A Model of Operational Interorganizational Network Formation
September 30, 2005
Kimberley R. Isett, Ph.D.
600 West 168th St, 6th floor
Department of Health Policy and Management
Columbia University
New York, New York 10032
(212) 342-3905
Ki2129@columbia.edu
Prepared for presentation at the National Public Management Research
Conference, Los Angeles, California, September 2005
(very rough) Draft- Do not Cite
For Discussion Only
A Model of Interorganizational Network Formation
Abstract
Interorganizational relationships (IORs) in the production of public services are a
fact of life. IORs stem from a number of factors that are well documented in the
organizational theory and public administration literatures. These factors include,
but are lot limited to: environmental turbulence, political advocacy, resource
scarcity, joint production functions, broad organizational missions, power and
relationship asymmetry, and institutional coercion (DiMaggio & Powell 1983;
Galaskiewicz 1985; Oliver 1990; Milward & Provan 2000). However, in some
cases interorganizational relationships are something more than just a series of
relationships between two organizations. Instead, they become a network.
Networks are created by dyadic relationships, without a doubt. But networks are
a governance mechanism (formal and/or informal) among those organizations
that belong to it. They have shared goals and processes that extend beyond two
organizations, to a multitude of organizations that create a unified response to a
given phenomenon (Chisholm 1999; Alter & Hage 1992). Interestingly, networks
may be formed in several ways: from the bottom-up as a collective response by
individual organizational actors; from the top- down through institutional mandate
or coercion; and through some combination of the two approaches.
While we know lots about interorganizational relationships, and a good deal
about interorganizational networks, one critical element of networks has thus far
been overlooked by network scholars is network formation. This paper seeks to
address this gap in the literature by developing a model of interorganizational
network formation. This model has been developed from the extant literature on
interorganizational relationships and networks, drawing heavily from the
organizational theory and management literature.
While the organizational theory and management theory forms a base for the
model constructed, insights from other disciplines are capitalized upon.
Literature from political science is particularly emphasized, especially the
Institutional Analysis and Development (IAD) framework (Ostrom 1990; Ostrom
Gardner & Walker 1994). The combination of empirical and theoretical
knowledge emanating from the three disciplines (public management,
organization theory, and political science) creates an opportunity to develop a
comprehensive model of interorganizational network formation without
emphasizing either top-down or bottom-up approaches –a common shortcoming
in the existing literature.
2
A Model of Interorganizational Network Formation
Interorganizational networks have become a prominent method of
organizing social interaction in the past two decades. As such, this phenomenon
has gained increasing interest among organization scholars across disciplines.
The existing literature on networks mainly focuses on how networks work, the
structural aspects of networks, and the organizational and social outcomes of
networks. However, scholars have yet to focus on the early stages of network
formation.
One potential reason for the scant attention to network formation is the
close alignment of the interorganizational relationships literature to the
interorganizational networks literature. Indeed, much of the research conducted
on networks is a natural outgrowth of interest in and research on dyadic or
organization set relationships. However, the phenomenon of interorganizational
network formation is different than simple interorganizational relationships and
deserves some concerted attention.
The literature on Interorganizational relationships (IORs) has been well
developed. This literature focuses on why two organizations would decide to
form a relationship. Seminal works on explaining why IORs form have included
both management (c.f. Oliver 1990) and sociological perspectives (c.f.
Galaskiewicz 1985). These works focus on the linkages between two
organizations or the linkages from one organization to another. While this
perspective is a valuable starting point for a network perspective, it needs to be
built upon to capture the differences of networks from dyadic relationships.
3
The primary difference between interorganizational relationships and
interorganizational networks is the need for collective action. Networks require
that many organizations come together to pursue a common goal in a
coordinated and concerted way. This requires more than a simple calculus of
benefit for joint production or exchange. It requires a trade-off of short term and
individual pay-off, for longer-term collective benefits. Just how does an
organization come to a decision to participate in a network? What are the factors
that contribute to network formation? This paper presents a model of
interorganizational network formation to begin to address these important
questions.
The model presented in this paper builds on ideas of collective action and
synthesizes them with the existing IOR and networks literature to provide one
conceptualization of interorganizational network formation. Through this model, I
seek to elucidate the similarities and differences between interorganizational
relationships and networks, as well as provide insight into the process of network
formation.
Conceptual Background
Networks are self-governing institutional arrangements. These
arrangements may be explicitly designed, as in many governmental service
delivery systems (see Provan and Milward 1995 and Isett and Provan 2005), or
may be more organically developed, as in many environmental management
4
focused networks (see Ostrom, Gardner, and Walker 1998). Regardless of the
way in which they were developed, all networks have a common archetype.
All networks are flat governance mechanisms in which actors come
together to devise rules of interaction focused on joint goal attainment. The goal
attainment may be productive, social, or conservation oriented, but requires
collective action to achieve those goals. Thus, the actors in the network come
together to share decision making efforts and authority in regard to the network
goal (Alter and Hage 1993; Powell 1990; Scott 1981).
One perhaps obvious statement about networks that is worthwhile to state
is that network members come together to both give and take organizational
resources to/from the network. Incentive to participate in networks comes mainly
from an organization having the opportunity to achieve a goal that it otherwise
would not be able to achieve on its own, similar to why organizations-proper
form. However, an organization must give the other network members a reason
for including them in the network as well as a reason for sharing their
organizational resources through relationships. Thus, organizations must have
something to give as well as to take away from networks. While this exchange
may not be symmetrical, there is still some benefit to the exchange for the parties
involved.
Coordination of activities is an expensive and time consuming (Dill and
Rochefort 1989). Thus, it is not worthwhile for organizations to participate in
network activities if there is little to gain, or if the organization can achieve its
purposes without the network. Although organizations will subsume network
5
goals and agendas to their individual goals and agendas, the network still aids
the organization to accomplish something on its agenda. Thus, the benefit of
network activities must come into balance with individual organizational activities
and provide some real benefit (tangible or intangible) for the organization.
Further, to reinforce the point above, if an organization offers no reason or
benefits to other organization to interact with them in a network, then it is difficult
to discern why an alter organization would spend the resources needed to
coordinate and establish a relationship with the ego organization when their
resource would be better used developing other relationships.
Further, these exchanges in networks are not caused by serial
interdependencies (Thompson 1967). Serial interdependencies can easily be
solved through traditional market transactions. Instead, networks are more of a
function of complex integrated interdependencies. Integrated interdependencies
means that actors must put their resources into the production of an outcome at
the same time and have those contributions interact with other organizations’
contributions; without this interaction and synchronous contributions the outcome
or product of the network will not be achievable.
While networks serve network members by guiding action and activities
(Isett and Provan 2005), they also serve members in other ways. Network
members capture benefits of remaining formally independent and small, such as
speed of innovation, while reaping economies of scope and scale as well through
the structure of other organizations (Powell, Koput, and Smith-Doerr 1996). Thus
6
networks offer its members flexibility in terms of the resources of time, transition,
and cost (Sabel 1989).
Despite this knowledge of how networks work and the benefits members
receive by belonging to them, the knowledge on how and why networks form is
still scant. The early literature on interorganizational relationships suggests that
organizations form relationships in order to compensate for resource
dependencies and uncertainty. More recent literature on interorganizational
relationships has developed reasons such as legitimacy, information needs, and
stability.
James Thompson (1967) suggested that organizations will buffer their
core technologies from environmental turbulence. This means building
structures at the governance level of the organizations that focuses on boundary
spanning and acquiring needed organizational resources from that environment.
Buffering is particularly important in turbulent environments.
Turbulent environments present uncertainty for organizations in that
conditions (political, environmental, market, and/or social) are changing and
organizations have to face contingencies about how and where they will capture
organizational resources, a type of state uncertainty (Milliken1987). Turbulence
in the environment leads organizations to seek interorganizational relationships
in order to smooth out environmental perturbations and to have more certainty
with regard to resource acquisition (Oliver 1990; Galaskiewicz 1985). More
turbulence leads to greater need for interorganizational relationships, and
perhaps more of them.
7
Not only do interorganizational relationships help organizations even out
their resource acquisition, but it also helps them in their planning and strategic
management. Organizations seek out stability from their environment and their
operations. While this is a similar point to the idea of buffering core technologies
and dealing with uncertainties, it merits further explication.
Stability of relationships and within the environment helps organizations to
better adjust to market conditions and to other contingencies it encounters. We
see this concept most clearly from the contracting literature in both management
and public administration. When organizations contract with other organizations,
they must adjust their operations to accommodate the style and requests of their
partners. This is especially poignant if the partner is a major source of the focal
organization’s business or service recipients. Thus, if a contractor changes, the
organization must go through a new adjustment period which may disrupt
operations and takes time to learn and anticipate partner needs (Uzzi, 1997;
Larson 1992).
Therefore, contracting can become a stabilizing or disruptive part of an
organization’s operations, based on frequency of principal changes. So a
principal in a contracting partnership must balance the need for accountability
and flexibility through frequent contracting, with the partner/agent’s need for
adjustment and operational process norming through less frequent contracting
(Milward and Provan 1993).
Stability concerns were found to be an important variable in several
empirical network studies in the past decade. Provan and Milward (1995) found
8
that mental health networks had improved effectiveness if there were stability
related to the Network Administrator and their connections with the state.
Likewise, Isett and Provan (2005) illustrated that networks may also have stable
network structures, which helps to smooth out operations by having a stable
roster of organizations with which an organization interacts, consistent with the
buffering core technologies and pre-empting environmental uncertainty concepts
discussed above.
The vulnerabilities created by turbulence in the environment are enacted.
Just as organizations enact their environments, choosing which elements to pay
heed to and to address, they enact their vulnerabilities as well. Organizations will
choose to perceive vulnerabilities that they feel are important. More importantly,
however, is that the vulnerabilities themselves are perceived (Van de Ven and
Walker 1984). One such vulnerability that has been increasingly cited in the new
institutional literature is legitimacy.
Vulnerabilities, or perceptions of vulnerabilities, are an important reason
for organizations to come together. While most vulnerabilities and uncertainties
have some tangible quality to them, the conferring of organizational legitimacy is
one organizational resource in which the focal organization has little control of
acquisition.
Organizational legitimacy is the idea that other actors in the organizations
environment accept the organizations actions, processes and outcomes as
appropriate (Suchman 1995; Zucker 1991). Legitimacy is socially conferred from
outside the organization and can not be manufactured from within (Zucker 1991).
9
Thus, the organization is dependent upon others in their environment to bestow
legitimacy upon them.
One way that some organizations approach legitimacy acquisition is
through developing relationships with other organizations. This strategy is
consistent with upward appeal activities of organizations where being associated
with a prestigious alter organization produces a halo effect for the ego
organization (Stinchcombe, 1965). Not only does this organizational behavior
produce some legitimacy effects, it also helps the organization to overcome
some of its inherent liabilities, such as newness and size (Stinchcombe 1965;
Powell, Koput and Smith-Doerr 1996).
Legitimacy is a powerful attribution and can impact organizational
outcomes. Tolbert and Zucker (1983) illustrate the pressures to adopt civil
service reform among public agencies in order to achieve or retain legitimacy.
Early adopters became organizational and field leaders, while late adopters
experienced pressures to mimic the successes of those governments with the
reform already implemented. However, while Tolbert and Zucker illustrated the
power of adopting innovative reform, it is less obvious that the reform itself must
attain a level of legitimacy itself before adoption is viewed as desirable.
Human and Provan (2000) demonstrate the power of legitimacy for
innovations. In their study of two small manufacturing networks, they show how
legitimacy works on three levels in network: network as interaction, network and
entity, and network as form. If any of these three levels of legitimacy is not
satisfied, then the network will not be effective, and will likely disband. Thus,
10
organizational legitimacy, in this case network legitimacy, is directly related to
organizational survival.
One way that legitimacy can be developed by an organization is through
the building of reputation. Reputation is the idea that alters can predict reliably
future or current behavior based on past behavior (Ostrom 1990). Alters can
predict behavior based on a pattern that and ego has established in past or
repeated interactions. Reputation attributions are stronger the longer established
and the more consistent a pattern of behavior is. Thus, reliability is, more or less,
the reliability that other have in predicting an ego’s behavior.
Reputation is not quickly established, but rather is established over time.
Organizations must engage in repeated interactions with the same partners
(Gulati 1996; Uzzi 1997), or repeat the same interaction with multiple partners in
order to establish the necessary accumulation of behavioral patterns to be
recognized and used for prediction.
Often, reputation is tied to legitimacy in that interpretation of reputation
stems from conforming to ideas of what actions are appropriate in a particular
setting. Thus, in some sense, reputation is related to the development of
operational norms within a network or interorganizational relationships. Within
any given social situation, norms of interaction and behavior will emerge. This
signals to the actors in the social context that there is accepted ways to approach
interaction. These accepted ways of interacting conveys shared meanings and
interpretations of the social situation (Ostrom 1998).
11
Norms of interaction often develop through repeated interactions where
actors in the social context begin to react to a stimulus in consistent ways. In this
way the initiator of the interaction reads a signal that is either positive, indicating
permissive behavior, or sanction, indicating prohibited behavior. Once these
responses become consistent and systematized throughout the social context (in
our case, a network), then these reactions are normative.
Operational norms in a new social context, such as in a newly formed
network, can be developed in two main ways. First, these norms can be newly
created and go through a process of development, introduction, and acceptance,
such as in Axelrod’s illustration of the norming of a “tit for tat” strategy (Axelrod
1981). Or second, norms may be appropriated from other social contexts
(Heikkila and Isett 2004) and applied to the new setting. However, when this
occurs, there is still a period where the norms must go through an acceptance
period by the other network members.
The development and acceptance of norms in a network may be facilitated
through isomorphic processes (DiMaggio and Powell 1983). Mimetic
isomorphism for norms can take place in two ways in a network. First, networks
can mimic other networks which they desire to emulate by adopting their
operations practices and processes. Second, some members of a network may
adopt the practices and processes of a particular prestigious network member,
thus accepting their normative rules and strategies for the entire group.
Isomorphism may also be influenced by professional organizations’ expectations
12
for behavior, thereby imposing a professional ethic onto a network through
normative isomorphism.
No matter the way in which networks or interorganizational relationship
partners develop their operational norms, these norms create the day-to-day
operational rules and heuristics that members use in interacting with one
another. If disturbances to the network operating environments occur and norms
need to be adjusted, this is a slow process that will occur slowly and will require
and alignment of operational, policy, and environmental factors (Isett, Morrissey
and Topping, forthcoming; Heikkila and Isett 2004).
Norm building, reputation, and reputation effects are all greatly facilitated
by communication among organizational partners. A consistent finding in the
social science literature is that communication among partners greatly increases
commitment to collective goals and affects the functioning of the relationships
within those partnerships (Ostrom 1998). Communication helps to spread norms
and reputation, as well as affecting the resolution of uncertainty and
contingencies.
One way that terms of relationships are often communicated in their initial
stages are through legal contracts. These contracts specify what each of the
partners should do in the relationships and the compensation for compliance or
penalties associates with non-compliance or default. Contractual relationships
are ubiquitous throughout the management literature on interorganizational
relationships (Uzzi 1997, Gulati 1998; Larson 1992; Isett and Provan 2005).
13
However, as relationships are repeated and organizations begin to
discuss the solving of contingencies, rather than relying on a legalistic
framework, relationships become embedded and the terms of the contracts may
become more vague, relying more on communication. Relationships
characterized by this embeddedness (Uzzi 1997) exchange proprietary
knowledge and relationships have more specificity to the needs to their partners.
Obviously, this is an intense relationships that requires large amounts of
resources to develop. However, network governance structures are an effort to
reduce those transactions costs of relationship development and acquiring
embeddedness (Isett and Provan 2005).
As has been shown in the game theory, experimental economics, and
common pool resource literatures, “cheap talk” is a very effective way to gain
compliance and communicate emerging norms and rules to network members.
The concept of cheap talk is basically the informal interactions among members
of collective groups. Further, Ostrom (1998) shows that face-to-face
communication is more binding than more anonymous interactions such as
memos and emails.
A common theme that emerges in all of the management literature that
deals with interorganizational relationships and networks is that relationships
change over time. Time is a critical factor in developing the operational
dynamics of a network. Human and Provan (2000) show that initial network
efforts will be directed at gaining legitimacy from its members and from its
environments Time works to build a pool of information on the network
14
members, as well as the network itself. This information decreases uncertainty
for network members and helps to stave off additional turbulence potentially
created by the network.
Although time has been cited in most of the IOR literature, only a few
articles have actually looked at the evolutionary dynamics of networks. Work by
Provan and colleagues explicitly look at how the structural aspects of networks
change over time and the implications of this change for service delivery in a
network servicing adults with severe mental illness (Provan Isett and Milward
2004; Provan, Milward and Roussin 1998). Isett and Provan (2005) then go on
to assess the changes of linkages within a network and the coercive isomorphic
pressures that i9nfluence the changes in linkages over time.
Model Development
Figure 1 presents a model of interorganizational network formation based
on the literature reviewed above. Although the IOR literature is well developed
and suggests numerous factors that impinge upon interorganizational
relationships, the factors that affect interorganizational network formation are
somewhat different, albeit they build from the IOR concepts.
At the top of the model there are four factors that are relevant for
interorganizational network formation. These factors are reciprocity, legitimacy,
stability, and resources. Reciprocity is the only factor that is a necessary
condition for network formation, however, the other three factors are facilitating
15
factor. These facilitating factors can be present at the time of network formation
or can be developed in the early stages of the network.
Reciprocity is a necessary factor in network formation. As networks are
formed, organizations come together in order to accomplish collective goals.
These are goals that require input from other organizations, and that no single
organization can produce itself at a reasonable cost to that organization. Thus,
the organizations come together to capture the benefits of other organizations’
structures (Powell, Kpout, and Smith-Doerr 1996), and the benefits of
participating in the network are outweighed by the costs (Provan 1983). If an
organization is not invested in the goals or potential outcomes of the network,
there will be a disincentive to work toward the goals of the network over
individual pursuits.
The three other factors at the top of the model are facilitators of network
formation. While these three factors are not necessary to formation, they greatly
facilitate it. Further, if these factors are not present at the time of network
development they may become issues or develop early in the network formation
process.
The first of these facilitating factors is legitimacy. Legitimacy is sought for
the long tern viability of an organization, including network forms of organization.
While the conferring of on a network legitimacy in any of the ways noted by
Human and Provan (2000) (form, entity, or interaction) is not a prerequisite for
network formation, legitimacy must be achieved at some point in order to acquire
16
resources from its members and its environment. Otherwise, the network
organization will not be viable –as with organizations.
The second of the facilitating factors is a contextual in nature –stability.
The political, cultural, and operating environments in which the network seeks to
form must have sufficient stability so that the network organizers can focus on
and facilitate coordination and cooperation. While this is not absolutely
necessary –since the network may be an attempt to bring order to chaos - some
stability in the three environments would lend to the development of the trust and
communication that are necessary to create cohesive collective action.
Otherwise, with excessive instability, individual organizations may be too
distracted putting out their own fires to fully pay attention to or address issues of
collective governance and norm building, as needed in anew network entity.
The final facilitating factor is also contextual: resources. Many IORs and
networks form out of the need to address resource scarcity (Aiken and Hage
1968). However, if there is not at least a minimal level of resources available for
network formation –time, money, and/or human resources –then network
formation and viability will be tenuous. The actual amount of minimal resources
needed for a network tog et off the ground will be varied and will depend upon
scope and scale of network activities, and the type of network/network structure
chosen.
These four factors, one necessary and three facilitating factors, are the
precursors for the collective action necessary to create a network. These factors
can come together to create a network. However, the simple presence of these
17
factors does not mean a network will be created, just that it may. There are two
causes of network formation that must be present for a network to form: will and
knowledge.
First, the will must be there to create a network. A network is a social unit
of organization. Actors, in our case organizations, must desire to come together
and work collectively. This desire may be organic –as in many bottom-up
networks that form (see the CPR literature, especially Ostrom and colleagues’
work). It may be imposed –as in many government funded service delivery
network (see the mental health literature, especially the results of the ACCESS
study by Morrissey and colleagues). Or it may be some combination of the two
(especially the work of Provan and colleagues). Although the desire may come
from many places, it must be present in order for the network formation to occur.
Will also encompasses the classic idea of collective action: that actors
must be willing to voluntarily act to further their interests in collective goals and
activities (Ostrom 1990), while also avoiding the temptation to free ride on the
activities of others. There must be a conscious collectivity of a broader
governing logic for a network to be present. Otherwise, the partnerships are
merely a series of dyadic, atomistic relationships. In other words, there must be
a will to coordinate.
Second, there must be knowledge that the factors exist in order to form
the network. If an organization does not know that other organizations exist that
have complementary products and services to accomplish a goal, or even who
those organizations are, then it is not likely that the organization will see a
18
partnership with those organizations. An analogy to clarify this point is if you do
not know that you have eggs in the refrigerator, it doe not matter that you have
flour in cupboard. You just will not think of baking a cake, or that baking a cake
is possible given current resources.
So, assuming that the necessary formation factor of reciprocity is present,
there is sufficient will and knowledge to form a network, and the facilitating
factors are present in varying degrees (including not at all), then a network may
form. Organizations can come together to form a network. However, there are
some important transformation processes that must occur in order for a network
to pass the threshold of burgeoning/neophyte to an operational network.
The evolution from a neophyte network to an actual operating network is a
process that develops communication, norms appropriate to incentives, and
reputation over time. Time is the essential characteristic in this transformation. It
has been well documented that norms are very slow to evolve, as well as
reputation and trust effects to occur. All of this happens through increased and
repeated interaction where communication is open and facilitated.
Several strain of literature support this emphasis of time. Common Pool
Resource and Game Theory scholars have shown that actors facing a social
dilemma will adjust their strategies over time to achieve the best possible
outcomes (Axelrod 1981, 1984; Ostrom 1990, 1998). Further, organization
theorists have shown that time is a critical factor in the development of
sustainable relationships between organizations (Gulati 1995; Larson 1992; Uzzi
1997; Van de Ven and Walker 1984).
19
In the laboratory and in field settings, communication has been shown to
enable the resolution of commons problems (Ostrom 1990) and in sustainable
IORs (Larson 1992; Gulati 1995; Uzzi 1997; Van de Ven and Walker 1984).
Communication helps to facilitate the exchange of ideas, proprietary knowledge,
and future strategy intentions between actors in a collective action situation
(Larson 1992; Ostrom, Gardner and Walker 1994; Van de Ven and Walker
1985). This communication assists actors in reducing their perceptions of their
core vulnerabilities as well as aiding others in predicting future outcomes
(Lazerson 1995; Ostrom 1990, 1998; Uzzi, 1997). As stated by Ostrom (1998,
7), “exchanging commitment, increasing trust, creating and reinforcing norms,
and developing a group identity appear to be the most important processes that
make communication efficacious.”
One way in which group identity is created is through shared norms.
However, norms must be consistent with and enhance the incentive structures in
an operational network. Misalignment of norms and incentives could work to
impede achievement of network objectives. Social learning takes place among
the members of a network in how to behave, as well as how to interpret and act
upon the formal legal structures of the network. When adequate social and legal
guides are in place (through incentives and norms) the temptation to free ride or
behave counter to the collective goals is reduced. This reduction of deviant
behavior creates an opportunity to realize collective goals and outcomes for the
network.
20
Reputation that can develop into trust is perhaps one of the most widely
cited factors in creating viable IORs and IONs. Consistent interactions with other
actors create predictable future behavior (Gulati 1995; Ostrom 1990; Uzzi 1997).
This consistency creates reputation for those outside the relationship, and trust
for those more involved in the relationship. Once reputation is established,
commitments to behave in a particular manner become viewed as credible, and
the transactions costs of interactions then decline (Isett and Provan 2005).
Reputation will become enhanced or devalued as communication allows others
to make judgments about the credibility of other actors’ intentions (Gulati 1995;
Ostrom 1998). Thus, reputation and trust emerges in a network when promises
from one actor to take certain actions are accepted at face value or become
embedded in the pattern of the relationship (Uzzi 1997) by other actors.
The transformation stage of operational network formation varies by
network, and may never actually yield a viable network. The time that
transformation takes will be unique to each network and will depend on a number
of variables such as number of members, scope and scale of operations, existing
history among members, and the like. However, once the transformation begins,
patterns of interaction will begin to emerge. Once these patterns stabilize and
governance issues are settled, an operational network emerges.
It is important to note that not all networks will reach viability and become
operational. Many networks will languish for years in the transformation stage
and never really emerge as an operational entity. Also, while outcomes may be
accomplished during the transformation stage, the focus is on governance and
21
development issues, not the network goal. While these networks clearly have
outputs, they are not viable in that trust and norm alignment has not occurred.
Until viability is achieved, network will likely only produce outputs, not outcomes.
Conclusion
This model is a first look at how organizations come together to form
interorganizational networks. In this paper I have attempted to outline the
theoretical and conceptual elements of the existing literature that have framed
my thinking on interorganizational network formation. This paper has also
attempted to delineate where the networks literature differs or develops
differently from the literature focused on dyads or organizational sets.
As such, a model has been presented and developed to conceptualize
how networks form, why some become viable, and the elements which are a
harbinger of dissolution and failure.
22
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Figure 1
A Model of Operational Interorganizational Network Formation
Network PreConditions
legitimacy
stability
reciprocity
Neophyte/Burgeoning
resources
will and
knowledge
Transformation
time
communication
Norms
reputation
Viability
operational network
26