Network learning and principal-agent conflict:
Wine-makers in Chile’s Colchagua Valley
David E. Hojman
The School of Management
University of Liverpool
Liverpool L69 7ZH
UK
Fax: 44 (0) 151 795 3001 / 3005 / 3720
E-mail: JL33@liv.ac.uk
Abstract
Chile’s Colchagua Valley is both a geographical cluster of wineries and a
dynamic learning network of wine-making professionals. A principal-agent
problem arises in that the latter knowledge network is frowned upon by
owners and top managers. Whereas highly skilled employees are after
maximising quality, firms are interested in profits. Individual, personal
success as a world-class expert is worth more to each professional, than to
the respective winery. This conflict is compounded by traditional,
authoritarian industrial relations. Regression results confirm that expert
network activity is a very poor predictor of award-winning international
performance, or profits.
Keywords:
Networks, Principal-agent, Wine, Chile
JEL:
D82, D85, L14, M54, O13, Q16
1
1 Introduction
Do Chilean wine-makers cooperate with each other? If they do, is this
reflected in their respective performances? This paper addresses the
apparent contradiction between Farinelli (2003), Visser (2004) and Visser and
De Langen (2005) on the one hand, and Giuliani (2003a, b) on the other
hand, regarding the alleged presence or absence of inter-firm cooperation
among Chilean wine-makers. These authors have all made substantial
contributions to recent scholarship on Chilean wine, but there seems to be a
fundamental disagreement between them. Farinelli (2003, p. 22) refers to ‘the
very pronounced fragmentation, isolation and individualism of the
entrepreneurs’, and argues that ‘the decade of “easy” exports did not
stimulate the mix of cooperation-competition which characterises most
dynamic clusters’. The PowerPoint presentation of her paper
(www.utoronto.ca/onris/ChilePresentation.ppt) mentions ‘scarce interaction
among wine producers (and) practically no inter-firm cooperation’. Visser
(2004) and Visser and De Langen (2005, p. 15) agree. The experts they
interviewed emphasised ‘the “extremely” individualist attitudes of Chilean
wine-makers, their “short-term mindedness”, and bias towards understanding
better … competition than … cooperation’. Absence of trust would be a key
problem (p. 16). 1
However, Giuliani (2003a, b, c) has found high levels of cooperation, in the
form of a healthy network of knowledge flows, among wine-making
professionals in Chile’s Colchagua Valley. Superficially, this seems to be
precisely the opposite from what was described in the previous paragraph.
Moreover, this discovery by Giuliani may not be a local characteristic unique
to the Colchagua geographical cluster, since the group of firms formed by
those she calls ‘innovators’ (which also have high absorptive capacities and
are open to intra- and extra-cluster knowledge exchanges) ‘… is
predominantly composed of 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’ (2003b, p. 23).
This paper argues that in fact there is no contradiction between Farinelli and
Visser and De Langen on the one hand, and Giuliani on the other. They are
really talking about different things. The former are talking about the attitudes
of the wine-making firms, companies, wineries, employers, top management,
CEOs, executives, or owners (in the rest of this paper, these terms are used
as equivalent), whereas the latter has been observing the attitudes of
employees (or some employees). 2
Thus, according to Giuliani, there is plenty of evidence of network activity in
Colchagua. Many Colchagua Valley wines have also been doing very well in
international competitions, such as the International Wine Challenge in
London. So, is the former causing, or at least making a contribution towards
the latter? This is one of the questions this paper addresses.
There are at least three types of inter-firm knowledge flows in the Colchagua
Valley. The first one is family-based: it takes place between members of the
2
same family. These are relatives, either close or distant, who own, or are part
of the top management of, different wineries (Duijker, 1999). The second type
of knowledge transfer takes place through consultants. The same consultant
works for two or more firms, sometimes simultaneously (Duijker, 1999; Tapia,
2001; Schachner, 2002). The consultant shares his or her knowledge (the
same knowledge) with two or more firms. In some cases, he or she also
increases his or her own knowledge, or acquires new local information, from a
particular winery, which is eventually passed on to another winery.
The third type of knowledge transfer is possibly the most interesting one.
Apart from it being identified by Giuliani, no study has concentrated on it
before. It is based on an informal network of professionals or skilled
employees. This is a knowledge network that is more active, or dynamic, than
what many of the respective companies would wish. Participation in the
network is more advantageous for the employee, than for the winery that
employs him or her. Network participation increases the professional’s
human capital stock, improves his or her technical performance, enhances his
or her standing (and social capital stock) with fellow network members, and
therefore ultimately adds to his or her prestige and lifetime income stream. In
contrast, the net impact of network activity on a particular winery’s profits may
be positive or negative. The firm wants its expert to receive information, not
to give it away. Not only that, but ideally the firm also prefers for the expert to
receive only that information which will make him or her more productive in his
or her current job, but not the sort of information that will make the expert
more attractive as a potential employee to competing firms.
Some evidence of both these network flows of knowledge, and the related
principal-agent conflict, are conveyed in the case study by Echecopar, Fetters
and McDermott (2004): ‘The upgrading of the Chilean wine industry benefited
greatly from competition, but not less importantly, by cooperation. Miguel
Torres [the Spanish oenologist and investor] was the first to share knowledge,
but he was not the only one … Chilean wine-makers not only changed jobs
often from one winery to another, thus diffusing knowledge in their new firms,
but they also did consulting for several other firms.’ And: ‘… [Douglas] Murray
… and [Aurelio] Montes’ knowledge and creativity gave rise to some winemaking experiments at San Pedro [one of the large traditional Chilean wine
producers] which were not looked on positively by an administration who saw
these experiments as distractions and preferred to focus on the bottom line.’ 3
The professional informal network identified by Giuliani is largely a personal
network, a network of individuals, not a network of companies.
The next section describes the main characteristics of the current wine boom
in Chile, and some of the specific features this boom has adopted in the
Colchagua Valley. Section 3 briefly summarises the relevant academic
discussion on geographical clusters and knowledge networks. The fact that
no satisfactory answer has been provided to explain the motivation behind
giving away knowledge to a competing winery in the Colchagua Valley is
addressed in Section 4. The principal-agent conflict at the root of this
particular case is discussed in Section 5. Another key aspect of the general
picture is the prestige, or celebrity status, which has recently been given to
3
successful wine-making experts. This is addressed in Section 6. Three
testable hypotheses are put forward in Section 7, and the respective variables
for empirical work are defined in Section 8. Section 9 presents and discusses
the results from multiple regression tests and Section 10 concludes.
2 The wine boom in Chile and Colchagua
By the beginning of the 1990s, Chile presented exceptionally favourable
conditions for a boom in the production and exports of quality wine. These
included practically perfect soil and climate conditions, economic and political
stability, a welcoming attitude towards foreign investment, institutional
transparency and lack of corruption, an export- and innovation-supportive
public sector, and a cheap and reasonably well-trained labour force. Vineyard
plantations increased from 50,000 hectares in 1994 to 109,000 in 2002. Wine
exports rose from 400,000 hectolitres in 1990 to 3.6 million in 2002.
Traditionally the largest export market had been Latin America. However, by
2002 about 80 percent of wine exports were going to Europe and North
America (SAG, 2003). In 2003, Chile represented 2.6 percent of world
production and 5.6 percent of world exports (Costa, 2004).
Wine has been made in the Colchagua Valley for several hundred years, and
good wine (by international competition standards) for at least a century.
However, Colchagua joined the current renaissance of Chilean wine relatively
recently, although it has been progressing at a very fast rate since then. 4
At least partly, the particular characteristics of the Colchagua network may
have to do with the local culture (Pilon and DeBresson, 2001; CORFO,
2004a). This culture is fully open to external influences, for example from the
parent company in the case of foreign direct investment or joint ventures.
There has been foreign direct investment in wine making in Colchagua by,
among others, Billington, Kendall Jackson, Mondavi, Marnier Lapostolle,
Guelbenzu, Lurton, Bodegas y Bebidas, and Rothschild (see Appendix 1).
The Colchagua Valley is also open to external influences, in that some local
wineries are subsidiaries of larger national companies, for example of older
and larger wineries from the Maipo Valley and elsewhere (Concha y Toro,
Santa Rita, San Pedro, Errazuriz). There are also some extremely talented
individuals, in both wine-making and other entrepreneurial activities (Aurelio
Montes, the Lurton brothers, or Carlos Cardoen, the industrialist and local
hotel and museum owner). Finally, there are local wine-making firms, mostly
long established, which are fully or largely based on Colchagua (Bisquertt,
Casa Silva, MontGras, Luis Felipe Edwards, Viu Manent). All of these
contribute to make the Colchagua Valley special and, according to some, also
to make its wines different from, say, wines from the Maipo Valley. Maybe the
local culture has always been different, but in any case it has certainly been
evolving in a particular, distinct way since the current renaissance of Chilean
wine started in the mid 1980s. In areas not directly related to vine planting
and wine production, there is more cooperation between firms in Colchagua,
than elsewhere in Chile. Good examples of this are the local initiatives on
4
wine tourism, and the private restoration and running of an old steam train,
activities which are much more interesting and innovative than in the rest of
the country (Guia de Vinos de Chile, 2005).
3 Geographical clusters and knowledge networks
There may be some disagreement or confusion in the literature as to what
exactly clusters and networks are, and what exactly they do. Martin and
Sunley (2003, Table 1, p. 12) have put together ten different definitions of a
‘cluster’, all of them published in the five-year period 1996-2001. A careful
distinction between ‘networks’ and ‘clusters’ has been offered by Maskell and
Lorenzen (2004, Table 1, p. 996). But several authors have expressed their
unwillingness to adopt these two concepts without proper, intellectually
coherent and generally accepted definitions. Concern has also been
expressed at the use of these concepts for largely unsupported policy
prescriptions (Breschi and Lissoni, 2001; Markusen, 2003). The otherwise
very comprehensive survey of Latin American clusters by Altenburg and
Meyer-Stamer (1999) does not even mention Chilean wine. Possibly this is
not because the authors are not aware of it, but because this particular case
does not conform to their own definition of what a cluster is. In this paper, we
will use the word ‘cluster’ to describe a physical concentration or
agglomeration of firms in a particular geographical area. These firms are
active in the same or related productive sectors, and they possibly trade with,
or are related to each other, vertically or horizontally. Some of the companies
in the cluster are small but there may also be large ones in it. As shown by
Ellison and Glaeser (1999), an important reason for the existence of many
geographical clusters is the possibility of taking advantage of local natural
resources and conditions. This is possibly one of the key factors behind the
wine-making cluster in the Colchagua Valley (Tapia, 2001; Schachner, 2002).
It has been convincingly shown by Giuliani (2003a, b, c) that the Colchagua
Valley is not only a geographical cluster, but also a knowledge network. New
knowledge, sometimes leading to productive innovations, may be locally
generated or imported from outside the cluster. In either case, this knowledge
flows between firms, or between professionals working for different firms, from
the ‘knowledge leader’, or ‘technological gatekeeper’ (whoever generated it,
or had the initial contact with a knowledge source outside the Valley), towards
others. 5
4 What motivates the knowledge giver?
A question that has not been answered adequately is, why should those
relatively more advanced firms in the Colchagua cluster be prepared to share
their superior knowledge with other, less sophisticated producers? What is
the motivation of the knowledge giver? Giuliani and Bell (2005, pp. 61-62)
argue that:
5
‘… willingness to engage in unreciprocated knowledge transfer to other local
firms may reflect … positive externalities … In a wine area, such as
Colchagua, which is currently investing in achieving international
acknowledgement for the production of high quality wines, the improvement of
every producer in the area is likely to generate positive marketing-related
externalities for the whole area, and these may outweigh the possible cost …’
However, there are some problems with this interpretation. Could such
positive externalities really be that substantial? Will firm A, the knowledge
leader, eventually benefit from increased recognition for the whole Colchagua
Valley, itself generated by the fact that firm B, the knowledge follower, is
becoming a better producer? Surely it makes more sense for A to try to
achieve international recognition for its own product, rather than devoting the
same amount of effort and resources to try to achieve recognition for the
entire Valley, and then wait for any positive externalities to come back to
benefit A?
Moreover, if B can eventually make a contribution to the Valley’s reputation,
possibly it would be because it has become so good that now it may represent
competition for A? Presumably, if B does not become really good (as good as
A, or almost, or even better), then it cannot make a contribution to the Valley’s
reputation? Or maybe B is shamefully bad, and the knowledge transferred
from A to B is limited, just enough to stop B from damaging the Valley’s
reputation? Is the information being transferred from A to B of only limited
value? It would be in the interest of A to help B to improve, but not very
much, just enough. Possibly B’s improvement could not be kept under control
by A, if the knowledge transferred is of great, or greater, value? But then,
surely it would not be long, either before B realises that it is not getting the
most valuable information, or before it uses what is getting fully and then it
requires better knowledge?
All of these outstanding questions suggest that relying only on positive
externalities as the explanation, not only requires strong assumptions, but it
also makes the resulting system highly unstable. In the words of Breschi and
Lissoni (2001, p. 980):
‘… it might be that what standard methodologies …, data sets … and
concepts … suggest to be pure externalities will turn out to be, on more
careful scrutiny, knowledge flows that are mediated by market mechanisms’.
A more convincing explanation than Giuliani and Bell’s (2005) is that at least
some of the knowledge transfer may take place, without the top management
or owners of the relevant firms being aware of it. At least some of those
engaged in the knowledge transfer (skilled and semi-skilled employees, junior
and middle management, professionals, agronomists, viticulturists,
oenologists, administrators, etc) may be doing it, because it is convenient for
themselves, and even if the respective company would disapprove, if it knew
about it. Some interesting evidence in this connection is offered by Giuliani
herself, in a previous paper (Giuliani, 2003a):
6
‘… much of the knowledge flowing between firms takes place via such
professionals, while owners and managers are quite reticent in releasing
information’ (p. 10).
Her interviews:
‘were directed to the oenologists or agronomists operating in the plant or
vineyard … [and] … employees working in more direct contact with the
productive activity: eg the farmer himself in the case of individual grape
growers or the cellar man’ (p. 14).
In the course of her fieldwork, she became aware that:
‘in some cases, local personnel are strictly asked by the parent firm not to
release any information’ (p. 23).
As mentioned before, also authors such as Farinelli (2003, p. 22), Visser
(2004) and Visser and De Langen (2005) have argued that Chilean wineries
are ‘individualistic’ and show a propensity to ‘free ride’. These views are
confirmed by Echecopar, Fetters and McDermott (2004) and Bjork (2005)
(see above). All of this evidence would be in direct contradiction with the
belief that positive externalities are all important, and that the local knowledge
leaders are aware of it and act accordingly. 6
5 The principal-agent question
So, there is here a principal-agent issue. 7 The Colchagua local knowledge
network seems to exist, despite the opposition of the firms’ (or some firms’)
top management and owners. The network is stronger and more active than
what these top management and owners would wish. For the skilled
employees or professionals in the Colchagua wineries, an active, dynamic
network is more important than for their companies. A particular firm may be
either better off or worse off as a result of network activity, depending on
whether it is a net giver (to potential competitors) or a net receiver of useful
network-transmitted knowledge. 8 But the skilled employee or professional is
always, or almost always, better off as a result of network activity, provided
that his or her winery does not catch him or her committing what many firms
would interpret as an act of disloyalty. As an information receiver, the
professional directly benefits. He or she learns something new, which is a net
addition to his or her human capital stock, and his or her performance at work
(or output) improves. As an information giver, the professional is doing
someone else a favour that will eventually be reciprocated.
A shared identity between the experts in different companies is also likely to
contribute to the network’s success. Knowledge flows will be more dynamic if
I see the person at the other end as equal to me, if he or she is ‘one of us’
(Akerlof and Kranton, 2005). Some authors have interpreted this role for
7
identity as another story of ‘social embeddedness’, or ‘strength of weak ties’
(Uzzi, 1997; Granovetter, 2005). As Giuliani (2003c, p. 22) puts it:
‘The oenologists and agronomists operating in the local area tend to interact
cognitively more when they have a common background and share the same
commitment to the improvement of the understanding of local viticulture and
oenology. They release critical information and cooperate in problem solving
because of commonality-diversity elements in their knowledge bases. Of
course, … such knowledge sharing is stimulated both by mutual trust and by
the expectancy that they will receive feedback sooner or later.’
But at least some of this knowledge transfer has to remain undisclosed, with
only the respective giver and receiver being aware of it. Many networks rely
on trust (Gossling, 2004). Trust is essential in the Colchagua Valley for two
reasons: because reciprocity is expected sometime in the future, and because
some knowledge transfers must be, if not secret, at least very discrete.
Giuliani starts one of her papers (2003c) with a quote from Krugman:
‘Knowledge flows are invisible; they leave no paper trail by which they may be
measured and tracked…’
This is very convenient when at least one of the partners in the transaction
does not want his or her employer to learn about it. To keep it secret is a
powerful reason for face to face contacts. Many networks require physical,
face to face contact (Urry, 2004). In the Colchagua Valley this may be
particularly important, since participants may often prefer their exchanges to
be verbal rather than written. 9 The need for discretion is reinforced as an
ongoing process of consolidation and concentration among wineries
advances (see Appendix 1 for some examples). The Colchagua Valley
network is informal, but this does not make it less effective. Principal-agent
conflict is not unheard of in informal knowledge networks (Von Hippel, 1987,
p. 302).
An additional incentive for professionals and skilled employees to participate
in this Colchagua Valley informal knowledge network is that there are already
many links between wineries because of family connections (Duijker, 1999).
There are also individual consultants who have advised different wineries over
the years, or are currently advising them, even two of them or more at the
same time (Duijker, 1999; Tapia, 2001; Schachner, 2002). Both of these facts
combine to make it possible for a general manager or owner, despite not
being an expert, to know more than the expert himself or herself, which would
leave the latter in a rather uncomfortable position.
A final reason for this informal, reciprocity-expecting, trust-based knowledge
network is that, increasingly, successful wine-making experts are being
treated as ‘celebrities’, ‘stars’, or ‘super-heroes’. This makes the individual
accumulation of capital stock, and the recognition and prestige attached to it,
all important.
8
6 The ‘celebrity’ wine-making expert as star
Increasingly, Chilean wine-making experts (arguably the best, but many of
them) are being seen and hailed as celebrities. In the spring of 2005, The
Times and The Sunday Times carried tabloid-size adverts for The Sunday
Times Wine Club, offering a mixed case of twelve bottles, in which the only
Chilean bottle was presented as:
‘Merlot from a winemaking “genius”: Vina Tarapaca Merlot 2004, Central
Valley … As the first UK merchant to buy from Chile, The Club enjoys special
access to wines from acclaimed makers such as Sergio Correa’.
This personality cult is becoming widespread. All the Chilean wines sold by
Marks and Spencer in the UK carry the individual wine-making expert’s name
in the label (both the individual oenologist’s name, and that of the company
which employs him or her, are given). 10 There is only one exception, a
Chilean firm which, instead of giving persons’ names, prefers to say that its
wine was made by a ‘team of Chilean and Australian makers’. According to
Eduardo Chadwick (2003), chairman of Vina Errazuriz, ‘there is a new
generation of talented young viticulturists and winemakers … who have
received international training and are passionate about quality’ (see
Appendix 1).
The Wine Spectator in April 2005 had an article on Chilean wine (Molesworth,
2005), in which oenologists of the wineries Concha y Toro, Los Vascos and
Antiyal (Enrique Tirado, Marco Puyo and Alvaro Espinoza, respectively) were
explicitly mentioned. The article also had a colour photograph of Casa
Lapostolle’s wine-making expert, Jacques Begarie. That issue of the Wine
Spectator also carried a full-page advert by Vina Santa Ema, with a large
photograph (and the name) of their own wine-making expert, Andres
Sanhueza. The name and a colour photograph of Vina Ventisquero’s winemaking expert (Felipe Tosso) may also be found in their full-page advert in
Decanter, June 2005. In the same publication, another winery is described as
going through ‘troubling times’, having lost their experts twice during 2003
(both are named). Luckily, either another expert (number three) was already
in place or was rapidly hired, and readers can see his photograph (Richards,
2005). Every year, the Guia de Vinos de Chile presents its ‘Best WineMaking Expert of the Year’ award (won by Marcelo Papa in 2005). The Guia
also chose the ‘Best Wine-Making Expert of the Decade’, for its tenth
anniversary in 2003 (Ignacio Recabarren). The names of many other
‘celebrity’ oenologists, with the respective firms they work for, may be found in
Tapia (2005). The winner of the trophy for the best wine in show in the
second year of the Wines of Chile Awards, Vina Falernia Alta Tierra Syrah
2002, Elqui Valley, was described as made by not one but three talented
wine-making experts: Aldo Olivier, Giorgio Flessati and Jean-Marc Sauboua
(Wine International, May 2005, p. 20).
Why are so many Chilean wine-making experts being hailed as celebrities, or
stars? The first reason is that everyone, and wineries in particular, are
9
becoming aware of how important specialist knowledge can be. This is not
only general knowledge, but also knowledge about local, micro conditions.
Such knowledge is not easy to come by, and the best of it may always be in
short supply. The best skills and experience are scarce. A second reason is
that this is a marketing exercise by the wineries. By saying explicitly, ‘this
wine was made by Mr. X (or Ms. Y)’, they are implicitly suggesting that ‘this
wine is so good, so special, that we must tell you who made it’. But there is
even a third reason, namely, that the practice is also supported by the experts
themselves. Such an explicit acknowledgment of a person’s skills is, in terms
of prestige, an important aspect of their remuneration packages. However,
not all wineries are equally happy to embrace this practice. As mentioned
before, one of the suppliers of Chilean wines to Marks and Spencer will not go
along with it. Maybe this particular employer feels that such explicit
acknowledgment will represent an excessive increase in the expert’s
remuneration package, and/or it will make him or her a desirable target for
headhunting by other wineries.
Another interesting characteristic of this particular labour market is that winemaking experts tend to move around substantially from one employer to the
next (see Appendix 1). Many experts do not seem to last a long time in their
jobs. This could be at least partly a result of booming demand for their
services. Before 1980, there were less than 200 oenologists who had
graduated from Chilean universities in the country (Farinelli, 2003, p. 10).
Another 50 graduated during the 1980s. By the end of that decade, the
Chilean wine boom had already started, and over 300 students graduated
during the 1990s. By 2004, the Chilean Association of Oenologists had 620
members (Miranda, 2004). So, this high rate of migration from winery to
winery may be caused by a temporary imbalance between supply and
demand, which will be corrected eventually. But there is an alternative
explanation. Migration may be caused by firms’ (or some firms’) unwillingness
to accept active participation by their experts in knowledge networks such as
the Colchagua one, which management consider disloyal. This problem may
be compounded by the traditional nature of industrial relations and human
resource management in Chile, which is paternalistic and authoritarian
(Hojman and Perez, 2005). As part of their professional development, winemaking experts must work with different soils, local microclimates and grape
varieties. But in an ideal world they should be able to do this without having
to change jobs.
The characteristics of the current network are not necessarily stable. The
long-term process of convergence towards equilibrium is affected by several
trends (Callander and Plott, 2005). Some of the large wineries (this is not
possible for a small winery on its own) may opt for engaging in the
modernisation of their industrial relations and human resource management,
and for providing an internal environment where scope economies associated
to diversity (of everything, from natural conditions to technological packages
to experts’ personalities) can be fully exploited. This is equivalent to trying to
internalise the positive externalities generated by their experts’ network
participation. Other large wineries may opt for publicly de-emphasising the
role played by their experts, which is compatible with attempting to preserve
10
traditional, paternalistic or authoritarian management practices. Smaller
wineries may try different forms of association. The best experts may try to
become independent, their own bosses, by starting their own businesses.
They may also go for non-conventional forms of partnership with the most
dynamic among the large firms. Many examples are presented in Appendix 1
(see also CORFO, 2004b, c).
7 The model and hypotheses
A formal theoretical model of the Colchagua Valley network, which explicitly
includes the determinants of the professional’s satisfaction, the level of
network activity, the winery’s profits, and the resulting principal-agent conflict,
is presented in Appendix 2. Building on the discussion of previous sections, it
is possible to suggest three hypotheses which may be tested empirically.
Hypothesis 1: Network activity and average quality in the domestic market
are positively related.
However, network activity may not be the only (or even the most important)
determinant of quality, because the impact of network activity on quality is
weakened by the attempts by the winery to maximise profits.
Following from Hypothesis 1, network activity and overall presence in the
domestic market (defined as the product of multiplying average quality times
the number of different wines offered, or ‘product range’) may also be
positively related.
However, network activity may not be the only (or even the most important)
determinant of domestic presence, not only because of the winery’s profitmaximising drive, but also because network activity may also affect the
product range in different, specific ways. The present discussion
concentrates on overall domestic presence, rather than product range,
because the former rather the latter is possibly more likely to affect
international presence and international success (via factors such as financial
strength and scope economies).
Hypothesis 2: The impact of network activity on international success is
small.
In particular, network activity may not be as important as overall domestic
presence, or other factors. More generally, there may be an inverse
relationship between the impact of network activity on a particular variable,
and the effect of that particular variable on international success, or profits.
Hypothesis 3: The impact of network activity on profits is small.
The rest of this paper is devoted to the empirical testing of these hypotheses
and to discussing the results.
11
8 Variables and data
Three indicators of network activity in the Colchagua Valley, by individual
winery, are available (Giuliani, 2003a). They are actor degree centrality
(DECE), actor closeness centrality (CLOS) and actor betweenness centrality
(BETW). Complete definitions are given and discussed in Wasserman and
Faust (1994, Chapter 5). Briefly, DECE is defined as an actor’s number of
direct, one-to-one, no-intermediary links with other actors or network
members (as a ratio of the maximum possible). CLOS is about both direct
and indirect links. It measures the number of intermediaries an actor has to
go through, on average, in order to reach all the other network members. The
lower that average, the greater the actor’s closeness to the rest of the network
will be. Finally, BETW measures the number of times actor B is an inevitable
intermediary between two other actors (say A and C) who are not themselves
in direct contact, when A and C want to get in touch with each other using the
shortest possible way (ie., via the smallest number of intermediaries). The
actual value of indicator BETW for actor B is given by the average number of
times B is the inevitable intermediary, when all possible couples of actors
(including A and C, but not only them), different from B, are trying to get in
touch with each other. A higher value of BETW means that actor B is more ‘in
the middle’, or is more of a ‘gatekeeper’, or has more ‘interpersonal influence’
(see Wasserman and Faust, 1994, pp. 171, 179, 186 and 191 for examples).
Colchagua wineries also have individual values for absorptive capacity
(ABCA) and extra-cluster openness (EXCL). These indices have been
defined and their values computed by Giuliani (2003a, pp. 22, 28). The
variable ABCA includes the educational levels of skilled workers, separating
national from foreign sources and first degrees from masters and doctorates;
national and international work experience; previous jobs, separating national
from international employers; and four levels of research experiments.
Variable EXCL is a scale measuring technical support and training received
from, and joint experiments with, national and international knowledge
sources external to the Colchagua Valley, in the previous two years.
Each winery’s average quality in the domestic market (GUIQ) has been
calculated using the highly respected Guia de Vinos de Chile (2005). The
Guia includes all the wines in the domestic market (over 900), with their
respective individual blind-assessed quality ratings. Colchagua is
overwhelmingly a red-wine producing area. So, only red wines were
considered in our tests. Also, wines were included only when the region of
origin was given as ‘Colchagua’, or ‘Colchagua Valley’, or sub-areas of it,
such as ‘Santa Cruz’. Some wineries have production facilities in Colchagua
but they choose not, or are not legally allowed, to give ‘Colchagua’ as their
region of origin (instead, they use ‘Central Valley’ or ‘Rapel Valley’). Such
wines were also excluded from the relevant statistical tests. The Guia’s
quality ratings rank from 1 (the lowest) to 4-plus. Some wines in ranks 2, 3
and 4 may also be ‘highlighted’, or designated as 2-plus, 3-plus and 4-plus
12
(meaning ‘distinguished in its own class’). This gives a scale with seven
levels, from 1 to 4-plus. For purposes of our statistical work, this scale was
converted to one going from 1 to 7. In other words, the old scale ‘1, 2, 2-plus,
3, 3-plus, 4, 4-plus’ becomes ‘1, 2, 3, 4, 5, 6, 7’.
A winery’s overall presence in the domestic market (GUIX) was defined as the
product of multiplying the winery’s average quality GUIQ by the number of its
wines, or product range, GUINU. For example, assume that winery W has
two red wines from Colchagua listed in the Guia (GUINU=2), with quality
rankings of 3 and 4-plus. In our new 1-to-7 quality scale, these are equal to 4
and 7, respectively, giving a total of 11 (GUIX=11). Variable GUIQ is equal to
5.5 (GUIQ = GUIX / GUINU = 11 / 2). This is a real life example and its
importance will become apparent in the next paragraph.
The last variable to be defined is a winery’s performance in London’s 2004
International Wine Challenge (IWC; see Wine International, 2004). London’s
ratings for wines which win awards are, in increasing order of quality, Seal of
Approval, Bronze, Silver and Gold. For purposes of our statistical tests, they
were converted to the numerical scale 1, 2, 3 and 4. For example, winery W
got two Seals of Approval and one Bronze. These translate to 1, 1, and 2,
respectively, in our numerical scale. We add them up, to get the value of our
variable IWC for winery W, which is 4 (1 + 1 + 2 = 4). 11 Incidentally, note that
winery W, which had only two wines in the domestic market, won three
awards in London (and it may have submitted more than three wines).
Winery W kept at least one of its wines, and maybe more, exclusively for the
international market. Conversely, some wineries with domestic sales (and
therefore mentioned in the Guia) chose not to take part in London, or took part
but won no awards (and therefore were not mentioned in Wine International,
2004).
Rankings of the top Colchagua wineries in 2004-2005, according to the three
indicators GUIQ, GUIX and IWC, are presented in Table 1. Descriptive
statistics for all the variables in the model are given in Table 2.
9 Empirical estimation and results
The proposition that a winery’s network activity (or more accurately, network
activity by a winery’s expert or experts) in the Colchagua Valley may affect the
average quality of the respective wines in the domestic market is tested in
Table 3. These multiple regressions also look at the possible role of
absorptive capacity and extra-cluster openness. According to the Table 3
results, of all three indicators of network activity, both DECE and BETW could
be making a contribution towards determining GUIQ. However, the respective
t statistics are relatively small (about 1.4-1.6), by the usual significance levels.
Although the sign is always positive as expected, the t statistics do not
confirm unequivocally that a relationship between either DECE or BETW on
the one hand, and GUIQ on the other, is present (but they suggest it). In
contrast, the Table 3 regressions confirm that EXCL and GUIQ are positively
13
linked. Extra-cluster openness is offering a better explanation than network
activity. Thus, Table 3 offers only weak support for Hypothesis 1. However, it
would be impossible to claim from Table 3 that network activity damages
GUIQ. It is certainly possible to conclude that, if there is a relationship at all
between network activity and GUIQ, it is most likely that it will be positive. 12
The possible impact of network activity on a winery’s overall domestic
presence, GUIX, is examined in Table 4. The quality of these fits is not as
high as in Table 3. Less than a third of the variance in the dependent variable
is explained by this model (as opposed to almost two thirds in Table 3). Still,
Table 4 offers strong evidence of a statistically-significant, positive-sign link
between CLOS and GUIX. However, since GUIX is defined as the product of
multiplying GUIQ by GUINU (the number of wines in the domestic market, or
product range), and since CLOS played no role in explaining GUIQ (see Table
3), it follows that CLOS explains GUIX, only because it is positively related to
GUINU. So, network activity does indeed affect domestic presence, although
this takes place via product range. Incidentally, product range is very low as a
competitive priority for Chilean wineries. Winery executives interviewed by
Foster et al (2002, pp. 36-38) ranked product range as their competitive
priority number 10, out of a list of ten possibilities. Network activity in
Colchagua helps with product range, but, in the views of winery executives,
product range as a priority comes last, after everything else. It is obvious that
the sample interviewed by Foster et al (2002) was very different from that
interviewed by Giuliani (2003a, b, c). 13
The possibility of a relationship between network activity and international
success (IWC) is examined in Tables 5 and 6. Table 5 presents regressions
exploring the impact of network activity, absorptive capacity, extra-cluster
openness, and GUIX, on IWC. Since GUIX itself may be endogenous, and a
function of network activity, some of these regressions were estimated using
instrumental variables (TSLS). According to the Table 5 results, the most
important determinant of IWC is GUIX. There may or may not be an ABCA
effect (in most cases the t statistic is about 1.6). If there is a BETW impact at
all (the respective t statistic is often, but not always, as low as -1.9), this
impact would be negative. So, either there is no impact of network activity on
IWC, or this impact is negative. But this is only after having controlled for a
separate impact of GUIX (and through GUIX, CLOS) on IWC.
The Table 6 specifications are similar to those in Table 5, except that in Table
6 GUIX is not introduced as a separate regressor. This is because, if GUIX
depends indeed on network activity, then the estimated coefficients for the
network activity variables in Table 6 will reflect both the direct impact, and the
indirect impact via GUIX. Since GUIX is not an explicit part of the Table 6
model, the sample can now be enlarged by adding wineries with no domestic
presence. This increases the sample size from 17 to 23. The indicator CLOS
is statistically significant. However, the adjusted coefficient of determination is
very small. This model explains less than 5 percent of the variance in the
dependent variable. Moreover, there is a very large risk of omitted variable
bias, which takes credibility away from the estimated coefficient for CLOS.
Both Tables 5 and 6 confirm that Hypothesis 2 should be accepted. Since it is
14
most likely that GUIX makes only a small contribution to explaining profits,
and given that Hypothesis 2 has been accepted, Hypothesis 3 is also
accepted.
A slightly different interpretation of these multiple regression results is also
possible. Given that the best fit in Table 4 (Regression 4.4) explains only 30
percent of the variance in GUIX, it could be argued that GUIX is largely
independent from network activity. Therefore, GUIX could be introduced as
an independent regressor in the Table 5 model. This means that the best fit
in Table 5 is Regression 5.2, obtained using ordinary least squares (OLSQ).
This would give us a fit explaining about 60 percent of the variance in IWC.
The most important determinant of IWC would be GUIX. Possibly ABCA
would also play a role (the respective t statistic is 1.6). But two of the network
activity variables, CLOS and BETW, seem to be affecting IWC negatively.
How, or why could this happen? There are several possibilities. Maybe
quality notions at home and abroad are very different. Or maybe network
activity is generating ‘lock-in’, or ‘small world’ negative effects (see
Granovetter, 2005, for some examples). Or maybe ‘excessive’ network
activity is encouraging uniformity across firms, and therefore mediocrity,
rather than distinctiveness. Or maybe not all the knowledge flowing in the
network is of top quality or conducive to top quality performance. And so on.
In any case, this alternative interpretation would also confirm Hypotheses 2
and 3.
Summarising, the empirical results suggest that:
First, the quality of Colchagua wines in the domestic market seems to be
largely explained by a winery’s extra-cluster openness. Possibly, network
activity may help, but this could not be confirmed by our tests. Second,
network activity contributes to a winery’s domestic presence, but it is not the
only factor and it may not be the most important one. Moreover, this effect
takes place via product range, a variable the wineries are not particularly
interested in. And third, network activity seems to make no contribution to a
winery’s international success (at least when the latter is defined as
performance in London’s International Wine Challenge). In fact, its impact
may actually be negative.
10 Conclusions
There cannot be any doubt that there is an informal knowledge network of
wine-making professionals in the Colchagua Valley. This network is active
and dynamic. However, it makes sense to ask what is it there for. The
empirical results suggest that network activity in Colchagua: a) may not be a
crucial factor for domestic quality; b) it helps with a winery’s domestic
presence, but for the wrong reasons; and c) its effect in terms of international
award-winning performance is negligible, or even counterproductive.
15
So, given these rather modest roles both at home and abroad, why is there a
Colchagua network at all? It is not surprising that many wineries are not
enthusiastic about it (and some are extremely unhappy). The most likely
explanation confirms the central idea of this paper. The Colchagua network is
a network of professionals, but not of their employers. Individual participation
by a particular employee may be against the wishes, implicit or explicit, of the
respective company. A principal-agent conflict has emerged from the fact that
what is the best for one of them is not the best for the other.
It may be very frustrating for wine-making experts that the network does not
make a stronger contribution to quality. This failure is highlighting a large gap
in time horizons, a clash between the expert’s lifetime development and
career ambitions, and the winery’s short-term profit maximising aims. In a
more positive vein, the Colchagua network is suggesting the presence of a
new type of scope economies. A winery may be large enough to be able to
offer each expert the possibility of working with, and learning from, different
geographical regions, soil conditions, microclimates, and grape varieties, and
interaction with other experts, without having to change jobs or give away
valuable company information. This winery may be prepared to acknowledge
publicly the important contribution that each one of its experts is individually
making. In that case, such a winery would benefit from internalising most of
the positive externalities generated by the network. Unfortunately, this option
is open to large wineries only. Small and medium-sized companies cannot
take advantage of it.
Notes
1
In a similar vein, Bjork (2005) argues that wine production in Chile, and
foreign direct investment in Chilean wine-making, have generated few
spillovers.
2
In addition to the authors mentioned before, see also Del Pozo (1995) and
Vergara (2001) for the historical context.
3
Conflict between quality maximising and profit maximising in wine making is
not unique to Chile. See Morton and Podolny (2002) for related evidence in
the Californian wine industry.
4
For example, the results of a blind tasting of 106 Chilean Cabernet
Sauvignons, organised by the magazine Decanter and published in their June
2005 issue, show how fast Colchagua wine-makers have progressed (or are
progressing). The only winner of a Decanter Award (5 stars) was from
Colchagua (Montes Alpha Apalta Vineyard 2002). Also one of the two 4-star
wines came from Colchagua (Vina Sutil Reserva Pablo Neruda 2002),
together with 10 out of 41 wines receiving the more modest 3-star accolade.
5
Another crucial aspect of the theoretical discussion is that networks do not
remain unchanged, but, on the contrary, they tend to develop, evolve or
16
converge towards particular or specific forms of equilibrium (Callander and
Plott, 2005). This is also true in the Colchagua Valley (or in Chilean winemaking more generally). A key related, or complementary, perspective is the
notion that economic transactions take place in, and therefore economic
outcomes are affected by, social structures (Granovetter, 2005).
The original Question 4 of Giuliani’s field research work (Giuliani, 2003b, p.
15) was: ‘Could you mark … those with whom you have collaborated …?’.
However, in the Giuliani and Bell (2005, p. 54) article, based on the same field
research work, this wording has been changed to: ‘Could you mark … those
with whom this firm has collaborated …?’. This change would be harmless if
‘you’ (the expert being interviewed) and ‘this firm’ were exactly the same
thing. But they are not. Giuliani and Bell (2005), by ignoring the fact that the
Colchagua network is one of professionals, different from a hypothetical
network of firms, represents a step backward in relation to Giuliani (2003b).
Giuliani and Bell (2005, p. 51) explicitly acknowledge their assuming perfect
identification between each interviewee and his or her firm: ‘… (L)ocal
knowledge flows within “cognitive subgroups” of professionals (and, therefore,
firms) …’ Such identification is misleading, as Giuliani (2003a, b, c) herself
had previously shown.
6
7
A typical principal-agent problem refers to the contractual arrangement
between a firm (the principal) and its employee (the agent) in the presence of
asymmetric information. Profits depend on the employee’s effort, but this
effort cannot be monitored by the firm. In the absence of adequate incentives,
effort will not be maximised (or will be suboptimal) and profits will suffer. A
typical ‘optimal solution’ would link the wage to profits. The employee would
be paid more when profits are high, and less when profits are low (Akerlof and
Kranton, 2005, pp. 13-14). For wine-making in Colchagua, instead of ‘low
effort against high effort’, the employee’s choice would be ‘to pass on or not to
pass on knowledge to another firm’s employee’. However, the Colchagua
story is more complicated for two reasons. First, the typical Colchagua winery
does not know the exact nature of the relationship between network
participation by its employee, and the firm’s profits. And second, the
motivation of the wine-making expert may be more complex than just a simple
textbook choice between income and leisure. A formal model is presented in
Appendix 2.
8
Even if the aggregate impact of the network on the whole of the Colchagua
Valley is positive, the individual winery typically does not know whether the
specific impact of the network on itself will be positive or negative. There is
also uncertainty for the typical firm in that, even if the short-term specific
impact of the network on the firm may be positive, the long-term effect may
not.
9
This need for face to face contact in the Colchagua Valley, in order to keep
(at least part of) the knowledge flow invisible to (at least) one of the two
owners or top managers, has nothing to do with the knowledge being ‘tacit’.
For a discussion of the role of knowledge ‘tacitness’ in the study of clusters,
see Lissoni (2001).
17
10
It is possible that Marks and Spencer may insist on getting and publishing
the individual expert’s name, as a form of insurance, or pressure, against
excessive personnel changes in its Chilean suppliers, and with them, wild
quality swings.
Our IWC indicator is one of ‘overall presence’, rather than ‘average quality’.
However, it differs from GUIX, not only in that it is international as opposed to
domestic, but also in that any wines which did not win awards were not
included in the IWC ranking. In terms of IWC ranking, not participating, and
participating without winning an award, are equally bad.
11
12
The fact that the link between network activity and wine quality is not
stronger is possibly a source of disappointment to many experts (and it could
be another reason for the high rate of expert migration from winery to winery).
13
According to Table 4, the variable EXCL seems to have a negative-sign
impact on GUIX (which is not significant at the usual levels in all the
regressions).
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21
Table 1
Rankings of top Colchagua Valley wine-makers (red wines only)
Guia de Vinos de Chile
2005: average quality
(GUIQ)
Guia de Vinos de Chile
2005: overall domestic
presence (GUIX)
International Wine
Challenge 2004 (IWC)
Lapostolle
Casa Silva
Casa Silva
Los Vascos
Montes
JOINT:
LF Edwards
MontGras
Viu Manent
Emiliana
JOINT:
Bisquertt
Cono Sur
Santa Helena
Montes
MontGras
Caliterra
Caliterra
Viu Manent
Santa Ines de Martino
Casa Silva
Siegel Crucero
JOINT:
Apaltagua
Bisquertt
Cono Sur
JOINT:
Caliterra
Los Vascos
Apaltagua
Ventisquero
Santa Helena
Lapostolle
etc
etc
etc
22
Table 2
Descriptive statistics
2A Means and standard deviations of variables
Variable
Mean
Standard deviation
ABCA
DECE
CLOS
BETW
EXCL
GUIQ
GUINU
GUIX
IWC
0.379
5.412
6.897
4.041
1.592
3.048
4.353
13.29
6.176
1.029
4.459
2.183
3.912
0.843
1.149
2.978
9.584
10.06
2B Correlation matrix
ABCA
DECE
CLOS
BETW
EXCL
IWC
GUIX
GUINU
GUIQ
ABCA
DECE
CLOS
BETW
EXCL
IWC
GUIX
GUINU
0.307
0.497
0.363
0.512
0.280
0.228
0.080
0.570
0.756
0.761
0.460
0.043
0.382
0.266
0.637
0.669
0.390
0.253
0.593
0.528
0.555
0.465
0.075
0.426
0.309
0.665
0.011
0.060
-0.194
0.761
0.742
0.653
0.152
0.896
0.366
0.008
The sample size is 17
23
Table 3
Average quality in the domestic market
(dependent variable: GUIQ)
Regressor
3.1
3.2
3.3
Constant
1.564
(2.690)
1.412
(4.922)
1.280
(5.783)
ABCA
0.229
(1.084)
0.209
(1.225)
DECE
0.055
(1.427)
0.046
(1.650)
0.044
(1.407)
CLOS
-0.029
(-0.295)
BETW
0.073
(1.531)
0.071
(1.492)
0.081
(1.608)
EXCL
0.632
(2.688)
0.641
(2.801)
0.754
(4.034)
Estimation
method
OLSQ
OLSQ
OLSQ
Adj R2
0.622
0.652
0.648
n
17
17
17
The t statistics are in parentheses. The standard errors and variance are
heteroskedastic-consistent estimates
24
Table 4
Overall domestic presence, defined as average quality times the number
of wines (dependent variable: GUIX)
Regressor
4.1
4.2
4.3
4.4
Constant
-3.852
(-0.921)
-3.265
(-0.993)
-1.737
(-0.976)
-3.390
(-1.852)
ABCA
-0.309
(-0.129)
DECE
-0.471
(-0.842)
-0.445
(-0.716)
CLOS
3.073
(3.385)
2.991
(2.616)
2.598
(3.558)
2.949
(6.642)
BETW
0.563
(1.283)
0.558
(1.318)
0.341
(0.682)
EXCL
-2.298
(-1.340)
-2.460
(-1.908)
-2.677
(-2.240)
-2.296
(-1.552)
Estimation
method
OLSQ
OLSQ
OLSQ
OLSQ
Adj R2
0.141
0.212
0.257
0.299
n
17
17
17
17
25
Table 5
Performance in the International Wine Challenge: an explicit role for
GUIX (dependent variable: IWC)
Regr.
5.1
5.2
5.3
5.4
5.5
5.6
Constant
2.851
(0.674)
3.821
(1.100)
2.972
(0.658)
3.954
(1.068)
3.285
(0.792)
0.250
(0.104)
ABCA
2.698
(1.634)
2.926
(1.624)
2.707
(1.614)
2.948
(1.606)
2.837
(1.607)
2.402
(1.149)
DECE
-0.064
(-0.120)
CLOS
-1.338
(-1.386)
-1.390
(-1.682)
-1.435
(-1.266)
-1.459
(-1.638)
-1.115
(-0.700)
BETW
-0.625
(-1.193)
-0.612
(-1.893)
-0.643
(-1.172)
-0.615
(-1.928)
-0.597
(-1.885)
-0.630
(-1.393)
EXCL
0.613
(0.337)
GUIX
1.010
(3.997)
1.001
(3.911)
1.042
(4.888)
1.027
(4.754)
0.896
(1.566)
0.569
(2.162)
Estim.
method
OLSQ
OLSQ
TSLS
TSLS
TSLS
TSLS
Adj R2
0.518
0.596
0.518
0.596
0.595
0.562
n
17
17
17
17
17
17
-0.049
(-0.087)
0.686
(0.374)
All the exogenous variables were used as instruments in Regressions 5.4 and
5.5, but they differ in that one of them uses also GUINU and the other does
not
26
Table 6
Performance in the International Wine Challenge, excluding GUIX from
the estimating equation (dependent variable: IWC)
Regressor
6.1
6.2
6.3
6.4
6.5
Constant
0.135
(0.032)
0.278
(0.067)
2.405
(0.435)
-1.927
(-1.518)
-2.442
(-1.851)
ABCA
2.602
(0.877)
2.506
(0.873)
2.582
(0.898)
DECE
-0.333
(-0.583)
-0.466
(-0.780)
CLOS
1.556
(1.943)
1.537
(1.994)
0.900
(1.454)
1.430
(3.554)
1.162
(3.607)
BETW
-0.230
(-0.534)
EXCL
-2.148
(-1.101)
-2.239
(-1.179)
-2.444
(-1.322)
-1.498
(-1.174)
Estimation
Method
OLSQ
OLSQ
OLSQ
OLSQ
OLSQ
Adj R2
-0.069
-0.014
0.014
0.013
0.046
n
23
23
23
23
23
27
Appendix 1: Some wineries, owners and experts
Winery
Domestic
owner / coowner
Agustinos
Corpora
Almaviva
Concha y
Toro
San Pedro
Altair
Foreign
owner / coowner
Mouton
Rothschild
Chateau
Dassault
Anakena
Antiyal
Apaltagua *
B Prats, P
Pontallier
Aresti
Baron
Philippe de
Rothschild
Billington *
Mario Geisse
Juan Fernando Waldele,
Philippe Debrus (f Valdivieso),
Jochen Dohle
Calina *
Errazuriz
Lisa
Denham
Kendall
Jackson
(f Mondavi)
Canepa *
Carta Vieja
Casablanca
Lapostolle *
Casa Silva *
Casas del
Bosque
Casas del
f? Felipe de Solminihac
Billington
USA
Calama
Carmen
Ana Maria Cumsille
Carmen Merino
Michel Friou
(f Lapostolle)
Bisquertt *
Botalcura
Caliterra *
Juan Ignacio Ramsay, Jose
Henriquez?
Tod Mostero
Gonzalo Perez, Pascal Marti (f
Almaviva), f? Bernard Portet
Alvaro Espinoza
Alvaro Espinoza
Donoso
family
Aquitania
Oenologist, viticulturist,
consultant
Santa Rita
Santa
Carolina
Marnier
Lapostolle
Chateau
28
f? James Randy Ullom
Rodrigo Banto, f? Ignacio
Recabarren
Paula Cifuentes, Ernesto
Juisan
Pilar Gonzalez, Matias
Lecaros, f? Alvaro Espinoza, f?
Jacques Boissenot
Pascal Marti (f Almaviva)
Max Ibanez, f Ignacio
Recabarren
Jacques Begarie, Michel
Rolland
Mario Geisse
David Morrison, Camilo Viani
Toqui
Larose
Trintaudon
Clos
Quebrada de
Macul
Concha y
Toro
Conde de
Aconcagua
Cono Sur *
Cousino
Macul
Domaine
Conte
Domaine
Oriental
D Francisco
El Principal
Errazuriz
Patrick Valette, Ignacio
Recabarren
Tamara de Baeremaecker,
Marcelo Papa, Marcio
Ramirez, Ignacio Recabarren,
Enrique Tirado, Goetz von
Gersdorf, Max Weinlaub
Estampa
Gonzalez
Byass
Concha y
Toro
Santa
Carolina
Adolfo Hurtado, Cecilia Padilla,
Martin Prieur, Constanza
Vicent
Jose Miguel Ovalle, Jaime
Rios, Matias Rivera
Beringer
Blass
M Paoletti,
R+L Wan
Julio Valdivia
Patrick Valette
Sven Bruchfeld, f? Edward
Flaherty, f? Pedro Izquierdo
Estampa *
Falernia
F de Aguirre
Gillmore
Gracia
Guelbenzu *
Araucano *
Haras de
Pirque
Huelquen
La Fortuna
La Rosa
Leyda *
Los Vascos *
Concha y
Toro
Corpora
Santa Rita
Boisset
Guelbenzu
Spain
Lurton
Antinori
(f Rothschild
Laffite)
Lourdes
LF Edwards
Matetic
Miguel Torres
f Alvaro Espinoza
Torres Spain
29
Aldo Olivier, Giorgio Flessati,
Jean-Marc Sauboua
Lorena Veliz, f Carlos Andrade,
f? Aurelio Montes
Andres Sanchez (f Calina)
Jose Henriquez?
Cecilia Guzman, Alvaro
Espinoza
Gregorio Ferrada
Sergio Traverso
Jose Ignacio Cancino
Rafael Urrejola
Marco Puyo
Jorge Martinez
‘Australian experts’, Nicolas
Bizarri, f? JA Usabiaga, f? M
Farmilo
Rodrigo Soto
Fernando Almeda
Montes
MontGras *
Hartwig
family
Morande
Odfjell
Norwegian
investor
Penalolen
Perez Cruz
Perez Leon *
Porta
Corpora
Portal del Alto
*
Quintay
Ramirana
Ventisquero
Reserva de
Caliboro
Ignacio Recabarren
German Lyon
Boisset
Francesco
Marone
Cinzano
Irene Paiva, f Aurelio Montes,
f? Jacques Lurton
Pedro Izquierdo, Consuelo
Marin, f? Pilar Gonzalez
S Carolina *
S Eliana
S Laura *
Vinedos de
Jalon
Andres Sanhueza
San Pedro
Adriana Cerda, Francois
Massoc, Felipe Muller, Marcelo
Retamal, f? Aurelio Montes
Ernesto Jiusan, f? J+F Lurton
Hartwig
family
S Monica
S Rita
Selentia *
San Pedro
Sena y
Arboleda *
Siegel *
Sutil *
Tamaya
Errazuriz
Bodegas y
Bebidas
(f Mondavi)
Paz Lastra
Carlos Gatica, Andres Ilabaca,
Cecilia Pino, Cecilia Torres,
Alejandro Wedeles, f Ignacio
Recabarren
Christophe Paubert, Francisco
Ligero
Edward Flaherty
Pernod
Ricard
Jimena Egana
Diego Garcia de la Huerta
Carlos Andrade (f F de
Aguirre)
Sergio Correa, Cristian Molina,
Sebastian Ruiz Flano, f
Leonardo Contreras, f
Santiago Margozzini
Adriana Ceron, Robin Day,
Stefano Gandolini
Tarapaca
Terra Andina
/ Sur Andino
Jose Henriquez?
Carolina Arnello
Jorge Morande
Aurelio Montes Jr
S Pedro
S Ema
S Helena *
S Ines de
Martino *
Victor Baeza
Sven Bruchfeld, Santiago
Margozzini, Paul Hobbs
Eugenia Diaz
Arnaud Hereu, Paul Hobbs
Carmen
30
Terramater
Canepa
family
Patrick Valette, Cristian Vallejo
Terranoble
Terravid
Portal del
Alto
Tierra y
Fuego
Torreon de
Paredes
Undurraga *
Valdivieso
(f MataRomera)
Swiss
investors
Yves Michel, Yves Pouzet
Hernan Amenabar, f Aurelio
Montes
Brett Jackson
Coderch
family
Ventisquero *
Veramonte
Via Wine
Group
Villard
Vina Mar *
Vinedos del
Maule
Emiliana *
Franciscan
Vineyards
Coderch
family
Emiliana
Tarapaca
Felipe Tosso, Aurelio Montes
Jr, Aurelio Montes
Rafael Tirado, f? Jacques
Boissenot
Julian Grubb
Villard Spain
Viu Manent *
William Cole
William Fevre
Ignacio Conca, Henri
Marionnet
Alejandro Hernandez
W Cole USA
W Fevre
France
Roberto Lavandero, Fernando
Torres
Tatiana Eneros, Alvaro
Espinoza, Pablo Vergara
Leonardo Contreras, Aurelio
Montes
Francois Massoc
Sergio Hormazabal
Note: Not all wineries are listed, but only those with the same domestic
ownership for two or more wineries, or with foreign investment, or with known
experts, or with red wine production in Colchagua. Experts were excluded
when they were also the owners or co-owners.
* It makes red wines in Colchagua
f: formerly
Sources: Duijker (1999), Tapia (2001, 2005), Chadwick (2003), Farinelli
(2003), Guia de Vinos de Chile (2005), Hernandez and Vallejos (2005),
Molesworth (2005), Richards (2005), El Mercurio online
31
Appendix 2: The model
The professional’s satisfaction
Utility U of the wine-making expert depends on his or her wage W, the
contribution to his or her human capital stock, H, which is offered by the
current job, and the prestige P that this job gives. The sign of each of these
effects is positive.
[1]
U = U ( W, H, P )
U / W, U / H, U / P > 0
The contribution of the current job to the expert’s stock of human capital, H, is
positively affected by the level of the expert’s individual participation in the
knowledge network, N. Variable H may also depend on other factors, X,
which are not relevant to the present discussion.
[2]
H = H ( N, X )
H / N > 0
The impact of N on H is positive, even if the expert is a net giver of
information. The fact that, in the short term, the employee transfers more
knowledge to others, than what he or she receives himself or herself, is not a
problem. Although on balance in the short term he or she is giving more than
what he or she is receiving, that knowledge which he or she is giving to
someone else is not lost to the giver. He or she still keeps it. The giver is
also expecting some reciprocity in the future.
The expert’s prestige depends, with positive signs, on his or her stock of
human capital and on his or her level of participation in network activity.
[3]
P = P ( H, N )
P / H, P / N > 0
The level of network activity
Network activity is affected by human capital stocks, since knowledge flows
need some absorptive capacity at both ends (Giuliani, 2003a, b, c). Network
activity is also positively associated with the perception of identity I in network
members, as in Akerlof and Kranton (2005). Cooperation benefits from the
feeling that the person at the other end is ‘one of us’ (for example, we went to
university together, or even to the same school, etc). On the other hand, if the
expert is caught passing on information that the employer wants to keep
private, to employees of other firms, the expert will become discredited in the
eyes of the employer, and he or she may be accused of disloyalty, and
32
punished, dismissed or blacklisted. Therefore, the risk R of getting caught
affects N negatively.
[4]
N = N ( H, I, 1/R )
N / H, N / I > 0
N / R < 0
The winery’s profits
The overall presence of a winery in the domestic market, GUIX, is defined as
the product of multiplying average quality GUIQ, by the number of different
wines the company sells at home (or ‘product range’), GUINU. The names of
these variables start with the three letters GUI because they all come from the
Guia de Vinos de Chile (2005).
[5]
GUIX = GUIQ * GUINU
Quality depends on the knowledge, or human capital stock, of the winemaking expert, and therefore ultimately on the level of network activity. But
the product range depends on many other factors (Y), including the explicit
decision to either concentrate on only one, or a small number of different
products, or go for a much wider variety. Other possible determinants of
GUINU may include historical aspects or path dependence, and the possibility
to invest out of surpluses (and therefore, at a lower financial cost). The
impact of N (network activity by the firm’s own expert) on both GUIQ and
GUIX is expected to be positive, since network activity contributes to learning
by the expert.
[6]
GUIQ = GUIQ ( N )
[7]
GUIX = GUIX ( N, Y )
GUIQ / N, GUIX / N > 0
The winery’s profits  are defined as the product of the sales volume V
(including sales of award-winning wines and of wines for everyday
consumption, both at home and abroad), times the average price p, minus all
costs C.
[8]
 = Vp - C
Unfortunately, none of the four variables in Equation [8] is available. An
alternative, approximate expression for the profit equation is given in [9].
Indicators such as the overall presence of the company in the domestic
market, GUIX, and the degree of success in international competitions such
as the International Wine Challenge in London, IWC, may be positively related
33
to . Other variables, including sales volumes and costs, are represented by
Z.
[9]
 =  ( GUIX, IWC, N, Z )
 / GUIX,  / IWC > 0
The sign of the impact of the level of network activity N,  / N, is not known.
It may be positive or negative. For example, a particular firm may be a net
receiver of information that is used to increase output, quality or sales, at little
or no extra cost (which makes the sign positive). Alternatively, the firm may
be a net giver of information that makes the competition stronger, or higher
network activity may be associated with unconstrained search for quality that
leads to booming costs, or higher network activity may contribute to erode
other firm-specific advantages (all of which make the sign negative). Network
activity makes the firm’s own expert more productive, but also more
expensive, and puts him or her more in demand as both a network partner
and a potential employee of other firms.
Principal-agent conflict and multiple equilibria
Typically, the professional benefits more from his or her own network
participation, than his or her employer does.
[10]
∂U / ∂N > ∂π / ∂N
Depending on whether a particular company’s management style is traditional
or not, on how badly the firm wants to keep a particular expert, on the
company’s size, and on whether the firm sees network activity as a threat or
an opportunity, multiple equilibria are possible.
Most of the variables in Equations 1 to 10 are unobservable. However, there
are several indicators for N (Guiliani, 2003a). Average quality in the domestic
market, GUIQ, may be a good proxy for prestige P, although GUIQ applies to
the winery, whereas P applies to the individual wine-making expert.
34