The Development of Cooperation in Clusters and Cluster Organizations

Because the major aim of the publication was to identify the levels of cooperation advancement in selected COs and to propound a coherent theoretical concept regarding the trajectory of development of cooperative relationships in such organizations, the subsequent part of the work focuses on issues related to the development of cooperation: both in clusters and COs. For this reason, it is essential to examine the cluster typologies, which based on an evolutionary approach, show the processes of transforming industry clusters into higher forms. One of them is the typology by Van Dijk and Sverrisson (2003), who have distinguished five development stages/types of clusters. With regard to their approach, clusters can evolve, transforming from “lower” to “higher” types, while the “lower” ones do not have to disappear with the appearance of the “higher” types (they can be nested in them). Location clusters, i.e. the lowest type in the typology, are based on cooperation in geographical proximity facilitating the exchange of information among the individual components of the cluster. Along with the development of the local market and, in response to this - the emergence of strong competition, a location cluster transforms into a local market cluster, which due to a subsequent specialization and division of labor among enterprises becomes a local network cluster. The last two types are the most mature stages of the cluster - they are focused on innovation development (innovative cluster) and based on coopetition (industrial district).

The development of a cluster can also be traced when taking into account its life cycle (Bergman, 2008). According to this approach, a cluster changes along with its growth stages (Swann, 1998; Braunerhjelm & Feldman, 2006) and the transformation through individual stages in the life cycle is the result of evolution of its components (Menzel & Fornahl, 2010). Each phase has specific features that generate changes general for the entire cluster population. However, the evolutionary development of clusters does not always take effect in the same way - the paths that clusters go through in their life cycles are not identical (Ter Wal and Boschma, 2011).

Cluster evolution depends primarily on external factors, primarily on the life cycle of the industries that dominate in a given cluster (Pouder & John, 1996; Klepper, 1997).8 The life cycle of a cluster is closely related to the life cycle of the industry in which it operates. Nevertheless, although both cycles show some similarities, they are not the same - clusters emerge in the initial stage of a certain industry’s life cycle and usually stabilize and show some dynamics at the industry’s maturity stage (Trippl et ah, 2015). Clusters can also evolve (shifting through the phases in the life cycle) independently of the development of the industry, for reasons such as heterogeneity in competencies, localized learning processes and cluster-specific limitations (the openness or rigidity) (Trippl et ah, 2015). The impact of enterprise heterogeneity on the cluster’s life cycle is particularly emphasized in the works by Menzel and Fornahl (2010) as well as Ter Wal and Boschma (2011). As a cluster proceeds in the life cycle, its technological diversity and flexibility decrease. As a result, the cluster becomes more and more closed and blocked (Gancarczyk, 2015).

The literature provides various approaches applied to describe the life cycle of clusters. The differences are visible in the number and names of the stages as well as in their characteristics (Tab. 2.3).

Despite the noticeable differences, there is a clear common feature, namely three main stages can be distinguished in the cluster’s life cycle: the initial and developmental stage, extension and maturity (combined with decline) (Maggioni, 2002). In some approaches (Tab. 2.3), the decline stage is identified as the fourth one in the life cycle of the cluster - it is a period of the cluster’s transformation or disappearance. The transformation between the stages is gradual because clusters consist of many different entities that reach a given stage at a different pace. The achievement of a given developmental stage by the entire cluster is determined by the position of the key enterprises operating in the cluster’s life cycle (Menzel & Fornahl, 2010).

Cluster growth is related to pre-existing factors and settings in the region - local capabilities, resources and institutions (Boschma & Frenken, 2011). Clusters can be born as a result of historical events, innovations, inventions or internal investments (Rosenfeld, 2002). According to Maskell and Malmberg (2007), clusters emerge randomly in a certain location and it is difficult to predict where and when they will start to grow. At the initial stage of the industry’s life cycle, the companies operating in it can be geographically dispersed (Klepper, 2007). When the industry develops, more and more enterprises are beginning to appear on the market, showing an increasing tendency to create industry clusters. Such start-up and spin-off enterprises, as defined by the literature, are accompanied by R&D institutions with which the local enterprises cooperate (Arthur, 1994; Klepper, 2007; Brenner &C Schlump, 2011). At this stage of the cluster’s development, its critical mass is formed. It is primarily determined by the number as well as the type of enterprises located in a certain region, yet the key enterprises, more than the other ones located in the region, play a particularly important role in

Sources

Cluster life-cyclestages

Maskell and Kebir (2005)

  • 1. Existence
  • 2. Extension
  • 3. Exhaustion

Poudcr and John (1996)

  • 1. Origination (growth)
  • 2. Convergence (stabilization)
  • 3. Reorientation (decline and realignment)

Rosenfeld (2002)

  • 1. Embryonic stage
  • 2. Growth stage
  • 3. Maturity
  • 4. Decay

Bergman (2008)

  • 1. Formative
  • 2. Growth
  • 3. Maturity
  • 4. Petrification

Martin and Sunley (2011)

  • 1. Cluster full adaptive cycle
  • 2. Constant cluster mutation
  • 3. Cluster stabilization
  • 4. Cluster reorientation
  • 5. Cluster failure
  • 6. Cluster disappearance

Sonderegger and Taube (2010)

Sources

Cluster life-cyclestages

  • 1. Pre-cluster foundations
  • 2. Existence/emergence
  • 3. Exploratory expansion
  • 4. Exploitative expansion
  • 5. Partial exhaustion

Malakauskaite and Navickas (2011)

  • 1. Foundation
  • 2. Slow growth (development) and fast growth (development)
  • 3. Maturity
  • 4. Maturity transforming into the decline
  • 5. Decline and transformation

Isaksen and Hauge (2002)

  • 1. Formation of pioneer firms often based on specific local knowledge, followed by new firm spin-offs
  • 2. Creation of a set of specialized suppliers and service firms, and a specialized labor market
  • 3. Formation of new organizations that serve cluster firms
  • 4. Attraction of outside firms, skilled workers, and fertile grounds for new local companies
  • 5. Creation of non-market relational assets that foster local circulation of information and knowledge

6. A period of decline for the clusters because ‘lock-in situations may occur

Lorenzen (2005)

  • 1. Arise
  • 2. Decline
  • 3. Shift

Menzel and Fornahl (2010)

  • 1. Emerging
  • 2. Growing
  • 3. Sustaining
  • 4. Declining

Maggioni (2002)

  • 1. Birth/take-off
  • 2. Golden age
  • 3. Maturity

Source: Authors’ own study.

the cluster development (Arthur, 1994; Brenner, 2001; Brenner & Schlump, 2011). From the point of view of further development of the cluster, the entities from related industries are also important (Boschma & Wenting, 2007).

At the expansion stage, the cluster becomes more concentrated (Menzel & Fornahl, 2010) because it attracts new enterprises (competitors, suppliers), which increases the overall number of enterprises in the cluster (Brenner & Schlump, 2011). This stage is characterized by a strong growth of leading enterprises and the development of the cluster products, which strengthens the cluster’s competitiveness (also internationally) as well as stimulates entrepreneurship (Rosenfeld, 2002). At this stage, there is also intensive development of relations within the cluster, and the trust developed among the partners can become the basis for more advanced forms of cooperation (such as implementation of joint projects). Although actions undertaken by the enterprises are relatively simple to implement and do not require special resources, they bring noticeable effects. Enterprises operating in a cluster gain the benefits of an agglomeration (Marshall, 1890), especially in the context of knowledge flows (Maggioni, 2006), which occur not only among the enterprises operating in the same sectors of the economy but also among industries (Brenner & Schlump, 2011). Due to a better access to tacit knowledge (Maskell & Malmberg, 2007), also the collective learning processes of enterprises in the cluster become more and more innovative. The increase in innovation also depends on the quality of the innovative milieu in which the particular cluster develops.

During the maturity stage the cooperation among the enterprises does not disappear; the entities still benefit from their operating in the cluster. Flowever, the number of enterprises in the cluster falls since some of them begin to move to other more attractive locations. Innovations introduced in the cluster are gradual, the processes become routine (and easier to reproduce elsewhere) and the products increasingly standardized (Trippl et al., 2015). In the face of many followers, the costs become the key source of competitive advantage (Rosenfeld, 2002). Competitive pressure within the cluster encourages its enterprises to launch cheaper substitutes or to develop innovations, which may initiate a new life cycle of the cluster (Jircikova et al., 2013). Over time, the advantages of shared location diminish and give way to negative effects of shared location. The cluster may experience “lock-in” (Grabher, 1993), “closure” (Coleman, 1988) and overload (Swann, 1998; Beaudry et al., 2000), which may reduce its adaptability and competitiveness, consequently leading to its decline. There is also a slowdown in market growth (the market for products manufactured in the cluster becomes significantly limited). The cluster declines or transforms (undergoes renewal) in order to open to new market opportunities (Brenner & Schlump, 2011).

Analyzing the life cycle of clusters in terms of assistance programs, it is possible to indicate some forms of support that are beneficial for the development of clusters at a certain moment of their lives. In addition to COs (politically induced or mixed ones), one can mention a number of other forms of public intervention tailored for a specific stage of a cluster’s life cycle. According to Brenner and Schlump (2011), in the early stages, the focus should be put on supporting innovation and entrepreneurship. Therefore, in the first place, the innovative milieu should be strengthened by supporting scientific, business and training institutions and providing entrepreneurs with access to funding sources for innovation. All these actions facilitate learning processes and the flow of knowledge and technology to enterprises that are developing in a certain cluster and, in consequence, are advancing their innovation. As far as the entire life cycle of a cluster is concerned, it is necessary to support the development of cooperation among enterprises by initiating short-term joint activities (e.g. implementation of joint projects) and long-term joint activities (e.g. COs).

However, the approaches mentioned above are hardly connected with the heart of the matter discussed in the paper - they are essentially about clusters, not COs, which, as stated earlier, have their own life cycles. The model of development of COs was presented by Solvell et al. (2003), who, nevertheless, stipulate that it is difficult to create one universal model for the development of this type of organizations. They claim that every Cl is unique, which means that it has its own unique character based on the local resources and adapted to the local standards and institutions. The trajectory of development of CIs depends on many different factors, most of which are independent of it, e.g. national and regional conditions (in developed countries, at the transformation and developing stages, the trajectory looks different than in prosperous and less prosperous regions at a lower level of aggregation), the sector of the economy (in which the given initiative and its associated entities operate) and the cluster (on the basis of which the initiative develops) as well as support from public authorities. The development of COs is also influenced by internal factors related to capacity for proper projection and management of the initiative, the potential of cluster enterprises and their involvement in activities undertaken within the CO. Solvell et al. presented the life cycle of a CO by indicating four stages of its development: antecedence, formation, Cl and cluster-based institution for collaboration (IFC). Antecedence in this case refers to previous industry initiatives focused on the implementation of similar goals, affecting the launch of a given CO (e.g. lobbying, innovation activities, industry associations, business milieu institutions). According to the authors of the “Greenbook”, the transformation from the analysis stage (antecedence) to the emergence and further development of a Cl is a big challenge since the differences among these stages require different skills, different levels of involvement of the cluster participants and different work models. Following their observations, it takes more than 3 years to gain the Cl momentum. In addition, CIs can develop towards greater institutionalization and transform into cluster-based IFCs (belonging to business milieu institutions). Moving on to the next stages of development, the needs and expectations of the members change, which should be included in the list of objectives set for the Cl at a certain stage of its development. At later stages of the development of CIs, the role of “commercial cooperation” decreases, whereas the rank of “cluster expansion” increases (especially in the context of incubation of young enterprises) (Solved et ah, 2003). However, the life cycle of a CO presented by Solved, Lindqvist and Ketels is very simplified - it does not reveal how the development of cooperative relationships in this type of organizations occurs.

Nevertheless, the literature does not provide any other works that describe the trajectory of cooperation development - not in clusters but in COs, i.e. organizations established to support cluster development. The evidence is found in the results of the review of scientific publications registered in the previously mentioned databases: WoS and Scopus. In order to find out the number of publications on additional issues concerning cooperation, development trajectory and cluster life cycle as wed as Cl and CO, the author applied the previous criteria (Tab. 2.1 and 2.2) yet extended by four new keywords (Tab. 2.4 and 2.5).

In the case of the WoS database, with regard to CIs and organizations, only single papers were selected, which (as it was noticed after reading them) do not present the expected dynamics of cooperative relationships and hardly relate to CIs or COs. In the Scopus database, the number of search results was higher - the fewest records were selected by using the “trajectory” keyword (13 for Cl and 5 for CO), whereas the biggest number concerned the “cooperation” keyword (56 for Cl and 26 for CO). Nevertheless, also this source did not reveal publications that would holistically present the development of cooperation in COs. When comparing the results obtained for CIs, COs and clusters, it is impossible to miss the huge disproportions in the number of the found publications - in the WoS database, the number of search results for the combination of the word “cluster” and the additional keywords reached several hundred publications (except for the 55 publications, which were selected by using the words “trajectory”). In the Scopus database, it was over three thousand results regarding two words “collaboration” and “cooperation”, and about two thousand results in the case of the other two words: “trajectory” and “life cycle”.

It should be emphasized that the analyzed databases did not cover the entire output of the world literature. Therefore, one cannot rule out the presence of publications that would present the dynamic and at the same time the holistic approach to cooperation in COs. The aim of the holistic approach to the cluster reality is visible by the reflections and analyses in

Table 2.4 The results of the review of scientific publications in the Web of Science Core Collection database with additional keywords

Search criteria

Keyword

Cluster

Cluster

Cluster initiative

Cluster organization

Categories: Business,

Management, Fxonomics, Geography

13,186

6,634

26

9

Collaboration

562

281

4

1

Cooperation

513

311

3

1

Trajectory

118

55

3

0

Life cycle

228

147

3

0

Source: Authors’ own study based on the Web of Science Core Collection database (the figures quoted are as at March 21, 2020).

Search criteria

Keyword

Cluster

Cluster initiative

Cluster organization

Subject area: Business, Management and Accounting; Economics, Econometrics and Finance; Social Sciences

41,634

145

67

Collaboration

3,310

41

18

Cooperation

3,375

56

26

Trajectory

2,224

13

5

Life cycle

1,912

31

15

Source: Authors’ own study based on the Scopus database (the figures quoted are as at March 21,2020).

the authors’ earlier publications, not indexed in WoS or Scopus (Lis & Lis, 2014a; 2014b) - they addressed the adaptation of Bourdieu’s capital theory (Bourdieu, 1977; 1984; 1986; 1990; Bourdieu &C Wacquant, 1992) to the field of management sciences and the implication of such a modified concept to research and analysis of the conversion of four distinguished types of capital: the economic, social, cultural and symbolic ones in COs. Nonetheless, the concept of capitals applied to COs has not provided an adequate basis for distinguishing the levels of cooperation in this type of organizations.

 
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