“how clusters learn: evidence from a chilean wine...
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“How clusters learn: Evidence from a Chilean wine cluster”
Elisa Giuliani University of Pisa and SPRU, University of Sussex
Paper to be presented at:
EADI Workshop Clusters and Global Value Chains in the North and the Third World
Università del Piemonte Orientale Via Perrone 18 Novara - Italy
October 30th –31st 2003
(preliminary draft)
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Introduction
From an orthodox perspective, trade openness is considered an engine of growth (see, for example, Krueger,
1997, Srinivasan and Bhagwati, 1999), since, among other things, it facilitates international technology
transfer and reduces the technological gap between advanced and industrialising countries. While this is the
dominant view, there is a school of thought that questions the existence of any direct relationship between
trade openness, technological catching up (see, for example, Cimoli and Correa, 2002) and convergence (see,
among others, Rodriguez and Rodrik, 1999). More specifically, this perspective argues that macro policies
are not sufficient to explain the phenomena, which needs to be analysed looking at the relation between
macro, meso and micro dimensions (Katz, 2000).
A different view is that of evolutionary economics, which has generated both empirical and theoretical
contributions to explain the nature of technological change and the dynamics of productivity growth, based
on different assumption from mainstream economics1. Briefly, the underpinnings of these contributions are
based on the conception of firms as heterogeneous agents whose knowledge base is the result of a cumulative
process of learning which is a precondition for technical change. This view has influenced studies on
industrialization and technological change in developing countries, providing a shift in the interpretation of
technology generation and change with respect to neoclassical theories. As stressed by Bell and Pavitt
(1993), “the process of technical change in dynamic industries in developing countries bears little
resemblance to the technology adoption process represented in conventional innovation-diffusion models”
(Bell and Pavitt, 1993, pag. 158). Instead, it is more a story of technological adaptation and incremental
improvement, which allows firms to create a cumulative path of learning and the basis for future technical
change (Dosi, 1988).
This paper analyses the process of technological upgrading of a cluster in the wine industry, trying to provide
an alternative view to the one that attributes mainly to trade openness the reduction of the technological gap
with advanced countries. This particular industry is an interesting one to analyse as it has undergone a period
of intense technological upgrading and is now competing at the international frontier. While trade openness
is considered an important component to increase production capacity, this paper argues that the formation of
knowledge linkages at micro, meso and macro levels have contributed to the process of knowledge
improvement and change in the industry.
The paper is structured as follows: in Section 1 a brief theoretical overview is presented that includes the
analysis of knowledge linkages in clusters (meso and micro) and the concept of National System of
Innovation (macro). Section 2 will focus on the macro-economic framework of Chile and the historical
1 For an extensive literature on evolutionary theories see: Nelson N., Winter S. (1977); Dosi et. al. (1988); Nelson R. (1995).
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evolution of the wine industry in the country. The methodology is presented in Section 3, while Section 4
analyses and comments the empirical findings.
Section 1. Theoretical Framework and Research Question
1.1.From micro-to meso: do clusters matter for technological learning?
Starting from the 90s, there has been a growing interest in the analysis of clusters in developing countries.
Following the successful experience of Italian industrial districts (Becattini, 1979; Pyke et al. 1991), several
scholars have studied clusters in less advanced countries2. In those contexts, clusters are conceived mainly as
geographically agglomerated firms operating in the same or interlinked industries (Schmitz and Humphrey,
1995; Altenburg and Meyer-Stamer, 1999) and are believed to be a viable way to foster the development of
small local (informal) industry and to eliminate the growth-constraints of small realities (Schmitz, 1982):
"….such clustering opens up efficiency gains which individual firms can rarely attain." (Schmitz, 1995, pag.
530). More specifically, two main approaches have been developed in the analysis of clusters in developing
countries3: on one hand the ‘collective efficiency’ approach (Schmitz, 1995) emphasises the importance of
productive linkages and co-operation among clustered firms ad its impact on performance; on the other, the
‘Local System of Innovation’ approach, bases on the evolutionary theory of the firm and analyses at local
level the linkages that spur firms’ innovation (Cassiolato and Lastres, 2000). While the former approach is
more analytical and focuses mainly on the analysis to local productive linkages (Bell and Albu, 1999); the
latter is rather descriptive and focuses more on local knowledge flows and interacting learning. Indeed, there
is a growing agreement on the importance of knowledge and technical change for the dynamic interpretation
of industrial clusters (Rabellotti, 1997) and on the need to develop more analytical studies on this topic (Bell
and Albu, 1999).
In advanced countries’ contexts, clusters and districts are often seen as an ideal locus for collective learning
and incremental technical change (Bellandi, 1989; Capello, 1999). Since Marshall’s (1920) idea of
‘industrial atmosphere’, different contributions have reinforced the idea that the local environment becomes
crucial in the process of enhancement of firms’ capabilities and therefore clusters and districts are viewed as
cognitive laboratories (Becattini and Rullani, 1993; Rullani, 1994). According to different schools of
thought, geographic proximity (Camagni, 1991), productive linkages and social embeddedness (Becattini,
1990; Dei Ottati, 1995) generate at local level the conditions for diffusion (i.e. spillovers) and creation of
knowledge on an endogenous basis.
Albeit this view is supported by a multitude of empirical evidence in advanced countries (see e.g. Regional
Studies, 33(4), 1999), a doubt exists that this is not the case in developing countries. Firms’ knowledge bases
(Dosi, 1988) might be so distant from technological frontier that the diffusion of localised knowledge within
2 See, among others, World Development, Special Issue, 27 (9), 1999. 3 For a review see Giuliani (2002)
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the cluster might simply reproduce existing competencies and generate an ideal environment for negative
lock-in (Camagni, 1991; Grabher, 1993).
Indeed, several scholars now have suggested that clusters or districts cannot be viewed as engines of
endogenous knowledge creation, disconnected from the rest of the world, but, on the contrary, they need to
be interconnected with external sources of knowledge to rejuvenate intra-cluster knowledge and avoid
isolation (Camagni, 1991; Freeman, 1991; Schiuma, 2000). In developing countries, the capacity of clustered
firms to interlink with external sources of knowledge is therefore a critical one. Hence, clusters ought not to
be viewed in isolation from the context in which they operate. More specifically, the capacity to absorb
extra-cluster knowledge and to diffuse it at local level is important to foster development and improve local
performances (Giuliani, 2002). The intention of this work is therefore that of emphasising the importance of firms and their knowledge
endowments (i.e. absorptive capacity, degree of experimentation etc.) for the process of learning of a cluster
and for its degree of interconnection with extra-cluster sources of knowledge as, in this case, the National
System of Innovation.
1.2.The Macro-dimension: the National System of Innovation
1.2.1. The concept of National Innovation System
The National System of Innovation (NSI) is conceived as a network of institutions whose interactions
determine the innovative performance of national firms (Nelson and Rosenberg, 1993) or more specifically
as a set of distinct institutions which jointly and individually contribute to the development and diffusion of
new technologies and which provide the framework within which governments form and implement policies
to influence the innovation process. As such, it is a system of interconnected institutions to create, store and
transfer the knowledge, skills and artefacts which define new technologies (Metcalfe, 1995)4.
Hence, according to a broad definition of NSI, “institutions are embedded in a much wider socio-economic
system in which political and cultural influences as well as economic policies help to determine the scale,
direction and relative success of all innovative activities” (Freeman, 2002, p. 194). In a narrower sense,
instead, a NSI corresponds to those institutions, which deliberately promote the acquisition and
dissemination of knowledge and are the main sources of innovation. Therefore, in this last perspective,
institutions are conceived as organisations, formal institutional bodies where the innovative activity is
pursued (e.g. universities) (Niosi, 2002).
By its definition, NSI has three main essential features:
4 The concept of National System of Innovation, developed seminally by Friedrich List’s The National System of Political Economy (1841) (Freeman, 2002), has been applied to the analysis of differentials in growth and Science&Technology development between countries and has been diffused over almost two decades now.
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↔ national scope;
↔ systematic relations between institutions;
↔ innovation and technological change.
As regards the first point, the approach is primarily concerned with the national context despite the
controversies raised by different contributions which, on one side, suggest that, in an increasingly globalised
world, one should go beyond the nations; and on the other focus on sub-sets of the national systems,
developing concepts like ‘regional systems of innovation’ (Cooke, 1996; Cooke et al., 1997), ‘technological
systems’ (Carlsson and Jacobson, 1994) or ‘sectoral systems of innovation’ (Breschi, Malerba, 1997;
Malerba, 2002). Indeed, being the nations still political entities with innovation policy’s agendas, it is still
important to maintain an analytical framework at this level, which is nonetheless interwoven with other
approaches focused on the ‘meso’ (i.e. regional, sectoral) level. Moreover, different empirical studies seem
to indicate that the nation-specific innovation system remains important for explaining innovation rates (see
e.g. Archibugi and Michie, 1995 and Patell and Pavitt, 1994).
The systemic character of the NSI suggests that it needs not to be conceived as a simple aggregation
of formal institutions. Instead, the concept includes human and knowledge linkages between universities,
firms and governmental institutions, regulating flows from government agencies towards innovative
organisations and also financial flows between government and private organisations (Niosi, 2002). Of
course, this ought not to be considered as a set of characteristics, which are present by definition within a
NSI. There is an enormous heterogeneity between countries in their way of operationalising this framework
and adopting the process of interactive learning within the NIS.
As regards the last point – innovation and technological change– a distinction needs to be cast between
advanced and developing countries. In fact, the NSI approach has been also applied to the analysis of
economic development in late industrialising and developing countries. Starting from seminal works by Kim
(1993), Dahlman and Frischtak (1993) and Katz and Bercovice (1993), there has been an interest by different
scholars in the application of this framework to such contexts. At this respect, two main issues need to be
raised here: the first one concerns the limits of the applicability of the narrow concept of NSI to developing
nations, because, as stressed by Lundvall et al. (2002), "a narrow innovation system concept focusing on the
research and development system and on high tech and science-based innovations makes [limited] sense in
the South" (Lundvall et al., 2002; p. 226). While the second refers to the fact that developing countries
depend very much on technologies and systems of innovation of other more advanced countries; as stressed
by Intarakumnerd et al. (2002), "the effective utilisation of foreign technology is more important than doing
a lot of R&D in some east Asian NIEs such as Hong Kong and Singapore" (Intarakumnerd et al., 2002; p.
1446).
The understanding of NSI in developing countries is therefore important as it can shed light on their
commitment in reducing the gap, or otherwise on letting it grow. Different contributions (among others, Gu,
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1999; Intarakumnerd et al., 2002; Lundvall et al., 2002) suggest that the NSI in developing countries have
the following characteristics:
↔ They are less developed. Historically, the technological and institutional properties necessary for
modern growth were not developed within their systems. NSI in developing countries should hence be
studied in the context of economic development.
↔ They are specifically related to the country’s development stage and structural and institutional
development.
↔ Unlike developed countries, capital accumulation and learning, rather than innovation, are the main
contribution to technical progress in developing countries.
The lack of technological capabilities, hence, renders the concept of NSI strictu sensu, potentially
unproductive for developing countries. This has been suggested also by Viotti (2002), who adapts the NSI
approach to late industrialised countries and develops the concept of National Learning Systems (NLSs)
because it is learning in its various many meanings that matters in such contexts rather than innovation per
se. In fact, while in the past the US and Germany caught up by radical innovations in new industries (i.e.
steel, oil, chemicals), today "the latecomer firms may not have the option of radical innovation in new
industries and have no alternatives but to pursue the path of imitation and learning" (Freeman, 2002; p. 200).
Viotti (1997; 2002) distinguishes further between active and passive NLSs, because he assumes that even
within ‘ideas-using’ (Romer, 1990) systems of innovation, there are two different approaches to
technological use and technology absorption: on one hand, firms and formal institutions might adopt
technologies with a minimal effort, assimilating just the abilities needed for the establishment of the capacity
to produce certain goods or services (e.g. turnkey projects or purchasing of equipment packages linked with
technical assistance from the capital good suppliers). On the other, technological absorption is characterised
as active absorption, when a more intense effort is done by firms or institutions in adapting the technologies
acquired (e.g. by reverse engineering and imitation). In this latter case, hence, a process of active learning
takes place, which can produce incremental innovations.
1.2.2. National Innovation Systems in Latin America: R&D institutions and knowledge linkages
It was no later than the ‘60s, when the first Latin American scientific and technological organisations
emerged. Indeed, the National Institute for Scientific Research (INIC), precursor of the Consejo Nacional de
Ciencia y Tecnologia (CONACYT) was created in Mexico in 1950. Similarly, other institutions were
established along the region, such as the Brazilian National Research Council (CNPq) (1951), the
Argentina’s National Council for Science and Technology (1958). During the 60’s and 70’s most of LA
countries developed such organisational structures, to promote, coordinate and carry out research both in
applied and pure sciences (Katz and Bercovich, 1993). Intellectual property protection laws were also
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developed, as in the case of Brazil and Mexico that introduced in 1971 and 1973 an Industrial Property Code
which specified the patent, trademark and trade secret regimes (Alcorta and Perez, 1998). In general, during
the period of import-substitution policies, concerns for science and technology were high, which made them
be often incorporated into development plans. Human resources formation was also sustained in specific
sectors, such as nuclear energy, telecommunications, petrochemicals, informatics, microelectronics and
biotechnology. Also financial funds were made available to finance research and technological change.
Hence, the public sector has played an important role, historically, in the development of a NSI and the
‘narrow’ NSI has had a marked feature of strong state influence.
After the ‘lost decade’, in the 80s, the macroeconomic scenario changed dramatically in almost all LA
countries which since then were subject to structural adjustment programmes5.
As an immediate consequence, there has been a considerable reduction of the participation of the State in
S&T development. Furthermore, the exposure to international competition and the adoption of the new
‘market-oriented’ growth paradigm has driven the region’s productive system towards a process of de-
industrialisation and specialisation in industries with low domestic knowledge generation and value added
content (Katz, 2001; Katz and Cimoli, 2002). Thus, along with a reduced intervention of the state in the
research activities, firms have reduced their R&D and engineering activities, no longer necessary due to the
easier acquisition of foreign products with high technological content.
At the same time, one needs to acknowledge that technology policies, developed in Latin American before
the ‘90s, were ‘leaking’. Indeed, in a broader view, the NSI/NLSs of the import substitution-period, have
also been based on the import of technology. But if in other countries, like Japan and South Korea, the
import of technologies was part and parcel of their industrialisation strategies, in Latin America these
strategies were disconnected from the innovative activity performed by importing firms. There wasn’t, in
other words, a concurrent complementary research, development or engineering effort by the importing
firms. As a consequence, technology imports were only rarely assimilated into the continuous process of
technological accumulation (Cassiolato and Lastres, 2000).
Even in the narrower sense, the NSI was flawed and lacked of clarity in the objectives that were pursued
(Alcorta and Perez, 1998). As an example, there has been, over the decades, a proliferation of (sometimes
ad-hoc) institutions, with scarcely coordinated programmes. Different diverging and overlapping projects
were developed without the necessary qualifications or without a clear objective and often these were not
matched to demand. Others (Frischtak, 1990), remark the lack of specialisation as a further weakness in LA
innovation systems as they tended to increase the scope of their plans, programmes and instruments to such
an extent that they finally become difficult to implement.
Moreover, many institutions were unable to keep the pace with knowledge advance in their field nor were
actively engaged in a process of learning and networking with domestic and international partners (Alcorta
and Perez, 1998). There has always been often very little consultation with the private sector, which left the
programs developed, as said, to a dead-end.
5 Chile makes an exception in Latin America as there neo-liberal policies were implemented since 1973.
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In the ‘90s, an increased pressure was exerted on R&D institutions and firms for the achievement of
efficiency and competitiveness in order to be able to benefit from governmental programmes (Alcorta and
Peres, 1998). In this view, various projects have been developed to foster collaboration of the private sector
with public research institutions (e.g. PROFOs in Chile).
Along with Institutions, linkages are considered one of the main weaknesses of Latin American countries.
Also in this case, empirical evidence is scattered and unsystematic: on one hand, in fact, there are successful
cases, which tell stories of close co-operative relations between users and producers of technologies. To
mention few of them: a research led in Brazil shows a successful and co-operative relationship between
financial institutions and manufacturers of banking automation equipment in Brazil (Cassiolato, 1992); to
this one could add the experiences of SMEs clusters that show in some cases a moderate degree of vertical
and more rarely horizontal co-operation within localised firms and also with local and national institutions
(see among others Schmitz, 1999; Cassiolato and Lastres, 2000; Villaschi and Bueno, 2000; Campos,
Nicolau and Carios, 2000). In some of the case-studies above-mentioned, the co-operative relations have
been developed both between firms and between them and public research institutions and universities. In
the first case, as said, the relationships developed were mainly user-producers while horizontal co-operation,
that is, between firms performing the same type of activities (i.e. competitors), is scarce: informing cases at
this respect are that of the footwear cluster in Sinos Valley (Brazil) (Bazan and Navas-Aleman, 2001;
Schmitz, 1999; Vargas, 2001), the high-tech and software cluster of Joinville (Brazil) (Campos, Nicolau and
Carios, 2000); the sugar cluster in Valle del Cauca (Colombia) (Millan Constain, 2002) and the salmon
productive area in the Austral Region (Chile) (Maggi, 2002).
In other cases, local firms have established strong relationships with Universities and Research Labs. This
tends to occur especially in resource-based and agro-food industries and that depends on university research
for innovation (Pavitt, 1984). In these cases, local firms rely on basic and applied research, which they are
unable to sustain in-house. The cluster of Mangoes and Grapes’ in the area of Petrolina-Juazeiro (Brazil) is
an excellent example of high involvement of the institutional bodies (development agency like CODEVASF;
research institutions like EMBRAPA etc.) and local small and large growers (Gomes, 2002).
Despite these successful cases, the overall picture in Latin America is different and more critical. In fact,
user-producer, not to mention horizontal linkages are weak and firms tend to have an uncooperative
behaviour towards innovation (CEPAL, 1992). Also in this case one could mention various examples of low
joint commitment with reference to inter-firm relations: in traditional manufacturing the cluster of Gamarra
in Peru (Visser, 1999) is one where firms have very poor relations as well as the furniture cluster of Ubà
(Minas Gerais) in Brazil (Crocco and Horacio, 2001); this is also typical of the Northern regions of Mexico,
where the type of production based on ‘maquilas’, constitutes a disincentive to co-operation (see, among
others: Bair and Gereffi, (2001) for garment; Dussel (1999) for electronics; Carrillo, Mortimore and Estrada,
(1998), for audio-visual equipment).
Linkages with universities are another issue of concern. These have been historically very poor (Plonsky,
1993); in fact, during the Import Substitution period, there was little interest to cooperate because protected
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market conditions did not require firm to innovate and be competitive with imported products. At the same
time, universities had little incentives to transfer technologies to business because research was not financed
by privates but still by the Government.
Since the 90s, the situation has changed considerably and different policies have been focused on university-
industry linkages. It is not only government that fosters such initiatives but also international, multilateral
organisations (i.e. BID- Interamerican Development Bank) have provided universities with international
loans for the purpose.
For the time being there is no clear understanding of the results of this type of programmes, which are not
easy to assess. In particular, as stressed by Arocena and Sutz (2001), it is not clear if once loans have expired
and university-industry technology programmes finished, an innovative culture will remain in place.
1.3.Research Question
The idea of this work is that of merging micro (i.e. firm), meso (i.e. cluster level) and macro (i.e. national
system of innovation) levels of analysis and to describe what is the learning behaviour of firms in a catching
up wine cluster in Chile. This could be particularly informing as the cluster taken into consideration is a
successful one since many of its constituting firms have attained international appraisal and are now adopting
frontier technologies for production (Crowley, 2000; Schachner, 2002). The success of the area is certainly
due to excellent natural endowments (i.e. terroir) and to the effort done by firms in upgrading their
competencies and machine-embodied technologies. When specifically asked, key informants, in fact, all
agreed that private investment was the major responsible for the industry success. Furthermore, given the
weakness of Latin American National Systems of Innovation (Par. 1.2.2.), one would be inclined to think
that the role of institutions (both in a narrower and wider sense) in the growth of this industry is non-
relevant.
This study is an attempt to go beyond these perceptions and provide empirical evidence that traces
knowledge linkages between firms at local level and between these and the National System of Innovation.
Albeit these linkages can explain only part of the upgrading process, it is believed that the institutional side
of the story ought not entirely be overshadowed by other factors (e.g. the market).
Hence, this work is meant to shed some light on the following research questions: “Was the process of
technological upgrading in Colchagua Valley only the result of firms’ investments in foreign, frontier
machine-embodied technologies? Or, rather, there is another story that can be told, which includes
accumulation of knowledge at firm level and development of knowledge linkages both at meso and macro
levels?”
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Section 2 Historical overview of Chile and its wine industry
2.1. Chile: a brief overview of the macroeconomic frame
If compared with other countries of the region, Chile presents a different developmental history and it is
often considered among policy-makers as a shining star, a positive example of the perseverance of neo-
liberal reforms6. Chile implemented market-oriented policies right after the coup d’etat leaded by Pinochet in
1974. While overthrowing President Allende, the new military regime dismissed import-substitution policies,
which had been the main development paradigm since the 40s. In the period between 1974 and 1979 the
policies that were implemented were guided by the idea that once the market forces had been assured,
resources would be allocated without costs to export industries in which the country had comparative
advantage, thus leading to rapid growth of exports and overall production (Agosin, 1999). Yet, in a small
country like Chile, exports seem to play a core role for growth, because they foster production and
diversification much more than the limited and relatively poorer domestic market.
More in detail, the monetarist orthodoxy implemented by the authoritarian regime in the second half of the
70s, was aimed at promoting three main strategies: the anti-inflationary programme, the financial sector
reform and the opening to foreign trade. Moreover, the programme emphasised the importance of the market,
of privatisation and economic openness. For the above-mentioned reasons, the model implemented in Chile
is considered an extreme or ‘pure’ case of monetary policy.
While a detailed analysis of the short, medium and long-term effects of this type of policy is beyond the
scope of this present work, suffice here to say that the monetary ‘experiment’ got stuck in 1981, when
domestic recession, reinforced by the depression of the world economy, and excessive accumulated foreign
debt, throw the country into a severe financial crisis in 1982. According to Ffrench-Davis (1983), the
previous policy has intensified vulnerability to the external sector and hence worsened the effect of the
financial crisis. The GDP fell by 14,1% and the whole banking system had to be taken over by the
government because it could not pay its foreign currency debt. Approximately 50% of the private firms were
handed back to the control of the state because of their incapacity to solve financial debt. In effects, Chile
entered into a recession phase. As a response to the crisis, new policies were implemented after 1982, which
still had a neo-liberal imprinting but included a moderate involvement of the state and policy interventions to
solve market failures. The period in-between 1982 and 1991 has subsequently been named pragmatic to
counterpoise it to the pure monetary period. The neoliberalismo paragmatico, as it was called, has been
characterised by an increase in barriers to imports, the introduction of subsidy for export, an increase in
privatisation and a major control of the financial system, including the regulation of the interest rate
6 Indeed, Stiglitz (2002) argues that it is because Chile did not follow the standardised measures suggested by the IMF but adapted them to the specific requirements through the reforms applied in the 90s, that it did work so relatively well.
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fluctuations. The recovering of Chilean economy was gradual, reaching his culminating point in 1989. In
1990, democracy was re-established in the country and the new government started a decade of policies,
which were moderately adjusting those implemented in the previous period. Indeed, the economy was still
led by the exports and the trade policy implemented by the government was aimed at sustaining trade
openness, through preferential free trade agreements and export promoting institutions (i.e. PROCHILE).
From an industrial point of view, the 90s assisted, similarly to other countries in the region, to a pattern of
specialisation towards resource-based, capital intensive activities (Katz, 2001).
3.2. The Wine industry in Chile: an historical overview
The wine industry is certainly a peculiar case among resource-based productions. It is regarded as a non-
traditional primary product and differs from other resource-based industries in the sense that it is less
commodified. In some Latin American countries, it has experienced a considerable expansion and
modernisation in the past few decades (see e.g. Snoeck, 1999; Vargas, 2001) and it has been able to compete
successfully in the international markets. Among the successful new world’s countries, Chile, has reached
outstanding export performances (Crowley, 2001) which makes of it an interesting case study for analysis. Yet, production and consumption of wine in Chile is not so recent as it could appear. In fact, wine
consumption in Latin America was introduced by Spanish conquerors in the XVI century. They not only
imported Spanish wine but also started to plant a vine variety called Mision in Mexico, Negra Peruana in
Peru, Criolla Chica in Argentina and Pais in Chile. In that period, in Chile, the production of wine started in
the area surrounding Santiago and expanded quickly to other areas. During two centuries, the production of
wine increased and it was mainly oriented towards the domestic market. After the independence (1808),
Chile experienced a period of economic growth, which coincided also with the immigration of European and
North American populations in the country and the start up of new entrepreneurial activities. Interestingly
enough, this period was characterised as well by a drastic change in wine consumption and production styles.
In fact, the high regard of Chilean elites for French population and habits, stimulated imitation and visits to
France (esp. to Bordeaux). Imports of French wines increased and, as a consequence, French vines were
imported during XIX century and gradually substituted the autochthon variety País7. This new generation of
vineyards, mainly constituted by French varieties, were most of the times property of Chilean
entrepreneurial groups proceeding from second generation families (‘second wave’ of conquests in the XVIII
century). The result of the changes experienced in the period 1850-1880 proved to be important in shaping
the evolutionary trajectory of the industry over the years. From then onwards, in fact, the quality of wine
increased as well as vineyard plantation area.
During the period 1938 and 1979, though, the trend in wine production and consumption changed drastically.
A Law was approved in 1938 (Ley de Alcoholes, 1938) that limited wine production and vineyard planting
7 It’s worth reminding that the influence of Bordeaux was not only in Chile but also in other countries such as California, Swiss Crimea and Caucaso, in Argentina (Mendoza). Several varieties were introduced in each area: Semillon, Merlot, Cabernet.
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until the sector was re-liberalised by the Military government in 1973. At that time, trade liberalisation
polices allowed for a sustained process of renovation of the wine industry, which started producing
according to new standards and for the international markets8.
The main stylised facts of the history of wine production in Chile are summarised in Table 1 below.
I. Before 1850 • Spanish conquerors and Jesuits imported wine and later produced wine in the country (País)
• First generation of big ‘viñaderos’ • Development of different wine areas in the country: Concepcion, Coquimbo, Region Central, etc. • Low quality of wine and mainly domestic consumption
II. During the 1800 • 1808, Independence, economic growth, arrival of EU and US people. French people generated appreciation by Chilean people and stimulated visits to Bordeaux • 1850 : introduction of French vines • Improvements in the techniques due to French experts coming to the country • Governmental support to the Industry: Infrastructure, Human Capital and Credit • New structure of the industry: new vineyards founded by French oenologists • New investment by second generation Chilean entrepreneurs operating on other sectors
III. 1880-1938 • Expansion and consolidation of existing firms • Foreign families concentrate in trade and retail (bodegueros) • Domestic consumption • Universities
IV. 1938- 1973 • Ley of Alcoholes (1938) • Limited production (fines for extra planting), maximum prices were controlled (1965) • High domestic consumption of wine • Tributes • Mechanisation • Conflicting relations between big firms and small grape growers (upsurge of co-operatives and period of contestations and strikes) • Agrarian Reform in the 60s> Allende
V. 1973- 1990 • Military Dictatorship (1973-1989) • End up of the Agrarian Reform • Liberalisation of markets • Miguel Torres (1978) and introduction of French methods of production
VI. 1990- 1998 • Worldwide increase of production and consumption of wine • Development of ‘boutique’ wineries (SMEs, high quality) in Chile • Technological upgrading and international competitiveness of Chilean wines
VII. 1998- up to now • Slow down of worldwide consumption • Worldwide over-supply of wine • Reduction of International Prices and fierce competition
Table 1. Brief historical overview of the Chilean wine industry. Source: Author’s own based on Del Pozo (1998).
Historical facts provide an in-depth perspective of the wine industry in Chile, which is now among the most
competitive in the world.
During the 1990s Chile experienced a sustained growth of exports (see Picture 1) and an improvement of its
quality standards. This is most remembered as a golden period, which generated positive economic returns
and expectancies for both Chilean grape-growers and wine-producers that consequently deepened their
business commitment in the industry.
8 Miguel Torres, a Spanish wine maker, first introduced the French method and the use of barriques (i.e. a type of French barrels) in Chile in 1978.
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Exports of Wine (Volume: hl)
0500.000
1.000.0001.500.0002.000.0002.500.0003.000.0003.500.000
1990
1992
1994
1996
1998
2000
Volume (hl)
Picture 1: Exports of Wine, Chile Source: Own elaboration, S.A.G. (2002)
In the same period, strong market opportunities stimulated green-field domestic and foreign investments in
the country (S.A.G., 2002; Vergara 2001). Small and medium sized firms, producing high quality wine (s.c.
boutique wineries), proliferated and attained high performances. The second half of the ‘90s was also
characterised by a sustained increase of plantations; Table 2 shows clearly that in the period considered, the
Cabernet Sauvignon’s planted areas more than doubled while the plantations of Merlot tripled. Over the
period 1995-2000, the overall planted area in Chile doubled.
Type of Vine 1995 1998 2000
Cabernet Sauvignon 12.281 21.094 35.967
Merlot 2.704 8.414 12.824
Chardonnay 4.402 6.705 7.672
Sauvignon Blanc 6.135 6.756 6.790
Carmenère - 1.167 4.719
Total varieties 54.392 75.388 103.876
Table 2: Vine planting area (hectares), Chile. Source: SAG 2000.
While the ‘90s were driven by enthusiasm, the turn of the decade was characterised by a general slow down
of the industry which approached maturity and saturation. Moreover, fierce competition between new and
old producing countries did in fact reduce profitability margins so that the industry entered a worldwide
crisis (Anderson and Norman, 2002). It is expected that this crisis will produce a shake-out effect so that less
competitive firms will exit the sector. It is also expected that firms that will remain in the market will be
those that have invested in quality and technological capability in the past decades.
14
Section 3. Methodology
3.1. Collection of Data and Sample
The study is based on a fieldwork realised in a Chilean wine cluster in the period September-October 2002.
The cluster is localised in a wine area – Valle de Colchagua –that is situated within the VI Region, in the
central part of Chile. Data were collected through interviews based on a structured questionnaire led directly
to the technical professionals of the wine producing firms of the cluster. Being a rather small cluster, the
sample includes the whole population of fine wine producers (branded) and a small subset of bulk wine
producers (unbranded). As shown in Table 3, the sample has been determined as follows:
Wine producers
Branded Not Branded Locally grounded,
vertically integrated firms
Subsidiaries, vertically disintegrated firms
Population (N=100) Sample (n=32)
Of which : National Foreign
21 21
18 3
7 7
7 0
72 (estimate) 4
4 0
Table 3. Features of the Sample
3.2. Information collected and operationalisation of concepts
The questionnaire that was developed for the research, allowed to collect information about:
(a) human resources;
(b) technical change (both machine-embodied technology and techniques);
(c) degree of experimentation;
(d) knowledge linkages at local level;
(e) the knowledge linkages with the NSI;
(f) performances.
Relational data at local and national level [(d) and (e)] have been collected through a roster study and
analysed through graph-theoretical methods (i.e. social network analysis; Wassernann and Faust, 1994). In
the roster study, respondents were asked to indicate on a list (roster) of actors, with whom they established
knowledge linkages.
At local level, two questions (Q1 and Q2) were developed:
Q1: Technical support received [inbound] Question Q1: In the case you are in a critical situation and you need technical advice, to which of the local firms mentioned in the roster do you turn to?
15
Q2: Transfer of technical knowledge (problem solving and technical advice) [outbound] Question Q2: Which of the following firms do you think have benefited from the technical support from this firm?
Respondents were asked to provide ratings for each structural variable. The ratings are valued and ranging
from a minimum value of 0 to a maximum of 3. Both relations (Q1 and Q2) define directed linkages: Q1
defines the knowledge that each respondent firm has received from other local firms and institutions. While,
Q2 defines the knowledge that each respondent firm has transferred to other local firms.
At national level, firms were asked the following questions:
Q3: Technical support received [inbound] Question Q3: Could you mark, among the actors included in the roster*, those that have transferred relevant technical knowledge to the firm? * Please include actors that are not mentioned in the roster if they are relevant Q4: Joint experimentation Question Q4: Could you mark, among the actors included in the roster*, those with whom you have collaborated in research projects in the last two years? * Please include actors that are not mentioned in the roster if they are relevant
Also in this case, respondents were asked to provide ratings for each structural variable. The ratings are
valued and ranging from a minimum value of 0 to a maximum of 3. In this case the roster included private
firms (such as suppliers or consultants), research institutions (i.e. Universities), technology transfer institutes
and business associations.
The information thus collected was operationalised as showed in Table 4 below.
Concept Explanation and where they
are used in the paper Measure adopted
1) Firm knowledge base
Measures the absorptive capacity of firms. Used in Pars. 4.2. and 4.4.
Principal component analysis of: 1) Human Resources (degree education, years experience, n. of firms) 2) Experimentation
2) Performance Measure of performance of firms. Par 4.4.
Principal component analysis of: 1) Dimension of the firm in terms of revenues (*) 2) Price per litre of wine sold 3) Percentage of export on total production
2) External Openness Knowledge linkages of firms with the NSI Par. 4.4.
Number of linkages with extra-cluster sources of knowledge (NSI)
3) Degree of local cognitive interconnection
Knowledge linkages with other local firms in the cluster Par. 4.4.
1) Degree Centrality: knowledge linkages incident to a node (firm) 2) Out-degree Centrality: : flows of technical knowledge that originate from the firm and are directed to other local firm 2) In-degree Centrality: flows of knowledge that flows of technical knowledge that are transferred to the firm by other local firms
4) Structure of the local knowledge system
How the knowledge is diffused within the cluster Par.4.2.
1) Core-periphery analysis: allows to identify a cohesive subgroup of core firms and a set of peripheral firms that are loosely interconnected with the core. 2) Density: number of ties in a network on maximum possible ties
(*)Firm’s size is measured considering annual revenues. According to Peres, Stumpo (2001), Chilean Ministry of Economy (Ministerio de Economia) classify firms as:
a) micro if annual revenues range from 0 to 2400 UF b) small if revenues range from 2400 to 25000 UF c) medium if revenues range from 25000 to 100.000 UF d) large if revenues are above 100.000 UF.
UF stands for Unidad de Fomento, a Chilean indexation instrument, whose values vary according to the past month’s increase in consumer price index. In the period in which the fieldwork was carried out an UF corresponded roughly to 16.500 Chilean Pesos (C$).
Table 4. Operationalisation of key concepts
16
Section 4: Empirical Results
4.1. The micro-dimension: technical change and knowledge base in Colchagua Valley’s firms
According to the empirical evidence collected, the firms surveyed in Colchagua Valley have improved their
production capacity considerably in the second half of the ‘90s. More specifically, 87% of the firms sampled
declare of having adopted new capital-embodied technology in the past two years, which is at the
technological frontier. Such investments have been directed to upgrading of vineyards in 44% of the cases, to
the improving cellar technologies in 75% of the firms and in 34% of firms in bottling plants. As concerns the
introduction of new vines, one observes a relative high percentage of the both the introduction of new
varieties (62%) and new clones (53%). Furthermore, new methods of production, in both viticulture (94% of
sampled firms) and vinification (72% of sampled firms) have been introduced in the two years prior the
interview. Table 5 shows more in detail the main process innovations adopted by firms in the cluster.
Type of Innovation Number of firms % on total firms
sampled
1) Acquisition of new machinery in the last 2 years 28 87
2) Adoption of frontier technology 28 87
3) Destination of capital-embodied technology:
- vineyard
- cellar
- bottling
- other activities
14
24
11
3
44
75
34
0,1
4) Introduction of new vine varietals last 2 years 20 62
5) Introduction of new clones last two years 17 53
6) Introduction of new methods in viticulture 30 94
7) Introduction of new methods in vinification 23 72
8) Adoption of Precision Viticulture 8 25
9) Adoption of integrated canopy management 16 50
10) Adoption of organic manufacturing 9 28
Table 5: Technological change in Colchagua Valley Source: Author’s own.
These results do help to describe the degree of effort that is done at firm level in terms of production capacity
(Bell and Pavitt, 1993). In other words, they are useful to assess the degree of modernisation and adoption of
given foreign hard (machine-embodied, inputs) and soft technologies (methods of production and know-
how).
Another important element in the analysis, it’s the level of education of technical personnel in the sector. The
research shows that most firms employ technical professionals that have a degree in agronomic and
enologic-related fields or an upper qualification (master, doctorate). Table 6 shows that 75% of firms
interviewed have at least one graduate professional. In more detail, 41% of the firms have between one and
two professionals while 34% of them have more than two professionals.
17
Indeed, this data is important because such human resources can play an important ‘boundary spanning’ role,
linking firms to research institutes and universities. They moreover have high capabilities in problem solving
and it is particularly their ability in managing complex technical problems that make them so clearly
important in the firm. Particularly, these human resources become crucial when they experiment and
therefore apply their accumulated knowledge to generate new one.
N= 0 8 (25%)
N= 1-2 13 (41%)
NUMBER OF
PROFESSIONALS
(degree or upper qualifications)
N= > 2 11 (34%)
0 9 (28%)
1 8 (25%)
2 8 (25%)
3 1(3,2%)
DEGREE OF
EXPERIMENTATION
4 6 (18,8)
CONTEXTUAL 14 (70%*) TYPE OF EXPERIMENTATION
SCIENTIFIC APPLIED 7 (30%*)
Table 6: Human Resources and Experimentation *This percentage is calculated on total experimenting firms (23) Source: Author’s own
As concerns the degree of experimentation, the analysis shows that there is a high propensity of firms to
experiment: 72% of the sample perform at least some form of experimentation. More in detail, 25% of firms
do experiment in only one of the phases of the productive chain (either in viticulture, or in oenology) and
another 25% experiment in at least two phases of the productive chain. A remaining 22% experiment
internally in at least two phases of the productive chain and lead applied research in collaboration with
different Universities and/or Research Labs. Among experimenting firms, around 30% perform more applied
research while 70% tend to perform contextual research, typically embedded in firms’ routines and partially
tied to trial and error.
4.2. The Meso-dimension: do clusters matter?
Social Network Analysis allows tracing knowledge linkages between local firms. More specifically, as
remarked in the Methodological Section, what has been mapped are technical knowledge flows and joint
problem solving. Interestingly enough, it emerged that firms tend to exchange knowledge quite extensively
across the cluster (see Picture 2).
18
Picture 2: The local knowledge system in Colchagua Valley Source: Author’s own: UCINET 6.
More specifically, the work mapped horizontal knowledge ties between wineries, which implies that they co-
operate for the solution of technical problems. Nevertheless, the exchange of knowledge is not even across
firms (Giuliani, 2003), since some are better interconnected than others. Some firms also remain excluded
from the local knowledge system and hence have less chances to learn and upgrade their production.
The participation to the local knowledge system is important to acquire knowledge that flows at local level.
Provided that firms have heterogeneous knowledge endowments (Par. 4.1.), some firms might transfer to
others complementary pieces of knowledge, provide solutions to specific problems and induce technical
change accordingly. Therefore, the degree of firms’ interconnection at local level might be a proxy of how
much firms learn from their rival (local) firms.
Two main issues are raised here: is there a pattern of knowledge exchange or do firm interconnect randomly?
why some firms are excluded from knowledge transfer and what are the reasons for other firms to be
included?
To answer the first question we run a core-peripheral analysis (Borgatti and Everett, 1999) which allows to
see how knowledge flows between localised firms. The analysis identifies two main groups of firms: a core
of highly interconnected firms and a periphery of loosely interconnected or isolated firms. The results are
presented in Table 7, which shows the density of linkages within each group and across groups.
Density Average Absorptive
Capacity Core Periphery
Core (nC=14) 0,58 0, 571 0,155 Periphery (nP=18) -0,45 0,083 0,026
Table 7. Density of linkages within and between core and peripheral groups in Colchagua Valley Source: Author’s own data: UCINET 6.
As anticipated, from Table 7 it is possible to see that the density of the core group (0,571) is higher than in
the other cases. This suggests that there is an intense exchange of knowledge with a specific set of firms,
while other firms tend to remain isolated. Indeed, the density for peripheral firms is very low (0,026). An
19
inter-group pattern of knowledge transfer is also observable, since core firms transfer knowledge to
peripheral firms (0,155) more than peripheral do to core firms (0,083).
Interestingly, enough, firms in the core have higher absorptive capacity (Cohen and Levinthal, 1990) than
firms in the periphery (see Table 7). In another work (Bell and Giuliani, 2003), we have shown that micro-
level knowledge endowments shape the knowledge network at local level. Albeit the aim of this present
paper is fairly descriptive, it seems appropriate to put forward two main considerations: first that the
knowledge system described in this work differs from the ‘knowledge in the air’ story; second, that the
capacity of firms to benefit from local knowledge depends on their knowledge base both in absolute and
relative terms. Peripheral firms, characterised by weak knowledge bases, do in fact connect poorly with the
local knowledge system.
4.3. From Meso to Macro: Linkages with the National Innovation/Learning System
The openness of the cluster to external sources of knowledge represents the main driver for upgrading and
acquisition of new knowledge (Bell and Albu, 1999). The data collected in Colchagua Valley suggest that
firms in the cluster are fairly well interconnected with national research institutions or other organisations.
Picture 3 shows the linkages established by cluster firms (round nodes in the Picture) with national
institutions (square at the top) and business associations (triangle at the bottom). The majority of firms are
interconnected with both institutions and associations (central line), while smaller groups tend to have
linkages only either with the former (upper line of round nodes) or with the latter (lower line of round
nodes). Seven firms are cognitively isolated (left side).
This picture is quite informing, since linkages are typically considered one of the weaknesses of Latin
American Innovation/Learning Systems. In this case, instead, University-Industry and more broadly
Institution-Industry linkages seem to be an important part of the story.
Picture 3. External linkages with Research Institutions and main Business Associations in Chile Source: Own Data; UCINET 6.
20
In more detail, 78% of the firms have received technical support, training and other sorts of technical
knowledge inflows from different institutes and organisations in the past two years. Respondents were also
asked to give an evaluation of the importance of such inflows on a scale ranging from 0 to 3, where 0 stands
for no linkages and 3 for linkages that have improved considerably the technical knowledge base in the firm.
Aggregated results are presented in Table 8.
Table 8. Linkages with Research Institutions and other National Institutes Source: Author’s own (2002)
The first column of Table 8, shows the aggregated sum of values (ranging from 0 to 3) attributed by the
respondents to each of the abovementioned institutions. This is indicative of the quality of the service
proportioned by each institution or organisation. The second column, instead, represents the number of firms
that have turned to these institutions for technical assistance or support. What emerges is that both the
CEVIUC and the Centro de la Vid y Vino (University of Talca) are highly interconnected with the firms
sampled: more than 50% of the firms in fact have received technical assistance from them. Other
universities, such as the Universidad de Chile (Faculty of Agronomic Sciences) seem to play a more limited
role, whereas the INIA (the National Institute for Agronomic Research) is practically not connected with the
firms interviewed. Business associations also seem to play an important and active role in technology
transfer as, since they all present an aggregate value of about 10, which means that around 30% of the firms
interviewed do receive technical knowledge inflows from this type of source.
The third column represents the average value given by respondents for each institute/organisation. The
CEVIUC still remains, in terms of quality of the service offered, the most important centre for research and
technology transfer with an average score of 2.29. Values above 2 have been reached also by the Asociacion
Vinas de Chile and the Corporacion Chilena de Vino.
Similarly to this previous question, a second one was addressed to wine producers, which concerned their
participation to joint experimentation projects promoted by the institutions or organization abovementioned.
NATIONAL INSTITUTIONS and ORGANISATIONS Valued aggregate Dichotomic aggr.
(%)
Average value
(Valued
aggregate/n)
INIA (Istituto Nacional de Investigacion Agropecuaria) 4 2 (0,06%) 2
CEVIUC- UNIVERSIDAD CATOLICA 39 17 (53%) 2.29
CENTRO TECNOL. DE LA VID Y DEL VINO (UNIV. TALCA) 27 18 (59%) 1.5
UNIVERSIDAD CHILE (FAC. CC AGRONOMICAS) 16 9 (28%) 1.77
FUNDACION CHILE 10 6 (19%) 1.6
CHILEVID A.G. 17 8 (25%) 2.125
ASOCIACION VINAS DE CHILE A.G. 20 9 (28%) 2.2
CORPORACION CHILENA DE VINO 18 11 (34%) 1.63
INTECH CHILE 4 2 (0,06%) 2
ANALAV 10 6 (19%) 1.6
S.A.G. 19 12 (37,5%) 1.58
21
Here the answers show a more static situation, as firms tend to experiment less, jointly with institutions or
organisations. The highest value, though, is still reached by the CEVIUC that has established development
projects with around 19% of the firms interviewed. Moreover, the type of experimentation carried out was
considered by the respondents of quite high value (average 2,3) for their productive activity. Another
institution that seems to be involved in joint experimentation with firms is the University of Chile (Faculty of
Agronomic Sciences), which has carried out experimentation projects with 12,5% of the firms (4). In other
cases, the involvement is rather limited and marginal (see Table 9 for details).
Table 9. Joint Experimentation with Research Institutions and other National Institutes Source: Author’s own (2002)
During the ‘90s, Chile has developed a set of programmes to promote networking and innovation. The S&T
policy promoting institution, CORFO (Corporacion de Fomento), for example, has launched the ‘Proyectos
de Fomento’ (PROFOs), aimed at creating small networks of firms and fostering hence inter-firm
cooperation (Benavente, 1998; Vonortas, 2002; Crespi and Benavente, 2003). Furthermore, competing
funding schemes were increasingly made available during the ‘90s, to finance scientific and agricultural
research. Several funding institutions, in fact, are formally strengthening the country’s research and
development capacity and are interested in increasing quantity and quality of R&D and in facilitating the
transfer of knowledge and know-how to the productive sector through collaborative activities between R&D
performers and business firms (Vonortas, 2002).
This paragraph suggests that firms are not isolated agents in the process of technological upgrading. Instead,
their effort is also sustained through the interaction with the National System of Innovation /Learning.
NATIONAL INSTITUTIONS and ORGANISATIONS Valued
aggregate
Dichotomic aggr.
(%)
Average value
(Valued
aggregate/n)
INIA 3 1 3
CEVIUC- UNIVERSIDAD CATOLICA 14 6 (19%) 2.3
CENTRO TECNOL. DE LA VID Y DEL VINO (UNIV. TALCA) 4 2 2
UNIVERSIDAD CHILE (FAC. CC AGRONOMICAS) 8 4 (12.5%) 2
FUNDACION CHILE 2 1 2
CHILEVID A.G. 2 1 2
ASOCIACION VINAS DE CHILE A.G. 0 0 0
CORPORACION CHILENA DE VINO 1 1 1
INTEC CHILE 2 1 2
ANALAV 1 1 1
S.A.G. 0 0 0
22
4.4.Clusters within the cluster: learning behaviours and generation of knowledge The learning behaviour of firms is observable through the knowledge linkages that firms establish with both
intra- and extra-cluster sources of knowledge and also by the effort undertaken internally to generate
knowledge. Linkages in fact are an important part of the story but they might be exploited differently by
firms. On one hand, they might simply absorb knowledge and act upon imitation of the practices developed
by other inter-linked firms. On the other, firms might go beyond that and innovate upon the knowledge
acquired. Therefore it is intended here to identify patterns of learning and innovation on the basis of: the
degree of cognitive interconnectedness of firms in the cluster, the degree of external openness and the level
of experimentation carried out at firm level. Appropriate measures for each of the above-mentioned
dimension were defined (see also Par. 3.2.), namely: degree centrality, external openness and
experimentation and were applied to run a cluster analysis.
The results of the cluster analysis (see Table 8) show the formation of three separate groups of firms, which,
for their characteristics have been named laggards, imitators and innovators, respectively. Each group is
formed so that it minimises intra-group variability and maximises the differences across groups. It is
expected therefore that the learning behaviour of firms within their own group is similar. For each cluster
Table 10 presents the average value of in-degree and out-degree centrality, external openness and degree of
experimentation that are the variables applied to run the analysis9. The last two columns include other types
of information, namely: firms’ absorptive capacity, average level of firms’ performance, percentage of
locally based firms and percentage of foreign-owned firms.
Cluster Analysis*
Cluster 1: Laggards (N=12)
Cluster 2: Imitators (N=14)
Cluster 3: Innovators
(N=6) Out-degree C.(val) 0,8 8,14 8,00 In-degree C. (val) 1,6 7,93 7,00
External Openness 3,8 9,14 9,00 Experimentation 0,3 1,64 4,00
Absorptive Capacity -0,6 0,10 1,02 Performance -1 0,49 0,77
% Locally-based firms (1) 92% 85% 33% % Foreign-owned firms (2) 0,08% 28,6% 16%
* Groups formed by Multivariate Cluster Analysis Method: Between Group Linkages/Squared Euclidean Distance (SPSS) (1) Firms are considered locally-based if they perform all the activities of the productive chain within the cluster. (2) Firms are considered foreign owned when at least 50% of the property is foreign. Table 10: Learning behaviours and Innovation. The results of a cluster analysis. Source: Author’s own. The first group is composed by firms with a very weak learning behaviour. These firms tend not to
interconnect cognitively nor with other local firms neither with actors of the national innovation system. In
fact, the values of in-degree and out-degree centrality are rather low (0,8 and 1,6) and so is the level of 9 As said, the analysis was run using only one measure, degree-centrality, (Wassermann and Faust, 1994) instead of two separate indicators (i.e. in-degree and out-degree centrality).
23
external openness (3,8). This group of firms moreover do not perform any type of internal experimentation
(0,3). The average absorptive capacity is also quite low (-0,6). Finally, this group is formed mainly by
poorly performing locally-based and locally-owned firms. On the basis of its features, one is inclined to
define this group as laggard.
The second and third groups are quite different from the first one. In both cases, firms are highly
interconnected with the intra-cluster knowledge system and with the national system of innovation. In fact
these groups show very similar values of in-degree, out-degree centrality and external openness (see Table
10). The major difference among these groups is due to the internal degree of experimentation which is quite
low (1,64) in the second group and very high (4) in the third. Hence, while the second group is mainly
absorbing and imitating knowledge; the third one is more committed with innovating.
The second group, which is therefore mainly formed by imitators, show performances that are considerably
higher than the laggard group (0,49) but lower than the third group (0,77). Interestingly, the latter group
(innovators) is predominantly composed by large national-firms, which are leading the process of
technological renovation in the country by investing in applied research also jointly with national research
institutions.
Conclusions
The story of technological upgrading of Colchagua Valley is not entirely explained by the free access to
frontier machine-embodied technology. Instead, the heterogeneity of learning behaviours is symptom of the
fact that firms are not equally capable of successfully absorbing frontier knowledge. Also at meso and macro
levels, we observe patterns of learning which suggest that firms characterised by different knowledge
endowments learn differently and in some cases do not learn at all, as for the group of laggards described in
Par. 4.4.
The evidence moreover suggests that the process of accumulation of knowledge was not entirely sustained
by private firms. Most probably, there has been division of innovative labour and a co-evolution of industry
and institutions. It seems that, as remarked by Perez-Aleman (2000), the State has ventured beyond
macroeconomic management to both assist and encourage firms’ learning in a similar way to what Sabel
(1984) calls a developmental association.
To conclude, this paper has shed some light on the process of technological learning of a cluster. In doing so,
it included micro-meso-macro knowledge relations, whose dynamic relation is path-dependent and it’s likely
to explain the future development of a cluster.
24
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