more sparsely populated with small cities and towns. The settlement pattern has a strong impact on the form of cross-border linkages both with respect to innovation and more generic economic co-operation. Case study examples characterised by predominantly metropolitan areas include the Oresund, Helsinki-Tallinn as well as the two main cities in Ireland and Northern Ireland respectively: Dublin and Belfast. When the focus is around one core metropolitan area, as opposed to collaboration between two hubs, the associated functional linkages such as those related to commuting and labour force dynamics render the innovation policy collaboration more obvious. Other case study areas were networks of cities or sparsely populated areas and therefore not centred around one or two core hubs.

Internal accessibility and flows are an important enabling condition for the development of a well-functioning cross-border regional innovation system. Students, researchers and skilled and innovation personnel all need to be able to meet regularly in order to establish and maintain long-lasting connections. Strong internal accessibility thus promotes knowledge exchange between innovation centres in a cross-border region. Moreover, good infrastructure connects the cross-border area to international hubs, a consideration for attracting mobile investments, high-level international events and skilled expatriates. Depending on the geographic scale and on the level of development of the transport infrastructure, the internal accessibility of the area can be strong, moderate or weak. Internal accessibility and flows are strong in areas like the Oresund and the TTR-ELAt and to a lesser extent Helsinki-Tallinn, where, respectively the bridge, a dense network of roads and good fast-boat connections help connect the various parts of the areas. The non-capital parts of Ireland and Northern Ireland have more complex internal accessibility via roadway for most areas, while the situations of the Bothnian Arc and Hedmark-Dalarna are characterised by much greater accessibility barriers.

Industrial and knowledge specialisations that are similar or complementary provide interesting opportunities for innovation collaboration. A cross-border area may be constituted by sub-regions with the same, different or complementary industrial, economic and knowledge specialisations. There is debate on the suitable degree of specialisation of the firm structure to support innovation. In this context, the term “related variety” implies a sufficient degree of proximity between knowledge bases that permits a deeper specialisation, with a sufficient degree of distance that offers opportunities for innovation-enhancing diversification (Asheim et al., 2011).

The case studies illustrate examples of the same, complementary or different specialisations and thus varying degrees of potential to benefit from collaboration opportunities. The two sides of the Bothnian Arc exhibit a very similar specialisation in ICT, energy technologies and wood and paper processing, suggesting strong potential to build greater critical mass for innovation in those sectors. Other areas like Hedmark-Dalarna share a common specialisation in winter ski tourism, and a goal of further developing summer tourism. The specialisations in other parts of the regions are very different and less amenable to functional linkages (biotech and farming on the Norwegian side and ICT and steel on the Swedish side). In Ireland and Northern Ireland, despite some similar specialisations in broad technological domains (like ICT, food or renewable energy), the different weight of the public sector in the two economies (higher in Northern Ireland than in Ireland) and the different industrial fabric composition (the greater concentration of multinational enterprises in the Dublin area vs. the predominance of SMEs elsewhere in Ireland and in Northern Ireland) make collaboration within those industrial and knowledge specialisations less spontaneous. The TTR-ELAt, the Oresund and Helsinki-Tallinn all show similar specialisations with some degree of distance, opening the door to complementarities in knowledge and innovation activities. Examples of niches with cross-border complementarities can be found in areas such as nanotechnologies with energy and health in the TTR-ELAt and in ICT and e-services in Helsinki and Tallinn. In the Oresund, the presence of multinationals, dynamic SMEs and leading higher education and research institutions on both sides of the border favour the development of connections on the basis of complementary expertise, such as in life science.

The socio-cultural context is important for the functionality of a cross-border area with respect to innovation, but that importance is often underestimated. The socio-cultural features of the cross-border area can be very similar, somewhat similar or different depending on the presence or not of common historical background, high or low language barriers, similar business and working culture, etc. Like accessibility issues, the socio-cultural context is an important enabling factor for a well-functioning business and innovation eco-system (Box 1.7). Ireland and Northern Ireland, thanks to the same language and a common historical background, can be considered to have a very similar socio-cultural context. However, this does not mean that the functional ties are fully in place, which the organisation InterTradeIreland, through the creation of “networks of trust”, seeks to change. The northern European case studies tend to have similar socio-cultural contexts with small differences in comparison with OECD countries. Languages are understood across the border and the business environment can benefit from a common Nordic culture of trust. But even in a cross-border area like the Oresund, cultural differences are often raised as an issue that was more important than initially thought. The different areas comprising the TTR- ELAt have some common socio-cultural characteristics, but notable differences in language and culture are present with particular sub-regions.

Language barriers, a key element of the socio-cultural context, are reported to be increasing in several cross-border areas. As students look to be relevant globally, they are more motivated to study English than the language of a neighbour. Furthermore, television habits have changed language acquisition skills, with the rise of English-based programming. In the TTR-ELAt, it is reported in parts of the Netherlands that French used to be a desired language in education, but is less the case today. The same challenge for mutual language comprehension is reported in the Oresund. While Denmark requires that school children learn Swedish, they are seeking more innovative ways of ensuring that language acquisition has a more lasting impact.

Innovation system interactions among firms, universities, technology centres and other actors are not always pervasive throughout a cross-border area. Those interactions may be intense in the whole cross-border area (pervasive interaction). They may also be limited to the main innovation hubs of the region (hub-to-hub interaction), or only concentrated at the border. These different kinds of interaction are due to the geography and accessibility features of the cross-border region and shaped by the role, characteristics and strengths of the different innovation system actors. Given the richness and the intensity of the linkages among innovation actors, both the TTR-ELAt and the Oresund can be considered areas where the interaction is pervasive: the degree of collaboration among research centres, universities and firms is high in many science, technology and innovation (STI) domains. In other cases, like the Bothnian Arc and Helsinki-Tallinn, the main potential for interaction is mostly concentrated between the hubs, typically the largest cities in the region. Between

Hedmark and Dalama, interactions are predominantly concentrated on the border and in a very specific sector (tourism). For more innovation-specific interactions, the other parts of two regions have connections with other areas.

Box 1.7. Socio-cultural distance an impediment to cross-border innovation efforts

Several studies have shown that mental and cultural borders tend to be long-lived and have a negative impact on cross-border relations. Van Houtum (1998) has demonstrated that mental distance (defined as the perception of differences between a foreign country and the home country with respect to business formalities and conventions and the perception of the consequences of these differences) is an important factor that can limit the frequency and number of cross-border economic interactions. Kratke (1999) has shown that communication barriers, fears of competition and a low trust environment are the main impediments to interaction in the German-Polish crossborder area (see also Matthiesen and Burkner, 2001) and Koschatzky (2000) has found that cultural and institutional barriers are key explanatory factors for the relatively low level of innovation interaction in the Baden (Germany)-Alsace (France) cross-border area. Hahn (2013) and Trippl (2013) have shown that differences in language, business and working cultures are constraining cross-border innovation in the Saar-Lor-Lux region and in Centrope.

Sources: Trippl, M. (2010), “Developing cross-border regional innovation systems: Key factors and challenges”, Tijdschrif voor Economische en Sociale Geografie, Vol. 101, No. 2, pp. 150-160; Van Houtum, H. (1998), The Development of Cross-Border Economic Relations, Center for Economic Research, Tilburg, Netherlands; Kratke, S. (1999), “Regional integration or fragmentation? The German-Polish border region in a new Europe”, Regional Studies, No. 33, pp. 631-641; Matthiesen, U. and H.-J. Burkner (2001), “Antagonistic structures in border areas: Local milieux and local politics in the Polish-German Twin City Gubin/Guben”, GeoJournal, No. 54, pp. 43-50; Hahn, C. (2013), “The transboundary automotive region of Saar-Lor-Lux: Political fantasy or economic reality?”, Geoforum, No. 48, pp. 102-113; Trippl, M. (2013), “Innovation networks in a cross-border context: The case of Vienna”, in: Van Geenhuizen, M. and P. Nijkamp (eds.), Creative Knowledge Cities, Edward Elgar, Cheltenham, pp. 273-302; Koschatzky, K. (2000), “A river is a river: Cross-border networking between Baden and Alsace”, European Planning Studies, Vol. 8, No. 4.

The level of innovation development across the border can be balanced, and thus more favourable for knowledge-intensive interactions, or imbalanced and interactions focus on price differentials. The level of innovation development can vary overall and according to specific S&T domains or innovation system actors. A significant imbalance in the level of innovation system actors or S&T domains can limit the functionality of the area. A strong level of innovation development on both sides of the border definitely facilitates the emergence of strong cross-border innovation linkages. However, this characteristic alone is not sufficient and depends also on the enabling environment and level of pre-existing cooperation. For example, all the sub-regions in the Oresund, the TTR-ELAt and the Bothnian Arc have reached an advanced stage of innovation development. However, some of these areas exhibit a greater intensity of cross-border innovation interactions (the TTR-ELAt and the Oresund) than others (the Bothnian Arc), the latter having greater accessibility challenges among other differences.

< Prev   CONTENTS   Source   Next >