VILNIUS GEDIMINAS TECHNICAL UNIVERSITY
ENTERPRISE ECONOMY AND MANAGEMENT DEPARTMENT
AN EXAMINATION OF INDUSTRY CLUSTERS
Made by: VVu-2 Aleksandra Baloban
Checked by: dr. R.Korsakienė
DEFINITION OF INDUSTRY CLUSTER 3
IDENTIFICATION OF INDUSTRY CLUSTERS 6
FACTORS DRIVING INDUSTRY CLUSTER GROWTH AND DEVELOPMENT 7
INDUSTRY CLUSTER POLICIES 8
EVALUATION AND CRITIQUE OF INDUSTRY CLUSTER POLICIES 10
ADVANTAGES AND DISADVANTAGES OF CLUSTERS 11
CLUSTERING IN LITHUANIA 13
Region clustering dimention and cluster types variety in Lithuania 13
Clastering level in different industry brabchesand sectors of Lithuania 14
Clusters are a nebulous concept. It covers a variety of business structures and is used for
different purposes. Industry cl
Given the interest in innovative economic development strategies by both the public and private sectors, industry cluster policies have received significant attention in current literature. However, there is considerable deeebate regarding the actual definition of an industry cluster, how to identify an industry cluster, or what factors drive the development of an industry cluster. The literature focuses on the different definitions of industry clusters, and much of the literature isss case studies illustrating different types of clusters. A second focus in the literature is the identification of industry clusters. Given the many variations in the definitions of clusters, it is not surprising that there are several different approaches to identifying clusters. A third common theme in the literature is cluster policy, and how these policies can be incorporated into economic development programs.
This paper summarize the key literature on the issues mentioned above, focusing specifically on the definition and identification of industry clusters, the factors driving cluster development, and cluster policy in the United States. The last section describes attempts to evaluate industry clusters, as well as criticisms of clusters as an economic development tool. While there is ample literature onnn industry clusters in Europe, where cluster policy is more advanced, this literature review focuses primarily on the use of the concept in the United States.
DEFINITION OF INDUSTRY CLUSTER
Clusters are a nebulous concept. It covers a variety of business structures and is used for
different purposes. Therefore, there are numerous different definitions but almost all of them
share the idea of proximity, networking and specialisation.
The very basic definition of an industry cluster is “geographical concentrations of industries that gain performance ad
Michael Porter popularized the concept of industry clusters in his book The Competitive Advantage of Nations (1990). Porter developed the “Diamond of Advantage,” which is four factors he determined create a competitive advantage for firms. The four corners of the diamond include factor conditions, demand conditions, industry strategy/rivalry, and related and supporting industries.
“Diamond of Advantage”
Porter used this diamond to determine which firms and industries had competitive advantages, and his emphasis of the importance of related and supporting industries encouraged interest in clusters. While his original thesis was applied to nations as a whole, Porter recognized that the majority of economic activity takes place at the regional level. Thus, his ideas are commonly applied to cities and regions.
The bulk of Porter’s thesis deals with the competitive advantages of clustering for industries. This aspect of his work is discussed in the Section III. Porter provides a simple definition of two types of clusters: vertical clusters, and horizontal clusters.
Vertical clusters are made up of industries that are linked through buyer-seller relationships. Horizontal clusters include industries which might share a common market for the end products, use a common technology or labor force skills, or require similar natural resources (Porter 1990).
On the common, the theory of industry clusters of Porter sound like this:
“Clusters are geographically close groups of interconnected companies and associated institutions in a particular field, linked by common technologies and skills. They normally exist within a geographic area where ease of communication, logistics and personal interaction is possible. Clusters are normally concentrated in regions and sometimes in a single town”.
In FINAL REPORT OF THE EXPERT GROUP ON ENTERPRISE CLUSTERS AND NETWORKS of European commission all expert group members had come to common definition of clusters. They
proposed to use as a working tool for this project the definition of Porter, to which they added
few finer points:
“Clusters are groups of independent companies and associated institutions that are:
_ Collaborating and competing;
_ Geographically concentrated in one or several regions, even though the
cluster may have global extensions;
_ Specialised in a particular field, linked by common technologies and skills;
_ Either science-based or traditional;
_ Clusters can be either institutionalised (they have a proper cluster manager)
The cluster has a positive influence on:
_ Innovation and competitiveness;
_ Skill formation and information;
_ Growth and long-term business dynamics”.
Jacobs and DeMan (1996) and Rosenfeld (1996,1997) present more in-depth discussions of the different definitions of industry clusters, although these authors also use the definitions of vertical and horizontal clusters as the basis for their definitions. Jacobs and DeMan (1996, pg.425) argue that “there is not one correct definition of the cluster concept.different dimensions are of interest.” They expand from the definitions of the vertical and horizontal industry clusters to identify key dimensions that may be used to define clusters. These include the geographic or spatial clustering of economic activity, horizontal and vertical relationships between industry sectors, use of common technology, the presence of a central actor (i.e., a large firm, research center, etc.), and the quality of the firm network, or firm cooperation (Jacobs and DeMan 1996).
In addition to vertical and horizontal relationships, Rosenfeld (1997) includes criteria for defining a cluster, including the size of the cluster, the economic or strategic importance of the cluster, the range of products produced or services used, and the use of common inputs. He does not encourage defining clusters exclusively by the size of the constituent industries or the scale of employment, pointing out that many effective clusters are located in small inter-related industries which do not necessarily have pronounced employment concentrations. According to Rosenfeld (1997 pg.10), an industry cluster is: “a geographically bounded concentration of similar, related or complementary businesses, with active channels for business transactions, communications and dialogue, that share specialized infrastructure, labor markets and services, and that are faced with common opportunities and threats.” Rosenfeld’s definition clearly emphasizes the importance he places on the role of social interaction and firm cooperation in determining the dynamic nature of a cluster.
As evidenced in the literature cited above, there are several common themes in the definition of an industry cluster. First, it is generally agreed that clusters are a dynamic phenomenon.
Secondly, most of the definitions of industry clusters reference the geographic scope of the cluster, and the importance of spatial proximity. A third common theme in the literature is the importance of looking beyond individual industries and recognizing that individual firms are part of a much larger industrial system. Lastly, the role of social infrastructure in defining industry clusters is a theme prevalent in the literature.
IDENTIFICATION OF INDUSTRY CLUSTERS
The varying definitions of industry clusters help explain the differing arguments regarding the methodology to identify clusters. One of the common approaches to identifying clusters is based on quantitative techniques, including location quotients and input-output (I-O) analyses (Rosenfeld 1997). These tools help identify relative concentrations of industries in the region, as well as identify the buyer-seller linkages in different industry sectors. Michael Porter relied heavily on this type of analysis to form the basis of his international study of industry clusters. I-O analyses and other quantitative tools were also the basis for identifying clusters in several other studies, including the Twin Cities Industry Cluster Project (State and Local Policy Program 1998) and UNC-Chapel Hill’s study of North Carolina’s industries (Bergman, Feser and Sweeney 1996).
The quantitative approach towards identifying industry clusters is generally regarded as a critical component of a cluster analysis. This type of analysis will provide an initial tool for identifying potential clusters and will indicate the relative presence of different industries in the local region. An I-O analysis is especially useful in the analysis of a vertically-integrated cluster, when the buyer-seller linkages are more obvious. However, the quantitative analysis does not address whether relationships really exist between the individual firms, and it does not account for other factors beyond the product-market relationships, such as industry collaboration and information flow (Doeringer and Terkla 1995, Jacobs and DeMan 1996, Rosenfeld 1996,1997). “Although inter-industry transactions incorporated within production channels can sometimes be detected in input-output tables, neither the character or relationships among firms nor the benefits of clustering can be discerned in this way (Doeringer and Terkla 1995, pg.228).”
There is a general consensus in the literature that in order to truly identify industry clusters it is necessary to conduct a qualitative analysis in addition to the quantitative analysis. Surveys and interviews of key industry representatives will help expand an understanding of the buyer-supplier relationships, as well as further identifying commonalties between industries (i.e., workforce or infrastructure needs, or technologies used). The use of the qualitative analysis will both confirm the findings of the quantitative analysis, as well as help identify potential industry clusters that may have been overlooked by the conventional data analysis (Doeringer and Terkla 1995, Jacobs and DeMan 1996, Sternberg 1991, State and Local Policy Program 1998).
FACTORS DRIVING INDUSTRY CLUSTER GROWTH AND DEVELOPMENT
The factors which drive industry cluster development and growth are also the subject of debate in the literature. In general, businesses locate where it makes the greatest economic sense, either in terms of accessing the market for their product, the labor pool, or required resources. The basic factors that drive industry clustering are very similar to the factors that encourage urban or locational agglomeration economies. As stated by Doeringer and Terkla, “The presence of positive externalities explains the clustering process, whereas specific location sites for each cluster depend on either ‘historical accident’ or the cost advantages provided by immobile factors that attracted the firms anchoring the cluster (Doeringer and Terkla 1995, pg.226).” While there is consensus among the researchers that firms will cluster because they receive some type of benefit, the factors that create those benefits are debated.
Michael Porter (1990) argues competition is a driving force behind cluster development. Clustering is a dynamic process, and as one competitive firm grows, it generates demand for other related industries. As the cluster develops it becomes a mutually reinforcing system where benefits flow backwards and forwards throughout the industries in the cluster. Porter argues that it is the competition between rival firms in the cluster that drives growth because it forces firms to be innovative and to improve and create new technology. This, in turn, leads to new business spin-offs, stimulates R&D, and forces the introduction of new skills and services. Because many of the industries within the cluster employ a similar labor force, the labor force can freely move to other related firms within the cluster, thus transferring knowledge to new firms, and continuing to promote competition and therefore growth. This growth can either lead to increasing the vertical integration of the cluster, or it can lead to the horizontal integration of the sector. Increased vertical integration occurs as the division of labor gets more specialized, and new firms are able to fill the new niche markets. Horizontal clustering occurs as the new technology and labor skills are applied to related industries in different sectors. Porter points to Silicon Valley as an example of how competition has spurred the horizontal clustering process.
There are several other key factors that are discussed in the literature that contribute to cluster development. Doeringer and Terkla (1995) cite the benefits of agglomeration economies observed in industry clusters as one factor leading to cluster development. Firms locating in close spatial proximity benefit from lower transportation and transaction costs, as well as access to a skilled labor force. Agglomeration economies can also spur competition, which encourages information, knowledge, and technology transfer among related firms. The transfer of knowledge and technology among firms can lead to new industry growth, and therefore helps drive the overall growth of the cluster.
Face-to-face interaction is also cited in several of the sources as a critical factor in cluster development (Doeringer and Terkla 1995, Rosenfeld 1997). This interaction is most beneficial to small, specialized firms which have the flexibility to fill emerging niche markets as final demand or technology changes (Doeringer and Terkla 1995). Local proximity to firms in all aspects of the production process, such as the suppliers, machine builders, assemblers, distributors, and final customers allows the cooperating firms to adopt new technology and innovations rapidly, therefore increasing the overall efficiency of the production process. The firms collaborate to provide specialized services; through this collaboration, clusters develop (Rosenfeld 1997). The social infrastructure within the cluster helps facilitate technology and knowledge transfer, which strengthens the cluster and promotes future growth. The importance of face-to-face interaction is cited in Rosenfeld’s case studies of the furniture industry in Mississippi and the apparel/hosiery industry in Northern Italy (Rosenfeld 1997). Saxenian also discusses the importance of this interaction in the growth of Silicon Valley, and attributes much of the early success of the area to the social infrastructure (Saxenian 1994).
In summary, cluster development is attributable to several key factors, including technology transfer, knowledge transfer, development of a skilled labor force in related industries, the benefits of agglomeration economies, and social infrastructure. However, researchers differ on how these factors promote cluster growth. On the one hand, Porter attributes cluster development and growth to competition, and focuses on how these key factors drive competition (Porter 1990). On the other hand, the other authors cited above, say cluster development is promoted by collaboration among related firms that is encouraged by face to face contact. Through social interaction, technology and knowledge transfer occurs, therefore leading to the development and growth of clusters.
INDUSTRY CLUSTER POLICIES
Traditional economic development policy has focused on the individual needs of specific firms and industries. Cluster policies deal with firms and industries as a system. Proponents of cluster policies focus on developing a strategy that will encourage an efficient allocation of limited resources available for urban and regional economic development, provide a tool for industry recruitment, and encourage diversification of the industry base. Given limited resources available for economic development, it is critical that planners allocate these resources in the most efficient way possible in order meet the needs of established and growing industries. By identifying clusters, and understanding specific needs (i.e., infrastructure or work force needs) of the industries within the clusters, planners can build on the existing strengths in the region and provide more appropriate assistance to businesses. This is in contrast to many current policies, which direct resources at the industries the region hopes to attract, regardless of whether the existing environment is conducive to the development of these industries (Doeringer and Terkla 1995).
Industry cluster polices can also serve as a tool for industry targeting and recruitment. When an industry cluster is identified, gaps in the entire production process become apparent. Local planners can use this knowledge to target industry recruitment to fill these gaps, and complete the overall production process. Cluster policies are also encouraged, as they are believed to stimulate competition, which in turn leads to economic growth. Clusters can also help diversify an economic base, by developing the supplier networks or related support services needed to serve the larger firms in the cluster. Lastly, proponents of industry clusters claim that the clusters that include industries across several sectors are more adaptable to change, and can better withstand downturns in the economic cycle (Doeringer and Terkla 1995, Henton, Melville, Walesh 1997, Rosenfeld 1997).
While the benefits of cluster policies have been recognized, there are few examples of industry cluster policies currently in place in the United States. For the most part, industry clusters have been used to help identify current economic activity in a region, but few policies have been operationalized based on this identification. Currently, several states are attempting to incorporate industry clusters into their economic development planning. Specifically, both Oregon and Arizona have worked to identify key industry clusters within the states, and have focused their economic development efforts on identifying the needs of and promoting growth in these clusters (Rosenfeld 1996). Beyond the limited examples of state policies and several regional initiatives, industry clusters have not yet been incorporated into public policy efforts in the United States.
Porter (1997) has proposed incorporating industry cluster policy into inner city economic development. He claimed that there are certain industries that are likely to locate in inner city areas, and will receive a competitive advantage from the location. Porter suggests that economic developers should identify these firms, and encourage their development in central cities. As clusters develop, they can be used to target industry recruitment, as well as to direct job training programs to fill the skill needs of these clusters.
EVALUATION AND CRITIQUE OF INDUSTRY CLUSTER POLICIES
To date, there is little research on the effectiveness of industry cluster policy in generating economic development in cities or regions. The traditional measures of economic development are the number of new jobs created and tax revenue generated. In terms of these measures, there is no relevant literature available. However, Rosenfeld (1997) presents several criteria that could be used for evaluating the overall efficiency of industry clusters. These include the number of new spin-off businesses firms in the cluster have generated, the development of new technology and increased R&D capacity, the improvement of labor force skills, and the intensity and quality of firm networks created.
While there are very few industry cluster policies currently in place in the United States, the potential adoption of such policies has been criticized. Rosenfeld (1995,1997) provides a discussion of some of the general criticisms of cluster policies. The biggest concern is that cluster policies encourage over-specialization in the economy. If the industries in the cluster fail, then the economy in the entire region is damaged. Many leaders chose to encourage the diversification of the economy, and fear that the use of a cluster policy will run counter to this effort. Secondly, industry cluster policies are criticized for being more applicable to small, specialized firms, particularly because of the level of trust and cooperation required for a successful cluster. Critics claim that in reality, large, multi-national companies dominate the current economy, and these companies will undermine the trust that is required for a cluster to be effective. A third criticism of industry cluster policies is that it only applies to urban areas, and that rural areas lack the necessary scale for a cluster. Lastly, critics claim that new telecommunications technology is replacing the need for spatial clustering. Therefore, firms will no longer receive a competitive advantage from close geographic proximity.
Harrison and Glasmeier (1997) critiqued cluster policy specifically in regards to Porter’s application of cluster policy to inner-city economic development. However, several of their criticisms could be appropriate to cluster policy at all geographic levels. First, they claim that cluster development is more appropriate in areas where there is already an existing, diverse economic base, which can support new markets and diversification. A second criticism is that industry clusters are only capable of responding to small, incremental changes in technology and market demand. However with larger changes, Harrison and Glasmeier claim that clusters can be resistant to new information because it may introduce changes that are drastically different from the processes used for previous successes. As discussed earlier, information flow is critical for innovation, which is in turn necessary for a cluster to continue growth.
ADVANTAGES AND DISADVANTAGES OF CLUSTERS
By adopting The European Charter for Small Enterprises in June 2000, Member States
recognised that “Europe’s competitiveness depends on its small enterprises: these are
the main drivers for innovation, employment as well as social and local integration..
Therefore, the best possible environment for small enterprises should be promoted. And
to go further by affirming that:
“We will foster the involvement of small enterprises in inter-firm co-operation, at local,
national, European and international level as well as the co-operation between small
enterprises and higher education and research institutions”.
In that respect, enterprise clusters and networks are increasingly attracting the attention
of sub-national and national policy-makers, because they represent efficient structures
for stimulating the competitiveness, productivity and innovation of small enterprises.
The advantages and disadvantages of clusters and for the regions hosting them were
discussed in the expert group. But first, the driving factors for the
emergence of clusters were analysed.
Clusters are generally built up spontaneously by the local business players, who want to
take advantage from the synergy of several factors existing in the geographic area: the
presence of customers and suppliers, the access to qualified labour force and know-how,
the availability of specific natural resources and infrastructure, low transaction and
communication costs due to geographical proximity, the vicinity of universities, training
centres and research institutes, and the presence of financial institutions and other private
and public organisations.
Clusters constitute important knowledge spillovers for businesses. The physical
proximity of the factors outlined above furthers the creation of formal and informal
linkages and networks among firms, higher education and research institutions, financial
establishments, public agents and other local organisations, where information can easily
flow and propagate. Easier contacts are established with public administrations, allowing
them to adapt the infrastructure of the cluster to the businesses needs. All these
contribute to facilitating the innovation process. Indeed, to guarantee their survival in
these very competitive environments, cluster firms are obliged to develop innovative
strategies and to build in the necessary capacities to implement them. Innovation is not
just the sole preserve of universities or research centres, it is mainly the result of a series
of businesses initiatives and experimentation. In a cluster, enterprises voluntarily or
involuntarily learn from each other and copy each other. In such contexts, making
mistakes is allowed and is part of the learning process. The example of Italian industrial
districts is widely used to illustrate this. Furthermore, clusters that have been able to
develop a brand name bring to their companies and institutions a valuable tool to market
their products and services. The internationally renowned brand name Bresle Valley .
Glass Valley contributed to increase the sales of the glasswork cluster of the valley of
Bresle in France.
At a higher level, clusters have proved to be attractive to the regions hosting them. They
contribute to their economic growth and social wealth. As Porter stated, “prosperity
depends upon the productivity with which a region allocates its resources (manpower,
natural resources, infrastructure, etc) to produce goods and services.” And productivity
rises because of innovation. As demonstrated above, clusters can form the perfect
environment to enhance competitiveness. Clusters can improve productivity by allowing
firms to take advantage of specialised suppliers, local know-how, information, skills and
education. The proximity of customers, competitors, suppliers, universities and research
institutions provided impetus the creation and exchange of information and increases
opportunities for innovation. These in turn favour the growth, the high employment, and
the attractiveness of the regions.
It is worth noting that the reality of the advantages listed above has seldom been checked
on the basis of scientific performance indicators. Until recently, the majority of studies
carried out on clusters have restricted themselves to giving qualitative explanations on
the performance of clusters. Most of the time these have been based on the observation
of successful clusters.
In certain circumstances, however, clusters might become a hindrance to the further
development of its members, and, in extreme situations, even exacerbate the decline of a
In a context of rapidly-changing technology, cluster firms become more vulnerable if
they are locked in old technologies and if they do not develop enough flexibility to adapt
themselves to those changes.
Also, when cluster firms rely on few buyers or on the activity of one large or a limited
number of companies, as can happen, they may fail if these latter move or disappear,
even if they themselves are still competitive. At regional level, one should keep in mind
the existence of regions, which followed the decline of their clusters due to technology
lock-in and to an over-dependence on a small number of companies. Moreover, the force
of attraction of a region should not be over-estimated, as only few are internationally
CLUSTERING IN LITHUANIA
Region clustering dimention and cluster types variety in Lithuania
Kaunas Technology university Business Strategy insitute made the research in 2003 studing clustering in Lithanian region. One of the research goals was the present and potential clusters search in Lithuanian industry. Thus the main attention was put on national section. It was gone deep only into separate regions that research capacity and resourses had led, and also how clustering analysis oriented to some industry sections‘ region paticularity by all industry capacity.
Wanting to answer the question – if there is a point to try to find region clusters at all, the separate regions‘ input into county‘s economy was evaluated.
Exploratoty research had shown that it is possible to find the paticular micro clusters rudiment even now, some of regions have their clear specification (Jonava, Kedainiai, Mazeikiai, Ignalina and others). This clusterization aspect should be under state institutions supervision.
Analyzing clustering state in Lithuania, it was exhibited the making and potencial klusters’ variety:
Classic cluster, the point of which –the concentration of organizations round value creation chain. ( it may be meal production, TV production clusters). These clusters could be called macro clusters. But maybe it is early for Lithuania today to state there are such clusters in real.
Potential macrocluster – it could be creating macroeconomy cluster. It will depend on its width if it is classi or more sector cluster (wood cluster).
There are already not few micro clusters’ rudiments, though it is hard leastways approximately to show their nimber. Micro cluster ofen is made of 5-15 little firms, collaborating
with each other in different activities and projects. This can be common sduding, common marketing, common product creation or other cooperationally implemented activities.
Aleatorialy the two main microclusters types can be marked in Lithuania. Theh first, when similar firms are gathered by common asset links and make formal organization groups. This is par for wood manufacturing and furniture production, dairy industry branches. The second, when such activity is acted by totally independent little firms, forming firms’ networks.
It was possible to form all these picularities only by deep quality research help. Namely such research was the main making Lithuania industry clustering study.
Clastering level in different industry brabchesand sectors of Lithuania
1. Machines and devices production industry
• Machines and devices industry is one of the most fragmentary industry in Lithuania: organizations product especially wide spectrum or products.
• Now it early to state that this industry branch has clearly expressed cluster features.
• It is possible to find a lot of cooperation relationship between the same, however, the in most cases they are not stable.
• As majority metal manufacturing firm concentrate its activity to meet the Lithuania customers’ need, it is possible to see some tendencies of local micro clusters creation.
• TV and TV technical production cluster has the potential to grow into national cluster.
• The most substantial is mechatronic decision cluster.
2. Wood manufactory and furniture production industry
• Wood manufactory and furniture production industry is fully developed for realized and direct clustering. The present structure let us to say, that such cluster already exists, though is attached to “silent” cluster type.
• Also it is possible to set a lot of micro clusters.
• Wood manufactory and furniture production industry is good for formation of region clusters by their character.
3. Textile and clothing industry
• Burning and already beginning to form apace cluster, which has good perspectives for future is textile and clothing organization group, the nucleus of which is PLC “ECG”
• Cluster development strategy could be grounded by micro clusters around dynamic, into international clusters integrated organizations, creation.
4. Food industry
• Lithuania food industry sector – potential and large cluster, integrating not only food industry, but also it serving organizations.
• Now it is clearly seen micro clusters in different food industries, particularly in dairy and meat branches.
• The most credible and the best formatted sector cluster derivative in food industry – grain and its products production cluster.
5. Information Technology and communication industry
• Now Lithuanian ITT sector is only in every beginning, embryo development stage.
• ITT sector is strong potential national cluster.
6. Biotechnology industry
• By economic point this industry sector is not meaning for Lithuanian economy yet.
• The organizations’ group of this sector can not be classed even as embryo cluster category.
7. Laser and its component industry
• The sector is tenuous, only 9 main firms.
• The organizations’ group of this sector can not be classed even as embryo cluster category.
8. Chemistry industry
• It is found no clusters in this industry.
• The most respective by clustering viewpoint could be mineral manures production.
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EUROPEAN COMMISSION ENTERPRISE DIRECTORATE-GENERALPromotion of entrepreneurship and SMEs
Improving business support measures FINAL REPORT OF THE EXPERT GROUP ON ENTERPRISE CLUSTERS ANDNETWORKS
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