Download sustaining networks - IESE Business School

Working Paper
WP-115
October, 1986
SUSTAINING NETWORKS
J. Carlos Jarillo
Joan E. Ricart
IESE Business School – University of Navarra
Av. Pearson, 21 – 08034 Barcelona, Spain. Phone: (+34) 93 253 42 00 Fax: (+34) 93 253 43 43
Camino del Cerro del Águila, 3 (Ctra. de Castilla, km 5,180) – 28023 Madrid, Spain. Phone: (+34) 91 357 08 09 Fax: (+34) 91 357 29 13
Copyright © 1986 IESE Business School.
IESE Business School-University of Navarra - 1
SUSTAINING NETWORKS
J. Carlos Jarillo1
Joan E. Ricart2
Abstract
The notion of networking is gaining widespread acceptance as a strategic tool for obtaining the
efficiency and flexibility that are so badly needed in today's economic environment. It is also
seen as the preferred way for means-constrained entrepreneurs to overcome their limitations
and launch successful enterprises. The success of many business forms that can be
conceptualized as networks, from franchising to the “Benetton system” to the web of
subcontractors behind well-known Japanese firms, reinforces the perception of networking as
an important phenomenon.
Unfortunately, networks are not easy to deal with at a conceptual level. The very essence of a
networking arrangement entails cooperation, and the mental frameworks of business policy and
microeconomics are much better prepared to address competition. Of necessity, we must
postulate a profit-maximizing behavior by business firms, leave open the possibility for
opportunism, and recognize the fact that contracts are, in many cases, not enforceable at a
reasonable cost. It is precisely for this reason that economists have traditionally seen large
organizations as the only alternative to open, competitive markets. However, a network is
something clearly in-between: independent, profit-oriented firms that cooperate over the long
term. Strategy scholars have traditionally been equally wary of cooperative arrangements:
relationships between firms are normally analyzed in terms of “power relationships” or
“competitive positions”.
The need to understand why cooperation is indeed feasible, at a theoretical level, is patent:
without such understanding, all analysis of the phenomenon, let alone any prescriptive
statement for practitioners, will be condemned to superficiality or irrelevance. It is revealing
that most research on networks has been carried out on not-for-profit firms, where the
cooperation-competition dichotomy is, at least, less acute.
This paper presents some basic theoretical ideas on why cooperation is indeed possible for
profit-maximizing business enterprises. It covers both fronts: first, why cooperation may be an
efficient arrangement; and second, how cooperation can be sustained over the long run.
Drawing heavily from games and agency theory, some basic models are established that shed
some light on real-life cooperative arrangements. In the final analysis, long-term outlook and
the ability to elicit personal trust are seen as key ingredients for a successful network.
1
Assistant Professor, Strategic Management, IESE
2
Assistant Professor, Economics, IESE
IESE Business School-University of Navarra
SUSTAINING NETWORKS
1. Introduction
“Networking” is a fashionable topic. It is receiving increasing interest in popular management
publications, as well as specialized academic journals. After many years of study of the topic from
the field of organizational theory, strategy scholars are now discovering it, particularly in the
United States (Miles and Snow, 1984; Thorelli, 1986). In Europe, a longer tradition exists, based
around British and Swedish scholars (Farmer and McMillan, 1976; Macmillan and Farmer, 1979;
Johanson and Mattsson, forthcoming; Mattsson, 1986i Lorenzoni, 1982; forthcoming).
Although increasingly more phenomena that fall under the general heading of networking are
drawing the attention of strategy scholars, the overall phenomenon is not well integrated within
the general framework of current strategy thinking. The main reason is that all networking
arrangements rest upon some sort of cooperative behavior among independent business units.
This is hard to fit in a neat conceptual way with the overall competitive paradigm.
This paper addresses this problem by showing how cooperative behavior is indeed consistent
with profit maximizing behavior, given certain conditions. We will concentrate on cooperation
between pairs of firms, as this is the simplest possible case. This analysis of dyadic cooperative
relationships will provide a building block for understanding complex cooperative networks.
The paper first tries to define carefully the concept of strategic network; section 3 analyzes
cooperation as the theoretical stumbling block, and offers some well-known insights from game
theory. Section 4 analyzes the dyadic relationship from the point of view of agency theory.
Finally, section 5 summarizes the conclusions and opens up some avenues for further thinking.
2 - IESE Business School-University of Navarra
2. Strategic Networks
A strategic network is a form of organization that it is somewhere in between “hierarchies” and
“markets”, to use Williamson’s terminology (1975)1. It can be defined as a web of “long-term,
purposeful arrangements among distinct but related for-profit organizations that allow those
firms in them to gain or sustain competitive advantage vis-à-vis their competitors outside the
network” (Jarillo, 1986a)2.
The different firms in a network are independent in most dimensions, which is what differentiates
a network with respect to a vertically integrated or quasi-integrated organization (Blois, 1972). It
is a mode of organization that is not based on the price mechanism, nor on a hierarchical
relationship, but on coordination through adaptation (Johanson and Mattson, forthcoming). It is a
long-term relationship based on implicit contracts, without specific legal ties.
We can analyze now in more detail how a network is “between” markets and hierarchies. The
different “modes” of organizing complex economic activities can be categorized by representing
them in a matrix determined by two variables: the “legal” organization and the “kind of
relationship” (see Figure 1.) This representation gives us four “prototypes” or pure forms of
organization (See Jarillo, 1986a, for a more detailed explanation):
Figure 1
Approach to the Relationship
Legal Form
Hierarchy Market
Zero-Sum Game
Non Zero-Sum Game
Classic Market
Strategic Market
Bureucracy
Clan
“Classic Market” is an arrangement where many players interact on a spot basis.
“Bureaucracy” is a hierarchical organization with many characteristics of an open market
(basically, the pursuit of different interests by the interacting agents). It can be exemplified by
the antagonistic labor-management relationship.
1
Williamson’s well-known work states that “markets” are the “normal” mode of organization. However, transactions
between independent players in those markets do have a cost. Sometimes, the transaction cost is so high, that it is more
efficient to group the two players in the transaction under the same roof, in fact eliminating the market transaction and
originating what Williamson calls a “hierarchy”, which is the equivalent to a “firm” or an “organization”. Thus
“markets” and “hierarchies” are two different modes of organizing economic activity. The most efficient one for a given
kind of repeated transaction will eventually prevail.
2
This second section of the paper draws heavily from Jarillo (1986a), where the argument is developed in full.
IESE Business School-University of Navarra - 3
“Clans” (Ouchi, 1980) are long-term relationships, carried out through non-specified contracts
within the formal environment of an organization. The unity of purpose within the
organization is strong, which lowers the cost of internal supervision.3
“Strategic Networks” are the focus of this paper. A firm has a special relationship with the other
members of the network, which are independent organizations with no point of contact in
many other dimensions. However, this relationship also has many characteristics of a
“hierarchical” relationship: relatively unstructured tasks, long-term point of view, relatively
unspecified contracts.
Once we have classified the forms of organizations, the next natural question should be to try
to understand how a network can be more efficient than any other mode of organization since,
by definition, if it weren’t more efficient, it would not survive. We can view a firm as a
collection of activities that add value between suppliers and customers (Porter, 1985). Each of
these activities can be performed internally at a given internal cost IC, or be subcontracted at a
given external cost EC. In the latter case, we will also incur in a transaction cost TC. Therefore,
a particular activity will be integrated or not depending on the relation between IC and EC+TC.
Thus, a first technological constraint for a network to exist is that EC<IC.4 Given this, it is still
necessary that the cooperating firms be able to reduce the transaction cost to the point where
EC+TC<IC. Thus, the difference between a strategic network and the market is that, in the case
of the market, TC’s are low enough for any player in the market, out of their own nature. In the
case of networks, there is a first high cost that the firms taking part in the network are able to
lower through conscious efforts. Not every firm, then, is in a situation to perform those
functions externally (because they cannot get TC’s that are low enough). The firms in the
network, therefore, enjoy a competitive efficiency out of being in the network (all other things
being equal, of course).
A network can be sustained only if it is both effective and efficient (Barnard, 1968, first
introduced those concepts applied to organizations, but they can be used fruitfully here). It is
effective if it can achieve its end at a lower total cost than alternative modes of organization.
This effectiveness depends on two factors: technological considerations and transaction costs,
as we have just seen. The network is efficient if it offers the firms taking part in it more than it
demands from them. This also depends on two factors: first, the participants realize there is a
larger pie to share (which implies both effectiveness and the perception of it); and second, there
is a fair mechanism for sharing the pie, i.e., each individual participant thinks it will gain more
by being part of the network.
3. Cooperation as the stumbling block
Williamson (1975) argues, and we have followed him, that markets fail and hierarchies emerge
because of costs that make an arrangement based on market transactions inefficient. Those
“transactions costs” stem from four reasons: man's “bounded rationality” (Simon, 1976),
uncertainty about the future, the presence of a “small number” of players for a given kind of
3
Working within Williamson’s framework, Ouchi realized that many “hierarchies” do not, in fact, eliminate
“transactions costs” between their internal constituents. He then distinguished between “bureaucracies” and “clans”.
4
A typical reason why external costs may be lower than internal costs is the possibility of capturing external economies
of scale, i.e., buying from a specialized, high-volume supplier. Stiegler (1968) develops the argument in full.
4 - IESE Business School-University of Navarra
transaction, and the possibility of “opportunistic behavior” on the part of (at least) some of the
players. Those are the hurdles an entrepreneur has to overcome in order to establish a strategic
network (or gain his or her way into an already existing one). There is only one way to do this
and that is to generate trust. As we are about to see, trust is the great transactions-cost-lowerer
(see Jarillo, 1986b). Leaving out such important points as personal congruence in objectives,
friendship and other related psychological and social factors, we shall concentrate now on
analyzing the problem of trust, from a formal point of view, by drawing some insights from the
theory of repeated games and related economic areas.
A well known problem in game theory is the prisoner’s dilemma that we will use as a starting
point of our analysis. The general form of the game, as well as a particular version of it, is
given in Figure 2:
Figure 2
Cooperation
Cooperation
No Cooperation
Cooperation
R,R
S,T
Cooperation
No Cooperation
T,S
P,P
No Cooperation
No Cooperation
15,15
5,21
21,5
12,12
In the static version of the game, each player (row or column) must choose, simultaneously to
and independently of the other player, one of the two strategies available, cooperate or not
cooperate. If both cooperate, they receive the reward R. If none cooperates, they receive the
punishment P. The problem arises because each player has a temptation value T that is greater
than the reward R. Furthermore, if one player cooperates while the other does not, he will
receive the lowest possible payoff, called the “sucker's payoff” S.5
For the general situation to be a prisoner's dilemma, we must have:
T > R > P > S6
With these relations, as shown in the example, it is better for both players not to cooperate,
regardless of what the other player does. In the game theory jargon, not to cooperate is a
“dominant strategy” for both players, so that the expected outcome of the game is not to
cooperate for both players, resulting in the payoff pair P, P. Since this outcome is “socially
dominated” by the cooperative outcome R, R, the result is highly negative. In our context, given
that many situations that arise in a business relationship can be represented in this way, we
5
The “prisoner’s dilemma”, the name given to this general model, comes from its first formulation. It runs as follows.
Two (guilty) criminals have been arrested by the police. The police has some evidence that would cause the criminals to
receive a short sentence, but they lack substantial evidence about the more serious crimes. Both criminals (separately)
are offered freedom if they give testimony against the other. If one of them does, the other is hanged. So, the reward for
their cooperation (not talking) is to obtain a light sentence. If one talks, he goes free and the other is hanged. But if both
talk, both get heavy sentences (for there is incriminating evidence against both). The outcome of the game, without
absolute trust in each other, is that both get heavy sentences.
6
Strictly speaking, (T + S) < 2*R is also a necessary condition, especially if we allow for repetition of the game.
IESE Business School-University of Navarra - 5
encounter a big difficulty for sustaining networks.7 Still more negatively, if we repeat this game
any finite number of times, one can readily realize by backward induction that not cooperating
is the only equilibrium of this game for both players.
The prisoner’s dilemma is a good formalization of the basic problem of lack of trust. In spite of
the obvious benefit of cooperation, there is a strong temptation to default and take a larger
benefit. But, even more importantly, our own fears of being fooled (and get S) induce us to act
first and not to cooperate. Since both parties, if they are rational, would think along the same
lines, we end up at the inefficient point, i.e., the relationship is not possible.
How can an entrepreneur deal with such a negative situation? One first obvious direction would
be to try to change the game they are playing. Any effort in this direction is worthwhile and
can help avoid the dilemma by eliminating it. As a static game, however, it is not always easy
to change the game so that the temptation is avoided. One trivial way to do this is to sign a
contract or similar, so that both players (one is not enough) are committed to cooperating. But
contracts are often not enforceable, at least at a reasonable cost: this is precisely the essence of
transaction costs.
Intuition tells us that repetition should foster cooperation. Theory, however, prescribes that no
cooperation is the only equilibrium in the finitely repeated game. An experiment contradicts
this point. In his book “The Evolution of Cooperation” (1984), Robert Axelrod describes a
computer game with characteristics similar to those of the prisoner's dilemma. A large number
of professional game theorists sent subroutines ready to play the role of one of the players
against all the other submitted routines. The game was repeated 200 times and everybody knew
this information. The winner was a very simple routine submitted by Prof. Anatol Rapoport
from the University of Toronto. His strategy is now known as TIT FOR TAT.
The strategy specifies the following rule: start by cooperating; at any other stage, do exactly
what your opponent did in the previous move. That's all. This strategy proved to be robust even
against players that knew that this strategy was the winner in the first round. Furthermore, it
was also robust in an evolutive simulation where the winning strategies reproduced themselves
and changed the environment for the next round. Therefore, there seems to be hope for
cooperation to survive and end up dominating, even in a world of mistrust and no cooperation.
Analyzing the traits of the winning strategy, the author finds three relevant characteristics:
first, the strategy is nice, since it never starts a non-cooperative move by itself; second, it is
provocable, i.e., it “gets mad” quickly at defectors and retaliates; third, it is forgiving, since
retaliation is proportional to the length of defections. These three “good personality traits” of
being nice, provocable, and forgiving, seem to be the essence of both the strategy’s robustness
and its survival in an aggressive environment.
Without trying to push too much in this direction, we may think that these are personality
traits we should find in an entrepreneur able to create and sustain a network. It also gives us
hope that cooperation can survive even in a non-cooperative environment and end up being
the prevalent “way of doing business”. We also realize that the strategy’s robustness indicates
7
One example is joint R&D. If several firms decide to take on a given project in a cooperative way, it is to the best
advantage of each to assign a second-rate scientist to the project, while expecting that the others will assign their
best. No firm wants to send their best scientist, fearing that the others will send their seconds. So everybody sends
seconds, with the result that the project fails.
6 - IESE Business School-University of Navarra
that it is beneficial to have a reputation for being a “TIT FOR TAT”, since it beats more
aggressive behavior in the long run, even if this behavior is designed against it. Finally, note
that this strategy never really beats its opponent; at most, they end up equal; the benefit comes
from doing well on average against any opponent.
Thus, taking a long-term approach seems to bring an effective improvement to the problems of
cooperation. Let us, then, try to analyze in more detail what including the long-term outlook
contributes to the problem.
To be more realistic, the game has to include an “uncertainty factor”, ∂. This means that the
game will be repeated with a probability ∂, depending (presumably) on the satisfactory results
of previous games, among other things. Then, the probability that the relationship will still
survive in period t is ∂t. The incentive to cheat in a particular game is tempered by the loss of
future potential gains. Obviously, the game’s results depend on the value of ∂, i.e., how much
the future is valued. It can be seen that, as ∂ increases, so does the incentive for cooperation.
Following the case in Figure 2, the incentive for not cooperating is 21-15 = 6. But, if
cooperation is lost forever, we must take into account the 15-12 = 3 loss that comes from it,
adjusted by the probability of having more chances to play. In other words, the opportunistic
gain is sure, while the future loss depends on the probability of having more games to play. We
can calculate a value for ∂ that corresponds to the cut-off point between cooperation and noncooperation.
Thus, the future value of cooperation is
 15  12 
1 
The opportunistic gain is 6. Therefore, there will be cooperation if
6
15  12 
1 
The cut-off value can be found by solving 6(1-∂) = 3∂. The result is ∂=2/3, which means that if
the parties think that there is at least a chance of 2/3 for long-term repetition of the game, they
will cooperate.8
Given our interpretation of the game as a strategic network relationship between two parties, it
seems that an infinite game with discounting that incorporates a probability of continuation is
an acceptable representation of the situation. Note that if ∂<1 the game will finish in a finite
time with probability 1, but the final time is a random variable. We are, in essence, saying that
the threat to severing the relationship becomes the main deterrent to non-cooperation.9
8
In general,
9
For this to hold, there must be a “subgame perfect equilibrium”, i.e., the threat must be credible.
( T – R ) (1 – ∂ ) = ( R – P ) ∂ ;
T–R=∂(T–P)
∂=(T–R)/(T–P)
∂ is always less than 1, for R is greater than P, by assumption
∂ can also be interpreted as a discount rate. A cash flow A obtained in period t will have a present value of A∂t.
IESE Business School-University of Navarra - 7
The lessons to be gained by these results is that cooperation may be sustainable, even allowing
for opportunistic behavior. There are three points that should be highlighted:
Repetition permits cooperation.
Threats must be credible.
The discount factor matters. Impatience makes the agreement more difficult.10
Both the theoretical solutions and the empirical analysis show the same characteristics in the
optimal strategy for supporting cooperation. This seems to be telling us something about the
way one should act to address cooperation in the long run. In summary, be nice, provocable
and forgiving. Furthermore, any particular situation can be represented as a game like the one
in our example. If we are able to modify the game, we can make cooperation somewhat easier.
We can try to reduce the temptation level, we can include stronger punishments and make them
“cheap” to implement, or we can try to modify the discount factor by increasing the (perceived)
probability of continuing the relationship. Building a reputation becomes an essential
consideration, as it clearly introduces the long-term factor.
4. The supplier relationship
So far, we have presented some fairly general points on cooperation. Let's now turn to some
aspects more directly related to actual business practices. We will start by examining
contributions from the field of agency theory. Agency theory is the branch of economic theory
that, for the last 10 years, has been formally studying the relationship between a “boss” or
“owner” and an “employee”. We will try to gain some insights from this work (for an up-todate introduction, see Pratt and Zeckhauser, 1985). Although it formally deals with “inside”
relationships (i.e., within the organization) we will apply it to the external relationship between
a larger firm and a subcontractor, for networking relationships are, again, in between external
and internal transactions. It should not be surprising, then, that an agency relationship can be
shown to have a good fit with real-life relationships between firms in a network.
We say that an agency relationship is present when we have a party, called the “agent”, that
has to act on behalf of another party, whom we call the “principal”. The a priori problem is to
find an arrangement that solves the incentive problem. There is an incentive problem if the
following three elements are present in the relationship. First, there should be some kind of
uncertainty, so that given a particular outcome, it is not possible to know with certainty if the
agent chose the right actions or not. Otherwise, an authoritarian relationship would solve all
the problems. Second, we must have some discrepancy in the agent’s and principal’s objectives.
Otherwise, the only problem is sharing the joint profits, but not how they are obtained. Third,
the agent should be risk-averse. This last condition is necessary since otherwise the problem is
trivial: give all the risk to the agent in exchange for a constant value.
Given a relation that complies with the above conditions, we have a problem of finding a tradeoff between sharing risk and giving enough incentives to the agent to choose the “right” action
that is best for the relationship. The “optimal” arrangement is the one that achieves equilibrium
10
An interesting twist is that ∂ can be lowered and the cooperation equilibrium will still hold if we include the
possibility of penalties.
8 - IESE Business School-University of Navarra
between the two opposing goals. By way of illustration, suppose that the principal is riskneutral. Then, an arrangement that gives a flat wage to the agent is the best for risk-sharing but
does not give the agent any incentive to work hard. On the other hand, an arrangement that
gives a constant payment to the principal is the best incentive for the agent to excel, but it is a
disaster in a risk-sharing sense.
Along these lines, Holmstrom and Milgrom (1985) present an interesting model where the agent
controls the drift of the outcome stochastic process, i.e., the result of the agent's acts is
determined by his effort and some randomness. With some assumptions about the utility
function and the distributions, they prove that the optimal incentive scheme is a linear function
of the aggregate outcome. The choice of the parameter of the linear function determines the
trade-off between risk-sharing and incentives. Kawasaki and McMillan (1986) use this model
for an empirical test of Japanese subcontracting, a well-publicized case of successful
networking practices.
Subcontracting is a very extended practice in Japan. There are four times as many wholesale
transactions as retail transactions in Japan; in the United States, Britain and West Germany, in
contrast, the ratio of wholesale to retail transactions is between 1.6 and 1.9. In the Japanese
automobile industry, an average of 75% of a car's value is provided by outside suppliers, and
only 25% is produced within the firm; in the U.S. automobile industry, 55% is provided by
outside suppliers. This overall trend is increasing over time. The Ministry of International Trade
and Industry (MITI) has stated that the “Japanese manufacturing industry owes its competitive
advantage and strength to its subcontracting structure” (the preceding evidence is provided and
referenced by Kawasaki and McMillan, 1986, p.1).
It has been said that subcontracting practices are simply a mechanism by which large firms
export some of their business risk to smaller, defenseless subcontractors. The larger firms
would, for instance, keep production in-house when there is a slack in demand, thus avoiding
lay-offs. The agency relationship would then be based on exporting all of the risk to the
subcontractors. We are about to show that this does not seem to be the case.
For a principal to take on some of the risk of the relationship, there must be an agreement that
shifts (at least) part of the variance in the subcontractor's costs to the principal. Let's say there
is an agreed price b. If there is a cost overrun (or underrun), the price may be maintained, and
the subcontractor is forced to bear all the risk. Or, conversely, there may be a factor , that
represents the share of variance taken up by the principal. Thus, if  = 0, then the
subcontractor bears all the risk (it is a purely fixed price contract); if  = 1, the principal bears
all the risk (it is a cost-plus contract). The problem with  = 0 is that there is no real network
relationship (it would be the case of buying something at a given, fixed price, with no further
involvement between the firms). The problem with  = 1 is that there is no incentive
whatsoever for the subcontractor to be efficient. Our prediction, from what has been said on
strategic networks (and the success of the Japanese system), is that there would be an  > 0.
Kawasaki and McMillan examine a large sample of subcontracting arrangements, and find the
following: first , the subcontractors are indeed risk-averse (as may be expected from their small
size, compared to the principals); second, the contracts have the principal absorbing some of
the risk on behalf of the subcontractor ( > 0); third,  grows , among other things, with the
subcontractor’s degree of risk aversion and the size of the cost fluctuations; finally, the average
 is 0.69, with many of them being above 0.75. This means that the contracts are closer to the
cost plus end of the spectrum.
IESE Business School-University of Navarra - 9
Although an in-depth analysis of Japanese subcontracting practices is clearly beyond the scope
of this paper, and would have to include considerations from many different fields, the previous
points allow us to realize that an agency relationship offers a good representation of the actual
arrangements of extremely successful industrial networks. Thus, the risk-sharing agreement is
basic to the relationship’s long-term success, and the principal has to be willing to take it. The
supposed “exploitation” is certainly nowhere to be found. The arrangement gives flexibility to
the large firm while the subcontractor is better off because of the risk absorbed by the big firm,
which is presumably more risk-neutral. Furthermore, the contract seems to lean more toward
the risk-sharing feature than to the incentive function. The authors try to explain this feature
by the fact that periodical recontracting, taking into account competitive offers, is by itself a
strong enough incentive to perform adequately.
5. Conclusions
The fields of game theory and agency theory can shed more light on modeling basic
networking mechanisms. For instance, a firm can specialize in designing the game that other
firms play. It is a fact that cooperation is often impossible because of information asymmetries
or some other problem intrinsic to the situation. But a third party -who can also be involved at
a different level- can act as mediator, regulator, arbitrator, etc. The inventory of conceptual
models for representing activities in a network is thus enlarged well beyond the mere
cooperation to include network building and proactive sustaining activities.
In any case, the simple models reviewed here provide the following conclusions for
understanding why and how cooperative relationships are possible.
First, there is certainly room for “in-between” situations. Relationships of the kind studied here are
neither “arms-length” nor purely internal (“hierarchical”). It is important for managers to realize
this, particularly when the decision at hand is to integrate a function (i.e., performing it “in-house”)
because of the need to control it, when it would be more efficient to subcontract it. An entrepreneur
who is trying to establish his or her firm must also realize this point, and act accordingly.
Trust is of the essence. This comes as no surprise, but we have seen how it is at the root of the
problem for cooperation. But we haven't only seen that, we have also analyzed why, following
the simple “prisoner's dilemma”. This analysis has shown the two general avenues for overcoming
the problem: develop long-term relationships (or, for an entrepreneur, do all you can to show you
are in it for the long run, that your reputation is at stake), and try to modify the game, acting on
the four variables: cooperation reward (increase); opportunistic gain (reduce); punishment
(increase); “sucker’s payoff” (reduce); and, above all, the importance of the future.
The agency model reviewed shows how risk is indeed an important consideration and how the
large firm can trade risk and incentive with the smaller subcontractor. Again, in the case of the
entrepreneur, it is up to him or her to realize the situation and implement terms that will be
beneficial to both.
These are still fairly general ideas, reduced to dyadic relationships within a network. But they
can help in conceptualizing how cooperation is possible between firms, and which are the key
variables that entrepreneurs and large firms alike must act on to improve overall efficiency.
10 - IESE Business School-University of Navarra
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