REGIONAL INDUSTRIAL TRANSFORMATION AND KNOWLEDGE-INTENSIVE CLUSTERING: THE CASE OF THE NORTHERN SAVO REGION IN FINLAND

REGIONAL INDUSTRIAL TRANSFORMATION AND KNOWLEDGE-INTENSIVE CLUSTERING: THE CASE OF THE NORTHERN SAVO REGION IN FINLAND MIIKA VARIS 1 Department of Business and Management, University of Kuopio, P.O. Box 1627, FIN-70211 Kuopio, Finland; e-mail: miika.varis@uku.fi JARKKO PELLIKKA Savonia Polytechnic, P.O. Box 72, FIN-74101, Iisalmi, Finland; e-mail: jarkko.pellikka@savonia-amk.fi HANNU LITTUNEN Department of Business and Management, University of Kuopio, P.O. Box 1627, FIN-70211 Kuopio, Finland; e-mail: hannu.littunen@uku.fi Paper prepared for the 14 th Nordic Conference on Small Business Research, for the theme 'Entrepreneurs, clusters and innovation systems in contexts of local/metropolitan/regional development', May 11-13, 2006 Stockholm, Sweden Abstract In the new economic landscape, characterized by both globalization and regionalization and by the increasing importance of knowledge as a factor of production, the ability of firms and regions to develop and to adapt to changes in their external environment is closely related to the capacity to innovate and continuously renew the existing structures and knowledge bases. Dense concentrations of specialized knowledge-intensive activities are often considered as propitious environments for new innovations to emerge. The aim of this paper is to study regional industrial specialization and to identify emerging knowledge-intensive growth industries in a given region - in this case the Northern Savo region in Eastern Finland - that can be the target of policymakers efforts and serve as the drivers of change during the transformational phase of the regional industrial system. The paper also explores the role and possible tools of local policymakers in supporting and encouraging innovative activity and the growth of firms operating in the new knowledge-intensive industries. Theoretically we relate our study to the systems of innovation discussion that provides some useful insights with respect to how the transformation of existing organizational and institutional settings should be dealt with. Regional specialization and the existence of knowledge-intensive industries were analyzed by using the location quotient approach. Statistical analysis shows that the most growth-intensive industries in the Northern Savo region are manufacturing of textiles and clothes (LQ=6,3), forestry and forestry services (LQ=3,5), manufacturing of medical devices and instruments (LQ=2,5), and other manufacturing (LQ=2,4). 1 Corresponding author

Forestry and textile industry have traditionally played a significant role in the industrial activity in the region. However, manufacturing of medical devices and instruments and other knowledge-intensive manufacturing have continuously increased in their importance. The results can be thought to reflect a transitional phase in the region s industrial structure where the knowledge-intensive production in this case especially in the welfare sector - has a growing role. Keywords: regional industrial system, systems of innovation, regional economic and innovation policy, the Northern Savo region 1. Introduction The past years have been a time of significant change in terms of division of labor in industrial production at the global level. The emergence of a new knowledge-based (or, innovation-based) economy has emphasized the importance of both global and regional levels, instead of the more traditional national one, as the sources where innovation and economic growth primarily originate. Simultaneously, industrial countries have suffered from the loss of labor-intensive jobs when companies have moved their production to countries with lower labor costs. In longer term, this tendency will most likely lead to a decreasing competitiveness of regional economies that are relying on their traditional industrial structure and are unable to renew their existing industrial base by building strong agglomerations of knowledge-based industries. It is also apparent that smaller-scale regions cannot be the top players in all fields of the new economy but need to be more or less concentrated on industries supported by their existing or emerging specialized knowledge base. In this new economic landscape, the ability of firms and regions to develop and to adapt to changes in their external environment is closely related to the capacity to generate and utilize new knowledge, in other words, to innovate. Growing attention has thus been paid to the mechanisms facilitating innovation in firms, and, consequently, to the role of innovation policy in regional economic development. Geographical agglomeration of firms operating in the same or related industries, as well as the presence of organizations supporting their activities, is often considered to be propitious for the emergence of innovations. While this may not be axiomatic in all cases, we can relatively confidently assume that at least some sorts of benefits are gained through clustering geographically. The main aim of this paper is to study regional industrial specialization and to identify potential knowledge-intensive growth industries in a given region - in this case the Northern Savo region in Eastern Finland - that can be the target of policymakers efforts and act as the drivers of change during the transformational phase of the regional system of production and innovation. The paper also explores the role and possible tools of local policymakers in supporting and encouraging innovative activity and the growth of firms operating in the new knowledge-intensive industries. Theoretically we relate our study to the systems of innovation approach that provides useful insights with respect to how the transformation of existing organizational and institutional settings should be dealt with. The paper is organized as follows. The next section focuses on the SI concept and especially on the role of regional level authorities in designing and implementing policies to support the emergence and development of new knowledge-intensive

industries. The affect of geographical proximity - in terms of clustering and regional specialization - on innovative activity is also considered. The case region and empirical findings are presented in chapter 3. The main objective here is to identify possible growth industries within the knowledge-intensive sectors. Chapter 4 provides the conclusions. 2. The geography of innovation and knowledge-intensive clustering 2.1 The systems of innovation approach and regional development It has become widely recognized that technological innovation results from a complex, interactive and interdependent process - involving multiple actors and influences within dynamic systems - rather than exclusively from the internal research and development activities of firms. This systemic nature of innovations was already suggested in the works of Joseph Schumpeter (cf. Dosi, 1988) but it was not until the introduction of the systems of innovation (SI) concept in the mid 1980 s that this idea became more widely emphasized by scholars and also by economic development practitioners. Here, a process of innovation is suggested in which a number of economic agents interact with each other and with their external environment for searching and acquiring technological knowledge (Lundvall, 1992). While firms are still recognized as the key players in the process of innovation, their efforts in advancing technology seldom proceed in isolation but are notably influenced and supported by various external sources of knowledge, such as universities, research institutes, government agencies, and, of course, other firms. As a result of the emergence of a new knowledge-intensive economy, firms have become more and more dependent on external knowledge sources due to their incapability to generate all necessary knowledge on their own. Since various elements of uncertainty are also present in the innovation process, the firms also seek for external sources of techno-economic knowledge in order to understand the ongoing changes in their environment. Furthermore, the interaction with and learning from external knowledge sources implies that firms become more dependent upon decisions and actions made by other economic agents. As a result, a complex network of linkages is formed among firms and other organizations that can be considered as an interactive system of knowledge creation, transformation, and utilization. One result of the adoption of the SI approach is the increasing attention that has been paid to the role of regions as a source of economic development. Tödtling and Kaufmann (1999), for example, have suggested several reasons why SIs should actually be understood primarily as a regional level phenomenon. First, some important preconditions for innovation - e.g. the quality of labor force, the presence of educational institutions and of research organizations - are usually tied to specific locations and not very mobile, providing some regions innovation advantages. Second, firms operating in a particular industrial or technological field show a tendency to cluster on certain locations. When considering the importance of cooperation during the process of innovation, proximity is essential in reducing uncertainty and supporting the creation of trust-based relationships and the sharing of tacit knowledge between partners. Third, the interaction between knowledge producers and firms (such as links between university and industry), knowledge spillovers and spin-off activities are often localized since they work mainly through the mobility of persons on local labor markets and through personal interaction between actors.

Regions have also taken a more active role in designing and implementing technology and innovation policy. In many cases, an explicit objective of the policies is the creation or strengthening of regional industrial clusters. Moreover, as a result of the interactions between economic actors within a region, a shared technical and organizational culture, a trajectory, may develop. In favorable conditions this trajectory may support collective learning and innovativeness among actors belonging in a same technological field. However, certain risks are always present with this kind of path-dependent processes. When the local techno-economic structure and institutional framework become more and more established and homogenous, the learning capabilities of actors become, in turn, more and more limited. This may eventually lead to the incapability of both firms and their local economy to generate or adopt new knowledge and technologies. As a result of this negative lock-in situation, the viability of the whole local economic system may become seriously challenged. According to the systemic view of innovation, innovation and technology policies no longer focus exclusively on traditional issues such as increasing the inputs needed for R&D activities. Instead, emphasis has moved towards the improvement of the capacity of firms and other economic actors to operate and create linkages within a system, to access the external sources of techno-economic knowledge, and to increase their capacity to learn and innovate. Today, regional and local levels are of great importance in designing and implementing successful innovation and technology policies, also from the point of view of national economies as whole. As Storper (1995, 896) puts it, regional level " is an essential level at which technological synergies are generated and to which any national technology policy must therefore be addressed". While national governments do remain responsible for providing the broader framework - including general incentive systems, laws, regulations, and so forth - that has an important influence on the innovative activity, it is the regional and local level where the utmost decisions determining the future success of a region are made on the basis on the understanding of the local conditions. In the following, some possible policy issues arising from the SI discussion are considered. 2.2 Policy implications arising from the SI approach As noted earlier, it has become more widely recognized that the national level may not be the most suitable one for setting goals and policies for innovation-based economic development. Much emphasis is therefore placed on the capacity of regions, localities and cities to create structures and systems propitious for innovative activities. A number of reasons - both in terms of broader, national policy framework, as well as local level initiatives - can be found to support the view of the importance of innovation-based regional policy. First, technological change and innovations are essential for economic growth and development at both regional and national levels. Therefore, the support for innovation activity should be understood as a crucial element in regional policies. Second, regional innovation policy should be differentiated due to the variation in the nature of innovation processes between regions. The patterns of innovation processes may be different as a result of the regions firm and industry structure and are also influenced by different social and cultural environments. Third, it has become evident that universal policies do not exist. Since innovation appears often as a territorial phenomenon, the process of innovation is partly based on location-specific formal and tacit knowledge, as well as on norms and other informal institutions (Asheim & Isaksen, 1996).

What does the SI approach, then, suggest for the rationales for policy intervention? In general, there appears to be a significant expansion and qualitative change in policy guidelines when compared on those suggested by the earlier understanding of the nature of innovations. Although traditional issues, such as providing firms with material inputs for R&D activity, do not become insignificant, it must be recognized that, in utilizing these material resources, the immaterial aspects of innovation process - such as knowledge, technological capacity and absorptive capacity (see e.g. Cohen & Levinthal, 1990) - play a crucial role. These immaterial resources are often tied to specific firms, organizations and locations, indicating that they can be used as competitive advantages in the global competition (Nauwelaers, 2001). While the organizational environment - i.e. the presence of knowledge providers, financial organizations, etc. - of firms is of great importance for innovation, also the significance of informal institutions in innovation systems was acknowledged in the seminal works of both Freeman (1987) and Lundvall (1988). However, the visibility of organizations and formal institutions, i.e. laws, regulations and policies, may mean that the importance of informal institutional factors can easily be overlooked, though they may actually exceed the organizational issues in significance. For example, in a situation where the general attitude towards entrepreneurship is negative, it may be difficult to commercialize research through high technology start-ups. Therefore, the creation of propitious entrepreneurial culture is an important yet a difficult challenge for local governments and other actors devoted to local economic development. When firms and other local organizations face problems in their co-operation, intermediary organizations within the SI - such as applied research institutes and research associations - may also have a significant role as bridge-builders or facilitators between elements of the system. These intermediaries work typically with actors that have very limited levels of learning and absorptive capacity and are therefore facing problems when they should communicate directly with universities or other providers of latest scientific knowledge (see e.g. Asheim & Isaksen, 1996; Shane, 2002). It should also be noted that in a SI a number of bottlenecks may exist that can constitute crucial obstacles to regional economic growth and development. As noted by Edquist (2001), the traditional notion of market failures loses its meaning and applicability when considering systems characterized by fundamental disequilibrium and processes showing evolutionary characteristics. In this context other types of failures exist, often referred to as "systems failures" (OECD, 1996), requiring interventions very different from those based on the traditional assumptions. Systems failures can appear in the form of inertia and negative lock-ins and may relate, for example, to problems in the actors' interactions in the SI, to the inability of potential innovators to act in their own best interests, to the reconfiguration of institutions, and to the cultural and institutional framework conditions. Since systems failures are heavily dependent upon the interplay of characteristics in a given system, a key challenge for local policy-makers is the continuous identification and analysis of these failures. It is essential to identify the elements of the system that are subject to inertia or have become locked in to trajectories and structures that are inappropriate, so that real deficiencies can be addressed and dealt with (see e.g. North, 1990). Because the characteristics of individual systems change during their development, no universal best practices exist that could be discovered through, for example, benchmarking. Uncertainty is a fundamental property of the modern economy, implicating that the ex ante identification of the most suitable policy tools is not possible. As Edquist (2001) points out, due to the uncertainty of future outcomes of public interventions,

we can only afterwards evaluate whether the problems initially identified were solved or not. This further implies that political failures cannot be completely avoided and that they must be accepted as a natural consequence of uncertainty. The complexity that the SI approach brings to innovation policy requires the policy process itself to become knowledge-intensive. Therefore, the competencies of local policymakers become even more important. Innovation policy should also be understood as experimental: policymakers must have the courage to try new policy tools when needed. Also the role of academic research is important as a provider of basic theoretical frameworks and concrete policy suggestions. It must be stressed that it may be difficult for authorities to translate insights from theoretical discussion into concrete policies. In the words of Lovering (1999), "as a general guide to policy [the existing literature on regional economic development] is somewhere between ambivalent and inappropriate Regional development is changing uncontrollably, and prevailing theories and dominant policy institutions have little grasp either of what is going on, or what to do about it." 3 The empirical study 3.1 The case region In what follows, the empirical part of the study is presented. Before examining the findings, a brief description of our case region is given. The Northern Savo region is located in Eastern Finland. With 250,000 inhabitants it is the sixth largest county in Finland. The regional center Kuopio is the eighth largest city in Finland with more than 90,000 inhabitants and for natural reasons can be considered as the locomotive of the whole region s development, especially what comes to high-tech industries. Traditionally, Kuopio has been an administrative and university city with comparatively little industrial activity. The high level research in the region is concentrated in the science valley of Kuopio where the university is also located. Since its foundation in 1966, the University of Kuopio has been one of the most clearly profiled of Finnish universities. The focus of research and education has been on health and environment sciences and later also on the related fields such as biosciences and biotechnologies (Goddard et al., 2003). The main areas of research are biotechnology, molecular biology and medicine, chronic illnesses such as diabetes, cardiovascular diseases, musculoskeletal diseases and cancer, applied research on the environment and its health effects, drug development, the biological effects of drugs, social and health services, health economics, and clinical nutrition health care technology. Today, the city of Kuopio is an internationally recognized center of expertise on health and environmental sciences. Relying on the existing fields of expertise, the region aims to become one of the leading European centers of excellence in welfare expertise. The long-term history of the main fields of research provides also promising potential for the creation of new product and service innovations and new technology-based businesses. In order to reach these objectives, the regional Employment and Economic Development Center and the Regional Council of Northern Savo started designing the regional technology policy program that was completed in November 2001. The main objectives were, first, to identify the strengths and future potential of local technologies, second, to contribute to the profile of the regional industry, third, to start a continuing strategy process targeted to the relevant allocation of the resources for developing the regional innovation system and,

finally, to commit the regional policymakers to the strategy process and its implementation. Regional technology policy is a part of the cluster-based industrial strategy that directs the regional development activities. One concrete example of the efforts to develop regional welfare industry, "The Health Kuopio program", was started in June 2002. The program aims to support the creation of new services and products, high-level technological innovations, and also new business start-ups and jobs. The parties involved in the program are local firms, the University of Kuopio, the Northern Savo Polytechnic, Kuopio Technology Center Teknia Ltd., the Kuopio University Hospital, the Northern Savo Regional Consortium for Education, the city of Kuopio and other communities in the region, and a number of third sector organizations. This program aims to create over 5,000 new jobs and 150 new business start-ups by the end of the year 2012. The overall costs of the program are 180 million euros. Since the region has a clear profile with regard to its high-tech industrial development, it was in our interest to find out whether this specialization has also lead to concrete results, considering economic development and regional industrial structure. In the following, the design of the empirical study and the findings are presented. 3.2 The identification of regional specialization in the Northern Savo region In order to identify possible concentrations of knowledge-intensive industries in our case region, we performed a quantitative analysis of data supplied by the Statistics Finland (see Littunen & Tohmo, 2002). The principle data sources used in this analysis are the following registers of statistics: 1) The registers of firms and places of business - The number of firm start-ups and closures in different regions (1995-1999) - The places of business, personnel, and the rate of turnover in the different branches and regions (1995-1999) 2) The structural register of the industry and construction - The places of business and rate of exportation in regions and industries (1995-1999) - The added value increase of the industries in different regions (1995-1999 In addition, a statistics of the high growth firms was formulated on the basis of the registers described above. This statistics was made in order to provide information of the regional and branch-related differences of the high growth firms. Here, a high growth firm was defined as a firm whose turnover had increased a minimum of 100 % during the years 1995-1999. The other group of firms was constituted by firms whose turnover had increased less than 100 % during the same time period and whose turnover in 1999 was more than 0.84 million euros. The firms whose turnover in 1999 was less than 0.84 million euros were removed from the data (see e.g. Smallbone et al., 1995). It should be noted that also the firms that operated (in year 1995 or 1999) in more than one region were also removed from the data.

In this study, a regional growth industry is defined on the basis of the increase of the firms turnover and the relative share of personnel. The regional structure of the industry was examined by using absolute measures (personnel, rate of turnover, and places of businesses). Regional specialization and the existence of knowledge-intensive industries were analyzed by using the location quotient (LQ) approach that is one of the most frequently used measures of industrial specialization or clustering. A LQ is calculated by dividing an industry s share of the total labor force in the region by that industry s share of the total labor force in the whole country. If the share of the industry in a region is the same as the average of all regions in the country the statistic equals 1. If the statistic is greater than 1 then the share of the industry in a region is higher than the average of all regions and the region can be considered as specialized in that particular industry. If the statistic is lower than 1, the share of the industry in a region is lower than the average of all regions and the region is not specialized in that particular industry. It should be noted that a high LQ alone is not an implication of regional clustering of small firms but may rather be due to a dominant branch plant. Also, the high value of the LQ only indicates specialization relative to other industries in the region and not necessarily the size of the sector relative to other regions. 3.3 Findings Statistical analysis indicates that, measured by labor force, definite regional specialization can be identified in some industries, particularly in the manufacturing of textiles and clothes (LQ=2,5), manufacturing of timber and wood products (LQ=2,2), agriculture, hunting and forestry (LQ=2,2), and mining of minerals (LQ=2,2), see Table 1. Among the most important regional branches, in terms of personnel level, there are not presented any knowledge-intensive (in this case, university-related) industries. This indicates that during the time period in question, these were not notable employers in the region. Table 2 shows that the most growth-intensive branches of industry in the Northern Savo region are manufacturing of textiles and clothes (LQ=6,3), manufacturing of medical devices and instruments (LQ=2,5), forestry and forestry services (LQ=3,5), manufacturing of timber and wood products (LQ=1,6), manufacturing of non-metal mineral products (LQ=1,6) and other manufacturing (LQ=2,4). The results can be construed expressing signs of a transitional period where the more traditional industries remain important but where the new knowledge-intensive production and manufacturing, although not being a major employer, has a growing role. Wood and textile industries have traditionally been an important part of the industrial and commercial activity in the Northern Savo region. However, manufacturing of medical devices and instruments and other knowledge-intensive manufacturing have continuously increased in their importance in the region. The policy implications deriving from the analysis are multiple though not unambiguous. First, although the analysis of the statistical figures underlines the substantial growth of knowledge-intensive industries in the region, it should be noted that the levels of export and turnover in these sectors are still quite modest. The average size of the firms in the new industries is relatively small, referring to the early development phase of the industries, and also indicating the challenges new firms face in commercializing and transforming university research and development into successful business and market-competent products.

Table 1. The most important branches in the Northern Savo region based on personnel level The Northern Savo Region, personnel BRANCH HL 1999 Change 95-99 Proportion 99 LQ99 LQ99- LQ95 Agriculture, hunting and forestry 1714 39.6 % 3.8 % 2.2 0,58 Mining of minerals 333-23.1 % 0.7 % 2.2-0.69 Food, beverages and tobacco manufacturing 1710-9.2 % 3.8 % 1.3-0.06 Manufacturing of textiles and clothes 1218 19.2 % 2.7 % 2.5 0.64 Manufacturing of timber and wood products 2241 16.1 % 5.0 % 2.2 0.22 Manufacturing, publishing and printing of pulp 2202-1.3 % 4.9 % 0.9-0.07 Manufacturing of base metal and metal products 2349 9.0 % 5.2 % 1.2-0.12 Manufacturing of machines and devices 1874 19.7 % 4.2 % 0.9 0.13 Electric, gas and water maintenance 997 106.8 % 2.2 % 1.0 1.21 Construction 4014 42.1 % 8.9 % 1.0-0.01 Wholesale and retail trade 7931 5.6 % 17.6 % 1.0-0.08 Hotels and restaurants 2017 18.5 % 4.5 % 1.1-0.02 Transport, storage and communications 5486 19.7 % 12.2 % 1.0-0.02 Financing 1426-10.8 % 3.2 % 1.0 0.04 Real estate, renting activities and research services 4033 23.8 % 8.9 % 0.7-0.08 Healthcare and social services 1048 28.7 % 2.3 % 1.3-0.08 Other social services and personal services 1158 36.6 % 2.6% 0.8 0.05 HL1999 Change95-99 Proportion99 LQ99 LQ99-95 = Personnel (1999) = Proportional change of personnel 1995-99 (%) = Proportion of personnel in all branches 1999 (%) = Value of the location quotient (1999) = Change in location quotient (1995-99) Source: Modified from Littunen & Tohmo (2002, 153) During thefirst EU programme period of Finland (1995-1999) the Northern Savo region s economic development policy was based, on the other hand, on strengthening the existing strong industrial sectors, and on the development of new innovationbased sectors, on the other (Littunen & Tohmo, 2002). However, it is noteworthy that at the time the region s development strategy stressed relatively modestly the importance of new industrial sectors but was rather focused on the development of traditionally important (and related) sectors, such as forestry, wood energy, food industry, tourism, and also metal industry, although the latest has not been one of the strong sectors in the region and can thus be seen as an effort to diversify the regional industrial structure. Supporting the region s existing strong industries is, of course, reasonable from the viewpoint of employment and economic growth. Renewal of the industrial structure is, on the other hand, important for the future prospects of many regions in industrialized countries. What comes to our case, the direction seems to be right. After the time the data of this study was gathered, significant efforts have been taken to

develop new industrial sectors and to commercialize university-based knowledge (see Chapter 3.1). Table 2. The growth firms in the Northern Savo region, their importance in different branches and firm start-ups and closures (1995-1999) Growth firms 1995-99 Other firms 1995-99 Firm start-ups Firm closures LQ BRANCH qty Person nel qty qty Person nel qty Agriculture, hunting and forestry 27 94 96 452 254 193 1,9 Forestry and forestry services 19 69 75 285 125 97 3,5 Mining of minerals 8 18 14 40 41 31 1,8 Industry 107 1210 279 4234 597 541 1,3 Manufacturing of textiles and clothes 8 97 20 567 126 87 6,3 Manufacturing of timber and wood products 18 185 31 589 89 95 1,6 Manufacturing of non-metal mineral products 7 80 12 157 20 13 1,6 Manufacturing of base metal and metal products 22 190 55 718 82 68 1,2 Manufacturing of machines and devices 13 199 43 453 54 60 1,3 Manufacturing of electro-technology products 9 187 20 218 28 22 1,1 Manufacturing of medical devices and instruments 7 135 13 127 16 8 2,5 Other manufacturing 9 155 21 248 63 55 2,4 Construction 126 838 245 1276 591 548 1,1 Wholesale and retail trade 128 570 656 2869 1348 1402 1,0 Hotels and restaurants 18 89 117 475 400 352 0,8 Transport, storage and communications 73 307 277 1225 318 356 0,9 Real estate, renting activities and research services 112 487 209 1003 873 641 0,7 Real estate services 34 112 54 373 110 112 1,3 Research and Development 1 17 - - 10 4 3,6 Other services for private sector 66 331 136 543 611 435 0,6 Health care and social services 18 49 128 510 150 81 0,8 Other social services and personal services 14 32 57 318 403 284 0,5 All branches, total 640 3715 2096 12466 5086 4476 LQ= Proportion of personnel in the high growth firms in the region / Proportion of personnel in the high growth firms in Finland Source: Modified from Littunen & Tohmo (2002, 154) 95-99 qty 95-99 qty 4. Concluding remarks In this paper, regional industrial specialization and the emergence of new knowledgeintensive growth industries in the Northern Savo region were studied. The results show that the region still relies largely to its traditionally strong industrial sectors. However, there are signs that new knowledge-intensive sectors are getting a toehold in the region and rising in their relative importance. Whether the tendency has continued and even strengthened, after major efforts have been taken to develop the

welfare industry in the region, would be a subject of a new study with more recent data. Even if the basic elements for industrial renewal - basic and applied research, financial institutions, commercialization services, etc. - seem to be in place, they may still work inefficiently as a whole. Since modern processes of innovation and commercialization involve a great number of different actors and functions, it is essential for local level authorities to somehow coordinate the different components of an innovation system. This may be challenging, especially when dealing with completely new industries whose special characteristics and needs are not sufficiently known. As is evident from the literature, innovation systems show different characteristics and involve different actors in different industries. The fact that different regional systems of innovation show notable differences that tend to be associated with their individual paths of specialization in production and technologies has some important policy implications. One of the main issues is that universally applicable policies do not exist but, on the contrary, policies aiming to contribute regional innovation activity and economic development should be designed on the basis of location-specific characteristics. The patterns of innovation processes vary between regions, depending on their industry structure that affects what is done and therefore what is learnt in a given region. Furthermore, despite of the presence of globalization forces in the modern economy, the process of innovation is tied on the particular knowledge base of a region that is the result of, and affected by, specific historical developments. The systemic approach to innovation also suggests a strong role for other non-material factors in the process of innovation. Many of these factors can be defined as institutions and include, for example, norms, behavioral rules and cultural factors, that both support and constrain human activity and thus affect the way things are done. Therefore, effective policy interventions must be based on the study of localized innovation processes, organizations and institutions over extended periods of time. References Asheim, B.T. & Isaksen, A. (1996) 'Location, agglomeration and innovation: Towards regional innovation systems in Norway?' STEP Report series R-13. Cohen, W.M. & Levinthal, D.A. (1990) 'Absorptive Capacity: A New Perspective on Learning and Innovation'. Administrative Science Quarterly, Vol. 35, pp. 128-152. Dosi, G. (1988) 'The nature of the innovative process', in G. Dosi, C. Freeman, R. Nelson, G. Silverberg & L. Soete (eds.), Technical Change and Economic Theory, Pinter, London, pp. 221-238. Edquist, C. (2001) 'Innovation Policy - A Systemic Approach', in Archibugi, D. & Lundvall, B-Å. (eds.), The Globalising Learning Economy: Major Socio-Economic Trends and European Innovation Policy. Oxford University Press, Oxford. Freeman, C. (1987) Technology and economic performance: Lessons from Japan. Pinter, London. Goddard, J., Asheim, B.T., Cronberg, T. & Virtanen, I. (2003) Learning Regional Engagement: A Reevaluation of the Third Role of Eastern Finland Universities. Publications of the Finnish Higher Education Evaluation Council 11: 2003. Littunen, H. & Tohmo, T. (2002) KTM:n hallinnonalan EU-hankkeiden suhde maakuntastrategioihin. Ohjelmakauden 1995-1999 toimialakohtainen tarkastelu. Kauppa- ja teollisuusministeriön tutkimuksia ja raportteja 16/2002, Helsinki. Lovering, J. (1999) 'Theory led by policy: The inadequacies of the new regionalism (illustrated from the case of Wales)'. International Journal of Urban and Regional Research, Vol. 23, No. 2, pp. 379-395. Lundvall, B.-Å. (1988) 'Innovation as an interactive process: From user-producer interaction to the

national system of innovation', in G. Dosi, C. Freeman, R. Nelson & L. Soete (eds.), Technical change and economic theory, Pinter, London pp. 349-369. Lundvall, B.-Å. (1992) National systems of innovation Towards a theory of innovation and interactive learning. Pinter, London. Nauwelaers, C. (2001) 'Path-Dependency and the Role of Institutions in Cluster Policy Generation', in Å. Mariussen (ed.), Cluster Policies Cluster Development? Nordregio Report 2001:2, Stockholm, pp. 93-107. North, D.C. (1990) Institutions, Institutional Change and Economic Performance. Cambridge University Press, Cambridge. OECD (1996) 'The OECD Jobs Strategy: Technology, Productivity and Job Creation', Vol. 2. OECD, Paris. Shane, S. (2002) 'Executive Forum: University Technology Transfer to the Entrepreneurial Companies'. Journal of Business Venturing, Vol. 17, pp. 537-552. Smallbone, D., Leigh, R. & North, D. (1995). The characteristics and strategies of high growth SMEs. International Journal of Entrepreneurial Behaviour and Research 1 (3), 44-62. Storper, M. (1995) 'Regional technology coalitions: An essential dimension of national technology policy'. Research Policy, Vol. 24, pp. 895-911. Tödtling, F. & Kaufmann, A. (1999) Innovation systems in regions of Europe - a comparative perspective. European Planning Studies, Vol. 7, pp. 699-717.