Paper to be presented at the
35th DRUID Celebration Conference 2013, Barcelona, Spain, June 17-19
Heterogeneity of MNEs entry modes in industrial clusters: an evolutionary
approach based on the cluster life cycle model
Silvia Rita Sedita
University of Padova
Department of Economics and Management
[email protected]
Annalisa Caloffi
University of Padova
Department of Economics and Management
[email protected]
Fiorenza Belussi
University of Padova
Department of Economics and Management
[email protected]
Abstract
This paper analyses the heterogeneity of MNEs entry modes in industrial clusters by adopting an evolutionary approach
based on the cluster life cycle model. Three are the ideal-type phases of cluster life cycle described by the literature:
origin (emergence), development (increased number of firms and employees), and maturity (relative decline of firms
and/or employees). We mean to investigate the MNEs entry modes in relation to the specific cluster life cycle phase,
claiming the existence of an interwoven evolution of clusters and MNEs. The methodology applied is a comparative case
study analysis of four important global clusters: the sport-system cluster of Montebelluna, Italy; the footwear cluster of
the Riviera del Brenta, Italy; the footwear cluster in Pingzhou, in Guandong, China; the footwear cluster of Timisoara,
Romania. Our analysis suggests the existence of a variety of evolutionary patterns where either a) the MNEs originated
the cluster; or b) MNEs emerged as homegrown MNEs out of a process of expansion of local small firms; or c) the
MNEs entered the cluster in a development/maturity phase. The heterogeneity of cluster evolutionary dynamics and
MNEs entry modes open up a wide space for the formulation of specific cluster policies, oriented to establish adequate
measures for the attraction and localization of MNEs and for the internationalization of leading cluster firms.
Jelcodes:R00,F23
To be submitted to DRUID Celebration Conference 2013 – Barcelona 17-19 June
Track: L. Clusters, Regions and Growth
Heterogeneity of MNEs entry modes in industrial clusters: an evolutionary approach based
on the cluster life cycle model
ABSTRACT
This paper analyses the heterogeneity of MNEs entry modes in industrial clusters by adopting an
evolutionary approach based on the cluster life cycle model. Three are the ideal-type phases of
cluster life cycle described by the literature: origin (emergence), development (increased number of
firms and employees), and maturity (relative decline of firms and/or employees). We mean to
investigate the MNEs entry modes in relation to the specific cluster life cycle phase, claiming the
existence of an interwoven evolution of clusters and MNEs. The methodology applied is a
comparative case study analysis of four important global clusters: the sport-system cluster of
Montebelluna, Italy; the footwear cluster of the Riviera del Brenta, Italy; the footwear cluster in
Pingzhou, in Guandong, China; the footwear cluster of Timisoara, Romania. Our analysis suggests
the existence of a variety of evolutionary patterns where either a) the MNEs originated the cluster;
or b) MNEs emerged as “homegrown MNEs” out of a process of expansion of local small firms; or
c) the MNEs entered the cluster in a development/maturity phase. The heterogeneity of cluster
evolutionary dynamics and MNEs entry modes open up a wide space for the formulation of specific
cluster policies, oriented to establish adequate measures for the attraction and localization of MNEs
and for the internationalization of leading cluster firms.
Keywords: cluster life cycle, MNEs, footwear clusters, heterogeneity
1
1. Introduction
This article investigates MNEs (multinational enterprises) entry modes in industrial clusters,
considering clusters life cycle specificities. Despite the model of industrial cluster has been often
described, following Marshall (1920), as locally self-contained, various empirical researches have
recently pointed out its increasing involvement in the process of internationalization. Recent
contributions have described how the competitive advantage of agglomeration can be blended with
synergies with external-to-the- cluster actors, which become nodes of a research-oriented or
manufacturing-oriented network (Belussi et al. 2011; Belussi and Sedita, 2012; Lorenzen and
Mudambi 2012). Many research works investigate how the absorptive capacity of cluster firms
influences the efficacy of external connections. Mechanisms of searching, “transcoding” and
knowledge transfer are in place in low-tech clusters in Italy (Morrison 2004; Morrison et al., 2013;
Boschma and ter Wal 2005), and research networks spur innovation in high-tech clusters, such as in
the case described by Powell et al. (1996) for the Boston biotech cluster. Global alliances are
diffusely built in the case of bio-clusters in the field of R&D collaboration and for licensing
(Moodysson et al., 2008). In a global world (Dicken, 2003), where the access to resources (and
codified knowledge) is practically ubiquitous (Maskell 1999), the only strategy pursued by firms to
differentiate themselves from their rivals is to use complex monitoring strategies to disentangle
knowledge sources (such as cluster-specific architectural knowledge, see Pinch, et al. 2003) or
knowledge sources that can be available only to a restricted club of members, and/or embedded in a
local codebook (Cowan and Foray 1997).
If current literature has put in evidence the role of external linkages or pipelines which connects
clusters with the whole economy (Bathlet et al., 2004; Brazcyk et al., 1998; Becattini and Rullani,
1996; Henry and Pinch, 2001), our work emphasises a
peculiar and yet understudied aspect of
cluster dynamics: the presence of MNEs.
FDI (foreign direct investment) by MNEs increasingly takes the form of knowledge-seeking
investment (Dunning, 1998), whereby the MNE attempts to augment its knowledge base through
2
obtaining access to foreign pools of knowledge (Ghoshal and Westney, 1993; Humphrey and
Schmitz, 2002; Cantwell and Iammarino 2000; Holm, Malmberg, and Sölvell, 2003) by becoming
a participant in various localized knowledge clusters simultaneously (Enright, 1998; Rugman and
Verbeke 2001; Lorenzen and Mahnke 2004; Nadvi, & Halder, 2005; Kim & Zhang, 2008). Indeed,
being directly present where knowledge is generated is a more effective way to absorb it, in
comparison with cross-border transfers.
This article explores the modality through which cluster dynamics can be intrinsically interlinked
with the presence of MNEs. In some cases, MNEs are the main actor responsible to giving rise to
the local cluster, while in others they enter (or emerge in) the local cluster in one of the subsequent
phases of its life cycle (development or maturity). ‘Homegrown’ MNEs in clusters are formed
when small firms invest strategic resources in innovation and expansion and progressively
transform themselves into MNEs.
Our contribution is twofold. First we present a complete
literature review on the theme of MNEs and clusters . Second we present a cluster typology in
relation to the role played by MNEs, derived upon a comparative case study research. This
typology looks at the moment in which MNEs entered the analyzed clusters, either at the origin
phase or in the development/maturity phase. Following this line of reasoning we propose a newly
created cluster typology, which individuates four types of clusters: 1) satellite cluster; 2) evolving
satellite cluster; 3) evolutionary Marshallian cluster (with emerging Homegrown MNEs and MNEs
entry), and 4) multinationalised Marshallian cluster. Our typology stems from and adds to the
modeling of industrial clusters presented by Markusen (1996) more than two decades ago, and
follows the natural dynamics of cluster evolution, which is strongly affected by the emergence of
global forces. The cluster life cycle model represents a way to look at the relation between cluster
evolution and global challenges.
The paper proceeds as follows: section two is focused on the analysis of clusters life cycle.
Section three is dedicated to the interwoven evolution of clusters and MNEs. Section four presents
some illustrative case studies. Section five provides some conclusive remarks.
3
2. The cluster life cycle
The cluster represents a specific form of agglomeration of local firms; however it is characterized
by a multiplicity of possible evolutionary patterns of growth, innovation and learning (Porter, 1990,
1998; Humphrey and Schmitz, 1995; Asheim, 1996; Markusen, 1996; Belussi et al. 2003; Caniëls
and Romijn 2005; Guerrieri and Pietrobelli, 2004; Becattini et al. 2009; Iammarino and McCann,
2010; Morrison et al. 2013)1.
In the last century, some clusters have declined, whereas others have grown and changed, and
new ones have emerged. In search of a theoretical explanation of cluster dynamics, three main
streams of literature emerged. The first one is the organizational ecology theory, which has been
devoted to the application of demography and population ecology models to economics, referring
mainly to the works of Hannan and Freeman (1989) and Carrol (1984). A large stream of literature
has followed this path (Lazzeretti and Storai, 2001; Lazzeretti, 2006; De Propris and Lazzeretti,
2009). The second one, more embedded in the management studies literature, has explored the
relationships between the company growth strategies and the expansion of the clusters in terms of
innovation capabilities, integration/specialization and product diversification (Porter, 1990; Pouder
and Caron, 1996; Ginsberg et al. 1998; Lazerson and Lorenzoni, 1999; Giuliani, 2007; Audretsch
and Feldman, 1996; Belussi and Samarra, 2010). The third one deals with the evolutionary
economic geography (Boschma and Frenken, 2006; Martin and Sunley, 2006; Boschma and Martin,
2007, 2010), which explained the cluster evolution as a path-dependent process (David, 1985;
Arthur, 1994).
The emergence of this third stream of literature is strictly connected to the
pioneering work of Brenner (2001, 2004), who proposed a mathematical model to illustrate the
evolution of industrial clusters, which was linked to local symbiotic inter-firm interactions and the
existence of favorable exogenous conditions. Press (2006) introduced some other metrics to
measure the various phases of cluster life cycles. In the last ten years, scattered contributions have
analyzed the genesis and evolution of clusters adopting the life cycle model, some only theoretical
1
For a complete review of cluster research see Lazzeretti et al. 2013.
4
in nature (Wolfe and Gertler, 2004; Menzel and Fornahl, 2010), some other empirical, using
qualitative research techniques (Feldman & Braunerhjelm, 2007; Belussi and Sedita, 2009).
Alongside this view, a recently published special issue, titled “Cluster life cycles”, and edited by
Ron Boschma and Dirk Fornahl (2011), has re-ignited a debate over the issue, collecting a variety
of qualitative and quantitative case studies that generally shed light on the validity of the model. A
note goes to the contribution of Martin and Sunley (2011), who critically addressed the validity of
the model, proposing a new way forward to look at the evolution of clusters, rooted on complexity
thinking. They acknowledge the complex nature of the unit of analysis and suggest considering the
cluster as a complex adaptive system, following a four stage adaptive cycle: exploitation,
conservation, release, reorganization. Each phase is characterized by different level of 1) potential
resources available to the system, 2) internal connectedness of system components, and 3) resilience
(or the capacity to face internal/external shocks). Their deep discussion on the evolution of clusters
does not contradict at all the idea of a cluster life cycle, but it has the merit to alert us against bioevolution-type stereotyped models.
As promised, the special issue opened up a large debate among scholars. Li et al. (2012) signed
an important step forward in the analysis of the cluster evolution, by linking the cluster life cycle
model to network dynamics. They recognize the relevant role of social and business networks in
clusters, and propose an analytical framework whose main components are: context (economical
and institutional structures), action (related to the ability of individuals and organizations to explore
learning opportunities and make strategic decisions) and network (social and economic relations
between organizations). Following Belussi and Sedita (2009), Elola et al. (2012), by means of a
meta-study on four Basque clusters, accurately analyzed the factors that accounted for their origin,
development and maturity. For the scope of this paper, it has to be noted that they provide evidence
that the entry of multinationals is one of the main triggering factors for the emergence and
development of the analyzed clusters.
5
In order to understand the heterogeneity of cluster life cycles, it is, in fact, important, to
investigate the triggering factors which intervene in the local system’s genesis - the so called cluster
existence argument (Maskell and Kebir 2006) – and in its evolution-exhaustion, which refers to the
factors explaining the decline and pathology of clusters, as it has been authoritatively described by
Loasby for the shoes British industrial district or by Sunley (1992) for the historical decline of
Lancashire. Even if we acknowledge the limitation of the adoption of the biological metaphor to
illustrate cluster evolution, and we agree on the need of further scientific effort in search of the most
proper model to be applied, in this work we apply the cluster life cycle model to investigate the role
played by MNEs in shaping cluster life cycle.
Aligning with Belussi and Sedita (2009), we consider the cluster life cycle as composed of three
main stages: origin, development and maturity. Along these stages we find variations in the local
population of firms and workers, and in the structure of their social and business relationships. In
addition, different phases of cluster development correspond to different stages of the evolution of
‘cluster-specific conditions’ in terms of quantity and quality of the local pool of contextual
knowledge and skills, social norms and business practices.
In the origin stage, the set of cluster-specific conditions are not present. Retrospectively, we can
say that the local fabric of institutions, knowledge and competencies has not yet formed. However,
the cluster can host some historical sediment of knowledge and competencies, as well as a local
culture.
The development stage is characterized by the emergence of a set of cluster-specific institutions,
knowledge and competencies. In this stage we observe a progressive increase in the population of
local agents, and a thickening of the web of relations that develop among them and the external
context. Interaction among local agents enables virtuous processes of development, characterized
by a progressive enlargement and diversification of the local pool of resources and competencies.
These are produced and diffused into the cluster as specific public goods, freely available for all
agents that are part of the local community which contributed to produce them. The knowledge
6
exchanged among the actors in the cluster is mainly tacit, and therefore difficult for external agents
to grasp. In the maturity stage, the growth rate of the local population gradually slows down, as
does the virtuous cycle of semi-automatic reproduction of cluster-specific conditions. While a part
of the tacit, cluster-specific knowledge which previously accumulated progressively becomes
codified, the production of new pieces of knowledge gradually can slow down, and only in few
clusters local firms maintain their ability to renew their innovative capabilities. The transition from
one stage to another can bring about changes in the structure of the clusters and in their innovative
capacities, as well as in the management of external information-knowledge diffusion and recombination processes. However, the sequence of stages is not predefined. In fact, cluster-specific
conditions, and, in particular, institutions that rule the life of the cluster, are on one side the ‘carriers
of history’ (David, 1994), but on the other side elements that co-evolve with the cluster. They can
be hit by any kind of external or internal changes, leading to different short and long-term
consequences. An important change is represented by the localization of external agents into the
cluster, which can operate as a triggering factor for cluster origin or development, or even for
cluster maturity and decline (Bellandi, 2001, 2006; Zucchella, 2006; Belussi & Sedita, 2009).
Literature on this point has developed only in recent years, mostly on the basis of single case-study
analysis. For this reason, our understanding of the relationship between clusters and MNEs is still
very partial. We try to elaborate on this point in the following section by focusing on the role of the
MNE in a dynamic setting.
3. The interwoven evolution of clusters and MNEs
This paper focuses on the relationship between the cluster life cycle and the entry/emergence of
MNEs.
In the past, the MNE and the cluster have been analyzed mainly as two opposite
phenomena (Cowling and Sudgen, 1999). On the one hand, starting from the contribution of Vernon
(1966), Hymer (1972), and Dunning (2000) a large stream of literature has analyzed the MNE
model, highlighting the role MNEs can play in the creation of hierarchical networks having global
reach, and discussing the advantages of hierarchy. On the other hand, the cluster literature has
7
almost exclusively focused on the role of horizontal (often informal) local networks where the local
system developed at the beginning was initially considered a self-contained one, but soon during
2000s many researchers started to analyze the process of internationalization of clusters (Camuffo
and Grandinetti, 2011).
Recent studies have emphasized that the multinational and the cluster are not in opposition. In
fact, clusters can be attractive areas for foreign direct investment inflows (Birkinshaw, 2000;
Birkinshaw and Hood 2000), and this process can further generate a catalyst effect of cluster’s
growth (Andersson, Forsgren and Holm 2002; Williams et al., 2008; Malmberg and Waxell, 2007).
The possibility to reconcile the two models comes from the evolution of the two strands of
literature. Studies on MNEs argue that an increasing amount of FDI can be explained by the quest
for new knowledge, which is available in specific foreign locations (Cantwell 1989; Cantwell and
Iammarino 2000; Iammarino and McCann, 2013). Being located where knowledge is generated is a
more effective way to absorb it, in comparison with cross-border transfers, because the access to
informal and tacit knowledge, face-to-face contacts, and workers’ mobility (Jaffe, et al. 1993;
Kogut and Zander 1992; Shan and Song 1997). FDIs by MNEs increasingly takes the form of
knowledge-seeking investments (McCann and Mudambi, 2004; 2008), where the MNEs attempt to
increase their knowledge base by tapping into foreign pools of knowledge (Birkinshaw and Hood,
2000; Gordon and McCann, 2000; McCann, Arita and Gordon, 2002; Nachum and Keeble, 2003),
also by becoming a member of various clusters (Birkinshaw and Hood
2000; Rugman and
Verbeke, 2001). MNEs appear especially prone to performing R&D investments in foreign
locations with a strong technological activity, and in clusters characterized by a thick fabric of
specific knowledge and competencies.
The literature on clusters has changed, and has explicitly recognized the role played by external
resources in promoting cluster innovativeness and competitiveness (Belussi and Sammarra, 2010;
Belussi and Sedita, 2012). For instance, Guerrieri and Pietrobelli (2004), and Ernst (2002), by
looking at the rapid take-off of Far East clusters, have observed that the presence of a MNE can
8
stimulate processes of knowledge transfer and local development through subcontracting activities
to cluster firms. Quite opposite to that, other authors have denied a positive role played by MNEs in
clusters (Lipsey 2004; Veugelers and Cassiman 2004; Bair and Gereffi 2001). Clusters are not
simply recipients of MNEs, but they can play an active role in the creation of global networks. They
are experiencing internationalization through outflow processes of activities relocated abroad, in
terms of outsourcing-offshoring (McCann & Mudambi, 2004). When market conditions are viable,
capital goes abroad to seek low-cost labor, either through foreign direct investment (FDI) or
subcontracting activities. However, high-added-value or strategic activities are often kept out within
the boundaries of the cluster (Mudambi, 2007).
We believe that in order to properly link the two phenomena, we have to explicitly take into
account the specific stage of cluster evolution. Each stage provides different sets of location
incentives and disincentives for the MNE entry. MNEs choose to invest in a particular cluster on
the basis of the current state of the cluster, as well as of an estimation of its future state, or, more
precisely, on the basis of the current gains and the actual value of expected future gains.
In some cases, the entry of MNEs is to take advantage of low salaries, but over time they activate
also a local process of incremental learning and spillovers. In others, they start to benefit from their
new location in terms of innovation and new knowledge absorption (Kenney, Massini & Murtha,
2009; Görg and Greenaway, 2004). Other cases exist when the entry of MNEs is motivated by
resource seeking. A typical case in which the origin of the cluster coincides with the entry of
MNEs has been described by Markusen (1996)m calling this type of clusters satellite platforms.
However, as highlighted by Nachum & Wymbs (2005), initial localization of a MNE can also make
the cluster attractive for other MNEs, giving rise to a self-enforcing effect that produce an
agglomeration of plants, and possibly a change in cluster structure.
Localization in a cluster in its development phase presents various opportunities and risks. At
this stage, the relevant cluster-specific knowledge is mainly tacit and is produced and exchanged
among members of the local community. Therefore, as highlighted by McCann et al (2002), MNEs
9
can benefit from localization in this type of cluster only if they fragment their organizational
structures to give each establishment complete decision-making and enter into the local community.
If MNEs enter in a later stage they will have to bear higher costs for locating in the cluster,
resulting from higher prices of land and labor. In addition neither the immediate nor the future
benefits may be evident, since, at this stage, the specific idiosyncratic knowledge of local firms is
still in its formation, and it is not easily visible. All things considered, the cost-benefits to enter a
cluster in the development stage do not encourage simple decisions. Investment should be high, and
should not have a short-term perspective. As a result, we can expect a MNE afford it only in
presence of greater expected results, or specific inward FDI policies (Cantwell & Mudambi, 2000).
Things become different at the maturity stage, when the cluster-specific knowledge previously
accumulated becomes codified, more easily visible from outside (Chaminade and Vang, 2008). In
this context, MNEs can locate their subsidiaries with the scope of benefiting from the pool of
accumulated knowledge. In the maturity stage the cluster can develop “homegrown MNEs”, former
small firms that grow at a global scale. This appears to us an important issue which, nevertheless
has been scarcely addressed by the international business literature.
We reviewed the literature on clusters and MNEs, taking into account the differences among the
stages of cluster evolution, by looking (when possible) at the peculiar motivations driving the entry
of the multinational in the cluster. As shown by the following Table 12, we find support to the
hypothesis of heterogeneity of entry modes of MNEs. Many entries occur either in the origin or in
the development-maturity stage. MNEs entry has different determinants and different features
depending on the different stages of cluster evolution. MNEs give rise to a cluster when the locality
is characterized by favorable geographical conditions, when an educated labor force is locally
available, when some infrastructures are present (including R&D infrastructures), and – very often
2
Data come from ISI database. Observations are updated at October 2011. We searched the database using these
keywords: “industrial district*” AND “multinational*”; OR “industrial district*” AND FDI; OR “cluster*” AND
“multinational*”; OR “cluster*” AND FDI (as topic in ISI) . We excluded articles referring to “cluster analysis” as a
statistical procedure or articles, which did not provide empirical evidence on the relationship between cluster phase of
development and entry/origin of MNE.
10
– when an IFDI (inward FDI) policy is at work, that is when the locality provide some subsidies to
foreign investors (e.g. Gorg and Rouane, 2000; Tsai, 2001).
INSERT TABLE1 ABOUT HERE
MNEs choose to enter a cluster in the origin phase when the locality boast some manufacturing
ability, or when some resources are available or potentially available at low cost in the locality (e.g.:
availability of networks of suppliers that could meet the MNEs quality and delivery standards) (e.g.:
Fromhold-Eisbith and Eisbith, 2005).
In the case of clusters in the maturity stage, knowledge-, technology-, and competence-seeking
motives prevail. This means that the cluster-specific knowledge, technology and competencies are
attractive objects for the MNEs (e.g.: Cantwell & Janne, 1999; Teubal, Avnimelech and Gayego,
2002; De Propris and Driffield, 2006).
Finally, we note that most of the cases of homegrown multinationals (MNEs originated in a
cluster) emerge in the maturity stage of the cluster. They behave as other MNEs do, going abroad in
search of reducing costs, accessing important resources and markets, and tapping into networks of
foreign knowledge (De Propris, Menghinello and Sugden, 2008). When local cluster’s firms grow,
MNEs or large firms can originate multi-centered clusters, formed by locally owned firms
(Brookfield, 2008).
4. Some illustrative case-studies
4.1 Methodology
In order to deepen our knowledge on the intertwined development of MNEs and clusters along the
cluster life cycle, we conducted a comparative cross-country case study. The research on the
interwoven evolution of clusters and multinationals is quite recent, and asks for an explorative
method, more than a confirmatory one. Therefore, it is better to apply a qualitative rather than a
quantitative approach (Doz, 2011; Welch, Piekkari, Plakoyinnaki, & Paavilainen-Mäntymäki,
11
2011). A qualitative case study research design is particularly recommended when the boundaries
between phenomenon and context are not clearly defined (Eisenhardt, 1989; Yin, 1994; Glaser &
Strauss, 1967). In this case, an intensive analysis of few cases is more suitable than a superficial
statistical analysis of many cases. Because of the importance of country-specific variables in the
determination of social and economic outcomes, we chose a qualitative comparative (cross-country)
case study research design. We used four surveys conducted by us addressed to the same sector
studying the cluster evolution in China, Romania, and Italy. Our selection was not random, but
information-oriented, guided by the principle of having at least two cases for each theoretical
category analyzed (in a cluster life cycle perspective). Accordingly, we selected two clusters where
the MNEs entered in the origin phase (Pingzhou and Timisoara), and two where the MNEs
emerged/entered in the development/maturity phase (Montebelluna and Riviera del Brenta). In
order to allow a dynamic and a cross clusters comparison we selected the four clusters in the same
sector (footwear). Therefore we tried to reduce the influence of variation caused by sector
specificities3.
For whose are worried by the fact we chose two Italian clusters to investigate the entry strategy
of MNEs in the development/maturity phase, and thus claiming a lack of variety in the case study
research design, we remind here that the majority of mature clusters are located in Italy, where also
cluster policies have a long tradition.
In each cluster, interviews (lasting 1 hour or more) have been conducted by the authors to
entrepreneurs or top managers on the basis of a semi-structured questionnaire4. In the cases of
Pingzhou and Timisoara, the authors have been supported by simultaneous translators. The choice
of having the authors as interviewers has the advantage to allow direct observation of the
organizations and the local environment, which complement the information collected through the
3
30 companies and 10 local organizations were interviewed in 2004 for the Pingzhou cluster;30 companies and 9 local
organizations in 2003 for the Timisoara cluster; 40 companies and 10 local organizations in 2003-2004-2006 in the
Montebelluna cluster; 14 companies and 2 main local organizations in 2010 in the Riviera del Brenta cluster.
4
Related research works are published as: Caloffi, 2010; Belussi, 2010a and 2010b; Belussi, et al., 2011; Belussi and
Caldari, 2005; Acrib, 2010.
12
interviews. In selecting the companies to be sampled, we followed a random sampling
methodology; local organizations were picked up among the most active in terms of services
provided to the firms (i.e. support to the production process, innovation and marketing) and of
policy interventions at the local level. Fieldworks have been carried out in different time periods,
given financial constraints that have not allowed conducting all the interviews during the same year.
4.2. Results of the comparative case study analysis
The analysis of the four case studies leads to contribute to the present understanding of the
interwoven evolution of clusters and MNEs. The emergence and the entrance of the MNE may
occur in different stages of the life cycle, giving rise to a variety of growth patterns which affect
MNEs and clusters (Belussi and Sedita, 2009). Table 2 contains basic structural information on the
year of birth, size, sales, specialization, and phase of the life cycle of the four clusters in 2010. The
phase of the life cycle in which each MNE enters or emerges is also specified. Other relevant
information are added concerning the list of the largest MNEs operating in the clusters and the
emergence of homegrown MNEs. Moreover, some structural indicators (number of firms sales, and
employees) and innovative performance are reported.
INSERT TABLE 2 ABOUT HERE
The empirical evidence gives support to the hypothesis of the heterogeneity of MNEs entry
modes, which lead to different impact on clusters.
Considering the MNEs entry in the origin phase of the cluster, Timisoara and Pinggzhou show a
different pattern of evolution. Timisoara (North-West of Romania) represents a “Satellite cluster”5
that only evolved thanks to the external investments. In 2004 the cluster was composed of 300 firms
and 33,000 employees. The origin of the Timişoara footwear cluster is rooted in the presence of a
bulk of state-owned companies (such as Guban, Filty and Banatim in Timişoara; Libertatea in Arad;
5
We use this term instead of satellite platform utilized by Markusen (1996), to identify clusters dependent from
external MNEs. Our typology specifically refers to clusters and not to other FDI.
13
and Solidaritatea in Oradea) that produced shoes. The cluster took off after 1989, thanks to the
entry of foreign investors who acquired many state companies on the brink of economic collapse,
and created brand new plants. MNEs came to Romania mainly to explore the cost opportunity
offered by local labor costs. Local firms are mainly subcontractors of Western companies and the
main products are footwear items of medium quality for men, women, teenagers and children.
Outside the activities of the MNEs, the cluster has a very low share of endogenous entrepreneurs
and of innovative capabilities. Moreover, the cluster collective organizations are weak. MNEs
located in the area do not have many knowledge links with other local firms, but work mainly with
their headquarters located in Italy or Germany. Thus, there is little spillover at the local scale
(Belussi, 2010b; Montagnana, 2010). The MNEs entry did not boost local entrepreneurship.
The case of Pingzhou in the Pearl River Delta of the Guangdong province (China) describes
what we labeled an “Evolving satellite cluster”. In 2004 it counted 600 firms and 60,000 employees.
The origin of the footwear cluster is linked to the entry of a small number of Taiwan-based MNEs
in the area, which created a number of JVs with Chinese entrepreneurs. As in other areas of
Mainland, MNEs started entering China (and Guangdong in particular, which hosted the first
Special Economic Zone) after the open door policies (1979), which allowed foreign investors to
settle their business there. Until the beginning of the 2000s, this entry had to take the form of a JV
with a Chinese partner. However, unlike the case of other types of foreign investors, the Taiwanese
business has always been strongly rooted in the local Chinese economy, also by means of overseas
Chinese familiar linkages (Menkoff and Gerke, 2003). In 2004 local firms represented around 70%
of the number of total firms, while MNEs had a leading position in the productive chains (Bellandi
and Caloffi 2010). In the initial growth of the cluster, the MNEs are little involved in an effort to
upgrade the skills of the local labor force. However, during the time, as it has happened in many
other Chinese clusters, local entrepreneurs can be forced to upgrade their processes and products –
under the challenge provided by their MNEs final clients.
14
In the case of the Montebelluna sportsystem cluster (Northern Italy, Treviso province), which
has been defined as “Evolutionary Marshallian cluster”, MNEs grew embedded in the cluster, as a
process of expansion of small local firms, occurred in the maturity phase. The cluster is now
characterized by a significant number of SMEs, family-owned firms, and a few important local
larger companies, deriving from the original nucleus of the first founders, which were created at the
end of the last century and during the first decades of the Nineteenth century (Tecnica, Caberlotto,
Calzaturificio Alpina, Dolomite, Munari, and Nordica). The cluster is formed by 400 frims and
8,000 employees in 2011. The take-off of the district occurred during the 1960s. The number of
firms grew dramatically during the 1970s, thanks to the innovative products (plastic ski boots) that
the local district’s firms were able to introduce into the market. During the 1980s, new market
niches were created. The evolution of clusters is linked to the emergence of local “homegrown”
MNEs, like Geox and Stonefly, and the entry from outside of some global leading multinational
companies (e.g. Rossignol, Lange, HTM, and Nike), which settled in the cluster in the 1990s
through the acquisition of local companies. Big multinational firms in the recent years have located
their prototype development and design branches in Montebelluna in order to gain access to
employees and knowledge about design and material. The main change of the cluster happened
during 1990s when local firms started to delocalize and outsource labour-intensive manufacturing
phases abroad in low-cost countries (Romania, Hungary, and China). Local firms are typically very
innovative; they perform internal R&D, and are able to build external linkages - such as interaction
with international clients, participation at international fairs, and the utilization of national
consultants (Aage, Belussi, Sedita, and Porcellato, 2011).
In the case of the Riviera del Brenta (Venice province, Italy), we are encountering a typical
Marshallian district which evolved into what we called here a “Multinationalized Marshallian
cluster”. This footwear cluster is now formed by about 600 footwear firms and 11,000 employees
in 2010. The development of the cluster dates back to 1989, when the firm Voltan was founded
(Amighini and Rabellotti, 2006). The rapid process of take off occurred during 1960s and 1970s, in
15
connection with growth of the EU market. The competences on shoes manufacturing growth during
1990s, and the district firms specialized in high quality woman footwear. At the end of 1990s a
process of internalisation took place through the delocalisation of the most labour-intensive tasks to
low costs foreign subcontractors, mainly located in eastern countries. At the same time many
producers focused on high quality products in order to escape the competitive pressure coming from
China. Later in the 2000s the cluster experimented the entry of MNEs like Armani (calzaturificio
Guardi), Gucci PPR group which has acquired two local firms, Prada, which has acquired Lamos
and Luis–Vuitton, being part of the French LVMH which has acquired Corrado Maretto, Monique,
Arcad and the largest firm of the district: the calzaturificio Rossimoda). The entry of the global
multinational of fashion changed the nature of the old Marshallian district, which is now a
Multinationalized Marshallian cluster.
5. Conclusions
Nowadays the consideration of the interplay between location and ownership and internalization
advantages of the MNEs has become a crucial issue. On the one hand local cluster firms can benefit
of knowledge spillovers from the local activity of MNEs. On the other hand, MNEs can benefit of
choosing appropriate locations in low costs countries, and/or of absorbing local knowledge
produced in certain localities.
This article concerns MNEs entry modes in industrial clusters. Despite the model of industrial
cluster has been often discussed as locally self-contained, various empirical researches have
recently pointed out its increasing involvement in the process of internationalization. This is
occurring not only in terms of flows of exports, but also in relation to a more complex interchange
of inwards and outwards flows of goods, people, knowledge, which often involve the MNEs as
crucial players (Giuliani et al. 2005). There is now a vast literature that explores in detail the role of
MNEs. In this paper we have linked it to the analysis of cluster dynamics and life cycle model.
16
In some cases, MNEs are the main actor responsible to giving rise to the local cluster, while in
others they enter (or emerge in) the local cluster in one of the subsequent phases of its life cycle
(maturity).
An important aspect is in our view is related to the rise of homegrown’ MNEs. In both two of the
Marshallian clusters analyzed they supported the internationalization process. However, not in all
Marshallian clusters firms were able to invest strategic resources in innovation and market
expansion, and progressively transform themselves into MNEs. This is the cases of Riviera del
Brenta, were local firms were acquired by external MNEs.
Our paper analytically described the heterogeneous role of the MNEs within the clusters. We
reviewed the relevant literature on this issue and we applied a comparative case-study analysis. The
results of our analysis suggest the existence of a variety of evolutionary dynamics where, in some
cases, the MNEs originated the cluster, in some others, they emerged out of a process of expansion
of local small firms, and, in others, the MNEs were attracted into the cluster in a development or
maturity phase. The heterogeneity of cluster evolutionary dynamics related to MNEs entry opens up
a wide space to the formulation of specific cluster policies, oriented to establish adequate measures
for the attraction and localization of MNEs and for the internationalization of leading cluster firms.
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Table 1 – The relevant literature on clusters and MNEs
30
Source: Elaborations of the authors from ISI-Thomson Reuters Web of Science
database (ISI – Oct. 2011).
Note to table 1: [H] identifies cases of homegrown MNEs, that is cases when a
cluster firm becomes a multinational. Articles marked with an asterisk discuss cases
where the cluster originates the MNE.
31
Table 2 – The four case studies
MNEs entry in the origin phase
MNEs entry in the development/maturity phase
Year of birth
# Firms
# Employees
Sales (mln.€)
Specialization
Type
Pingzhou footwear cluster
1980s
600
60,000
241
Footwear
Evolving Satellite cluster
Timisoara footwear cluster
Beginning of 1990s
300
33,000
200
Footwear
Satellite cluster
MNEs*
No famous brands
Geox, Cesare Paciotti
MNEs motivation
Low cost of labor, proximity to the
MNEs’ headquarters, presence of
overseas Chinese familiar linkages
Low cost of labor, proximity to the MNEs’
headquarters
Core competences
Sales variation after MNE
# Firms variation after MNE
# Employees variation after MNE
Innovative performance after MNE
Manufacturing
+
+
+
+
Manufacturing
+
+
+
=
maturity phase
Riviera del Brenta footwear cluster
1960s
700
12,000
1,800
Luxury shoes
Multinationalised Marshallian cluster
(MNEs acquired by MNE)
Montebelluna sportsystem cluster
1950s
400
8000
2,200
Sportswear
Evolutionary Marshallian cluster (with
emerging Homegrown MNEs and MNEs
entry)
Geox (H); Stonefly (H). Rossignol, Lange,
HTM, and Nike (A)
Global market, local knowledge on
manufacturing technologies, existence of
good suppliers with high competences
Technology, Design
+
+
Armani, PPR-Gucci, Prada, LVMHLouis Vuitton (A, maturity)
Local knowledge on manufacturing
high quality women’s shoes,
competences on pattern design, local
know-how capabilities in machinery
adaptation
Handcraft abilities
+
+
Source: Authors’ fieldwork.
Note to table 2: * list of major MNEs in the cluster in 2010; A=Acquisition, H=Homegrown; “Sales variation after MNE” indicates if the total sales of the cluster increased (+),
decreased (-), or remained stable (=) after the entrance/birth of the MNE; “# firms variation after MNE” indicates if the total number of firms in the cluster increased (+), decreased (), or remained stable (=) after the entrance/birth of the MNE; “# employees variation after MNE” indicates if the total number of employees in the cluster increased (+), decreased (-),
or remained stable (=) after the entrance/birth of the MNE; “Innovative performance” indicates if the innovative capacity of the cluster increased (+), decreased (-), or remained
stable (=) after the entrance/birth of the MNE.
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