Multi-Level Complexity Inthe Management of Knowledge Networks

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Multi-level complexity in the management

of knowledge networks

Lisa Beesley

Lisa Beesley is a Researcher,

School of Marketing and

Management, Gold Coast

Campus, Grifth University,

Queensland, Australia

([email protected]).

Abstract While it is widely acknowledged that economic growth is now dependent on the

realization of a knowledge based economy, there remains much confusion as to how this is

actualized. Effective management of knowledge is endorsed as an essential element for

organizational survival and competitive advantage, yet again, the ways in which knowledge

moves through knowledge networks remains poorly understood. This paper is the result of a

three-year qualitative investigation of the dynamic relationships among knowledge creation,

diffusion, and utilization occurring in situ in a collaborative knowledge network. In an attempt to

better understand how knowledge unfolds in such a system, this paper explores emergent

patterns, not only within individual, group, organizational and inter-organizational levels of

learning, but also among them. Two theoretical models acknowledging the multi-level

complexity of knowledge management in organizations while simultaneously identifying the

common inuences among them, are presented. In combination, it is then possible develop a

theoretical framework through which to better understand the relationships among knowledgecreation, diffusion, and utilization in collaborative knowledge networks, and thereby, optimize

the utility of knowledge designed for organizational application.

Keywords Learning organizations, Knowledge management, Information networks

It is widely recognized that the competitive edge for industry now comes through knowledge

and the ability of the organization to learn. In order to drive economic growth, recent

government policy in both developed and developing nations, demands greater interaction

among industry, government, and institutions of science in the production of knowledge. In

spite of broad acknowledgement of the complex dynamics found within these knowledge

networks, there remains the expectation that research will produce knowledge that is of

immediate use to industry, which in turn will promote economies. The underlying assumption is

that research generated in this sequential order will have direct and immediate applicabilityand will be used for problem solving (DIST, 1995; Slatyer, 1990, 1993; Stocker, 1997) yet,

knowledge is not typically drawn upon in a direct and supportive manner in organizational

decision making (Weiss, 1995, 1980). Of further interest is that although little is known about the

ways that the dynamics inherent in knowledge networks inuence the eventual production of

knowledge, the perception that collaborative research emerging through knowledge networks

will make important contributions to a knowledge-based economy continues to gain

momentum (Etzkowitz et al., 1998).

If knowledge is to drive innovation and economic growth optimally, it is important not just to

develop an understanding of the processes underlying the creation, diffusion, and utilization of

DOI 10.1108/13673270410541051 VOL. 8 NO. 3 2004, pp. 71-88, Emerald Group Publishing Limited, ISSN 1367-3270

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knowledge produced for organizational application, but also the relationships among them.

Therefore, it is important to ask which factors more or less inuence the degree to which

knowledge designed for organizational application is utilised? The purpose of this paper is to

present a multi-level analysis of knowledge management one that encompasses individual,

group, organizational, and inter-organizational learning. This is with a view to identifying

common elements or some emergent order that would enhance or impede the effective

creation, dissemination, and utilization of knowledge not only within each level of learning, but

also among them. In so doing, it is possible to develop a theoretical framework through which to

extend current understanding of the way in which knowledge moves through collaborative

networks.

Knowledge moves to center stage

Why knowledge is not used systematically to inform decision-making and policy formulation has

been the focus of much enquiry. Social scientists have sought to describe and explain the use

of knowledge and, in so doing, have generated a substantial body of research investigating the

inuence of social factors on the acquisition, dissemination and utilization of knowledge

(Paisley, 1993). Simultaneously, cognitive psychologists have produced several theories

attempting to explain the structure and mechanisms of the cognitive processes underlying the

acquisition, creation and use of knowledge (see Eysenck and Keane [2000] for a review). Social

cognitive theorists strive to integrate social and psychological processes in order to map the

cognitive processes that underlie social interaction, and the emotional responses that are

associated with cognitive activity, while sociologists have investigated the role of politics and the

degree to which knowledge is drawn upon to inform decision-making.

Recent contributions to the study of knowledge management have moved away from a focus

on information indexing and retrieval systems, to effective knowledge management through

human resource practices (Soliman and Spooner, 2000; Bhatt, 2001; Myers, 1996). These

theories acknowledge the complex interplay of social factors, communication systems, and

organizational structure, and the relationships between them (Augier et al., 2001; Lincoln, 1982;Leydesdorff, 2000; Nonaka and Takeuchi, 1995; Nonaka and Konno, 1998; Nonaka et al.,

2000). However, no comprehensive theoretical model has been published that describes

the ways in which knowledge moves across individual, group, organizational and inter-

organizational levels, while simultaneously identifying the common elements within each level.

This paper is the result of a three-year research project that aimed to develop an understanding

of how these elements operate within and among each level of learning.

Organizational and inter-organizational learning

Fundamental to knowledge networks is the concept of organizational learning. Theories of

organizations, as knowledge-creating entities have focused on how complex, unstructured

problems are solved, and context and contextualization are considered central elements in the

task (Knorr-Cetina, 1981; Nonaka and Takeuchi, 1995; Nonaka et al., 2000; Nonaka, 1999).

Putting knowledge in context is important because knowledge-creating processes areessentially context-specic in terms of who participates and how they participate in the

process. The context here does not mean a static set of surrounding conditions, but rather a

dynamic process of which individual cognition is only a part.

The concept of knowledge networks is based on a theoretical perspective whereby networks

are dened as a social relationship among actors (Lincoln, 1982; Mitchell, 1969; Seufert et al.,

1999). Actors in a social network can be individuals or groups, but also collectives of

organizations, communities, or even societies (Seufert et al., 1999). The relationships evolving

among actors can be categorized according to content, form and intensity. Content refers to

products or services, information or emotions, form concerns the duration and closeness of the

`` Fundamental to knowledge networks is the concept oforganizational learning. ''

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relationship and intensity considers the frequency of communication. Typically, the relationships

among actors are of diverse forms, which may consist of various contents to be exchanged.

The form and the intensity of the relationship occasion the network structure (Seufert et al.,

1999). Further, the relationships between network members can be understood as deriving

from their autonomy and interdependence, the coexistence of cooperation and competition as

well as reciprocity and stability. Boundaries of networks are difcult to determine since they are

constructed socially by the network members. Accordingly, they are referred to as blurred

boundaries. From this perspective, the focus moves from the consideration and protection

of the boundaries of an organization to the management of and care for relationships.

Consequently, the knowledge assets of an organization lie in the pattern of relationships

between its members and are destroyed when those relational patterns are destroyed (Stacey,

2001).

Research shows that the degree to which knowledge is acquired and utilized in organizations

results from the interdependent inuences of organizational processes (Fulop et al., 1999;

March, 1988b, 1999; Pfeffer, 1981; Schaef and Fassel, 1988; Shapira, 1997; Turner, 2001),

individual limitations (Roch et al., 2000; Pruitt and Carnevale, 1993; Paulus and Huei, 2000;

Nonaka, 1991; Mohammed and Ringseis, 2001; Kleket et al., 2001; Kolb, 1984; Calvin, 1997;

Baum and Ingram, 1998) and the control opportunities and control problems that arise through

organizational structure (Allison, 1971; Frohock, 1979; Kattenburg, 1980; Weissinger-Baylon,

1988; Hayes, 1992; Lindblom, 1959, 1979; March 1988a,b; Simon, 1957; Fulop et al., 1999).

Therefore, organizations contain static (rules, norms and procedures) and dynamic (social

relationships) elements that mutually inuence the degree to which knowledge is acquired and

utilized in organizational settings the degree to which organizations learn.

The literature has shown that establishing functional networks means developing a common

language, a set of working assumptions, and trust among dissimilar people (Argote, 1999;

Argote and Ingram, 2000; Senge, 1990; Senge et al., 1994; McElroy, 2000). It is suggested this

is achieved through demonstrations of patience (Senge, 1990; Senge et al., 1994), tolerance

(Gavin, 2002) and compromise (Rietan, 1998). However, compromise can limit the capacity for

creativity and diversity resulting in safe, ``incremental'', middle-of-the-road solutions that

participants might not fully support (Rietan, 1998). Additionally, it is the balance between

creativity, and rules and procedures designed to ``buffer'' uncertainties that inuence the extent

to which organizations may learn (Delahaye, 2001, p. 534). Organizations themselves do not

learn per se, but rather, learning occurs within those who constitute their membership.

Accordingly, while network theories recognize organizational structure, social relationships, and

information and communication tools, they fail to identify adequately the ways in which

individuals and groups might negotiate their way through these networks in order to harness

and utilize knowledge optimally.

Group learning

While network theories acknowledge the complexities in which knowledge is managed, the

ways in which knowledge is utilized within individuals and groups is largely understood through

models that presuppose rational and linear processes as knowledge is drawn on to inform

decision-making and planning tasks. However, as many members of organizations have

discovered from their own experience, real decision processes in organizations infrequently t

this depiction.Decisions made in knowledge networks are rarely made by individuals acting alone. Rather,

decisions result through groups of individuals coming together, pursuant to a common goal.

Yet, research has shown that the degree to which groups acquire knowledge in order to inform

decision making, that is, the degree to which groups learn, is also subject to several inuences.

Recent contributions to this eld (Thompson et al., 1999a; Thagard et al., in press; Rowley,

2000; McElroy, 2000; Harinck et al., 2000; Argote et al., 2001; Argote, 1999) have looked to

group composition, group size, and familiarity among group members, communication

processes, and more recently, the role of emotion, in an attempt to solve this quandary. To

further develop an understanding of the ways in which groups learn, it is important to

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understand the ways in which individuals acquire knowledge, since group learning can not

occur if the individuals that give it form have not engaged in learning processes.

Individual learning

While there are varying denitions of knowledge, and what constitutes knowledge, for the

purpose of this investigation, knowledge is described as information that is imbued with

personal relevance or meaning. Knowledge acquisition has also been described in terms of

different skills that are required in order to effectively draw in new information and attribute it

with meaning (Sveiby, 1997; Savage, 1996; Lundvall and Johnson, 1994). From this per-

spective, the acquisition of knowledge involves procedural and contextual knowledge skills.

Procedural knowledge involves knowing how to take data, turn it into information and

incorporate that into existing networks so as to expand one's knowledge base. On the other

hand, contextual knowledge involves an acute awareness of one's environment, the issues

arising from it, and how that individual is embedded within it. If research ndings arising through

knowledge networks are to be utilized in problem solving or decision making tasks, it must rst

be integrated into an individual's knowledge structure procedural knowledge presupposes

that an individual has been able to identify where that new information ts within existing

knowledge structures. This means that individuals must know where knowledge ts within

existing knowledge structures before they are able to identify how that new knowledge might

change the ways in which they currently think about something. Therefore, knowledge

acquisition and utilization requires both contextual and procedural knowledge.

While there have been several theories to represent the structure of knowledge within an

individual, more recent connectionist or cognitive network theories, provide a useful platform

from which to understand individual knowledge acquisition (Rumelhart, 1980; Rumelhart et al.,

1986a; Rumelhart 1989). Knowledge can be represented as a collection of networks consisting

of elementary or neuron-like units or nodes containing information (see Figure 1).

These are connected together so that a single node has many links to other nodes. Each of

these other nodes can transmit an excitatory or inhibitory signal to the rst node. This node

generally takes a weighted sum of all these inputs. If this sum exceeds some threshold, it

produces an output that may then feed into another node, which does the same. Individual

learning occurs by associating various inputs with certain outputs, and then by storing patterns

of activation, or associations within the cognitive network. The establishment of theses patterns

of activation or associations in the network is how information is instilled with meaning.

Knowledge acquisition is a process in which networks are continuously reconstructed from an

existing network, while their similarity to or divergence from these preceding networks is at the

same time negotiated.

There are also functionally different collectives of cognitive networks, such as those that

encompass action (Pascual-Leone, 1997), logical and conceptual tasks (Pascual-Leone, 1984;

Wilkes, 1997), emotions (Forgas and George, in press; Forgas, 1999, 2000; Bower, 1981), and

social functions (Bar-Tal and Kruglanski, 1988; Fiske and Taylor, 1991; Gruenfeld and

Hollingshead, 1993). These collectives of networks are all capable of dynamically interacting

with each other (Pascual-Leone, 1997) while simultaneously operating in conjunction with

personal experience, cognitive ability and the willingness, or lack thereof, to engage in more

demanding cognitive processes that are sometimes required to acquire new knowledge

(Cropley, 1997; Eysenck, 1997; McClelland, 1963; Sternberg, 1988).

One important relationship to acknowledge is that between cognition and emotion. There has

been much debate over whether emotion requires cognition, or whether emotion can occur

`` Actors in a social network can be individuals or groups,but also collectives of organizations, communities oreven societies. ''

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independently of cognitive activity (Lazarus, 1982; Zajonc, 1980, 1984, 2000). Since thesetheories have been based on experimental research ndings, others have argued that the

debate is meaningless since the articial nature of the experimental settings fails to replicate

ordinary affective states and the social context in which emotion is normally experienced is de-

emphasized (Steptoe and Vogele, 1986; Power and Dalgleish, 1997; Parkinson and Manstead,

1992). While it is heuristically useful to use different names for different aspects of the origins of

affect, the parts are inseparable (Power and Dalgleish, 1997) cognition and emotion are

inextricably linked (Eysenck and Keane, 2000).

This brief overview of the literature demonstrates the high level of interest and enquiry into the

ways in which individuals, groups and organizations learn. In spite of this, and the fact that the

terms ``group learning'', ``organizational learning'', and ``knowledge management'' have come

into widespread usage among managers and scholars alike (Skyrme, 1999), popularity in

promoting learning systems contradicts the fact that the process by which knowledge iscreated, diffused and utilized in knowledge networks remain poorly understood (Brief and

Walsh, 1999). One reason for this is that many models of learning have arisen through research

conducted in experimental settings that fail to take into account the dynamics occurring in situ

(Argote et al., 2001). Therefore, the question is, what common elements exist among the four

level of learning in knowledge networks in real life settings, and in what ways do these elements

facilitate or impede the creation, dissemination, and eventual utilization of knowledge designed

for organizational application?

Any explanation of the ways in which knowledge is acquired and utilized in knowledge networks

must consider the process of knowledge acquisition and utilization at not only across the four

Figure 1 A multi-layered connectionist network showing (a) an input layer, (b)

internal representation layer, and (c) an output layer (adapted from

Rumelhart et al., 1986)

(c)

(b)

(a)

Input Layer

Internal

Representation

Layer

Output Layer

(c)

(b)

(a)

Input Layer

Internal

Representation

Layer

Output Layer

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levels of learning, but such an explanation must also acknowledge the cognitive (Anderson,

1996, 1988; Eysenck and Keane, 2000; Rumelhart, 1989; Rumelhart et al., 1986b), social

(Baggozzi et al., 1998; Bar-Tal and Kruglanski, 1988; Bendelow and Williams, 1998; Fiske

and Taylor, 1991; Forgas and George, in press), and communication factors (Langeld-Smith,

1992; Larson et al., 1994, 1996; Schwarz, 1994; Stacey, 2001) that are known to inuence

knowledge creation and utilization across all levels of learning. Through this approach, while

drawing on existing theories from the elds of sociology, and cognitive, social and organizational

psychology, this investigation aimed to examine the relationships among knowledge creation,

diffusion and utilization in a collaborative knowledge network, with a view to identifying the most

efcient means for formulating and disseminating research designed for organizational

application.

Method

This paper is based on the ndings of a three-year qualitative study of the relationships among

knowledge creation, diffusion, and utilization in a collaborative research undertaking involving

industry, local and State government stakeholders, and academic researchers, brought

together by a facilitating agency[1]. The ndings of the collaborative research project under

investigation were intended to inform the strategic management and future planning and of a

tourist destination. Such collaborative undertakings are frequently referred to as ``visioning''

projects. The project involved 22 separate research projects encompassing marketing and

positioning studies relative to domestic and international markets, market trends analyses,environmental and social impact studies, and facilities and infrastructure audits. Accordingly,

this visioning project provided the ideal forum in which to investigate the conceptualization

and utilization of knowledge designed for organizational application. Further, it allowed the

investigation of organizational learning where disparate participants coalesce and, in turn,

create an organization within its own right. Since these individuals represent and belong to other

organizations, there is simultaneously an opportunity for inter-organizational learning to take

place through the networks that are established.

Throughout this longitudinal study, data were collected through stakeholder interviews, various

documents, and participant observation of stakeholder meetings and workshops. Data were

analyzed using a grounded theory approach (Strauss and Corbin, 1990, 1994; Glasser and

Strauss, 1967), which involved an iterative process of continual sampling and analysis in which

existing literature served, not only to inform, but be informed by the analysis. In the absence of

any strong prior theory, this analytical task involved the sorting and extraction of meaning from

data that was most frequently unstructured. This systematic approach facilitated the generation

of codes to represent low-level concepts and more abstract categories or themes.

It should be noted that the analytical approach taken in this study should not be identied

merely by way of coding. To view the analysis as simply a form of coding is to view it as a form of

content analysis (Strauss and Corbin, 1994) and serves to dilute the importance of the research

ndings. Rather the analysis in this study incorporated methods of theoretical sampling

and constant comparison methods that clearly differentiate grounded theory from traditional

content analysis. Accordingly, throughout the duration of the project the analysis involved the

active sampling of new cases (being driven by theory with new cases being selected for their

potential to generate new theory or deepen the researcher's emergent understanding) and the

continual process of sifting and comparing basic data instances, emergent categories and

theoretical propositions. Therefore, as researcher I was sensitized to similarities and discrep-

ancies in the data and these served to promote conceptual and theoretical development.

Results

The results of this study clearly showed that while collaborative knowledge generation implies

a mechanism for joint decision-making, it need not follow that such mechanisms evolve. This

was evident in that, although the facilitating agency stated that the collaborative process itself

would provide a means of managing the tension between cooperation and the autonomy

organizations require in competitive environments to the extent that, by denition, collaboration

implies a mechanism for joint decision making among autonomous and key stakeholders of an

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inter-organizational domain, full stakeholder engagement was never achieved. There were

several factors that contributed to this outcome.

The management of the project was fundamentally awed in its assumption that the collabor-

ative process itself provides a means of managing tension. In fact, the approach the facilitating

agency took could be described as confrontational, since it was designed to ``challenge

mindsets and take people out of their comfort zones''. The result was that stakeholders

experienced negative affective states as personal values and belief systems that individuals

either previously held in esteem or were institutionally dependant on were brought into question.Stakeholders responded negatively and used their organizational positions to engage in political

activities designed to discredit the project, thereby satisfying self-interests. The facilitating

agency responded as if they were in crisis control mode; they began to behave as if they were in

a state of political panic. Their reaction was to narrow stakeholder focus to those they saw as

being able to bring about change. The high level of engagement with policymakers (to the

neglect of many industry stakeholders) meant that the facilitating agency gained greater

ownership and control of the project.

As the facilitating agency negotiated their way through the political mineeld that developed,

they realized the danger, and increasing likelihood that the visioning project could collapse

under its own political weight if not carefully managed. Accordingly, the ownership and control

the facilitating agency took over the project, while less than optimal, was perhaps a prudent

(and practical) response, if the project was to survive and realize the objectives that

underpinned its existence. Project management believed there was a need for the visioning

project's strategic research program, and that research ndings arising through the program

would serve to benet the destination's tourism industry and the region. As many industry

stakeholders did not share this belief, the facilitating agency directed their efforts of engagement

and dissemination of research ndings at a policymaking level. While the processes the

facilitating agency engaged in departed from those required of a learning organization, they did

not prevent learning from occurring.

The paradigm shift that occurred in local government in terms of how they viewed the role of

tourism in the local economy reected organizational learning to some degree. Due to the high

level of engagement of the local government, and the intensity of interaction between local

government and the facilitating agency, information was continually being fed to them, and

although the information was not always received willingly, over time elements of the ndings

had crept into decision making and policy formulation. What is of interest is that this knowledge

``creep'' occurred without decision makers realizing that the source of their information was the

visioning project.

When individuals were presented with information that was contrary to their existing beliefs or

values, acceptance of that new information frequently became problematic as they tried to

determine where that information might t within existing knowledge structures. If the new

information is to be accepted, then some elements within existing knowledge structures must

change in some way. In determining what knowledge structures must alter in order to integrate

new information, recipients experienced the negative affect that may be associated with

cognitive change, but were not always cognizant of why they were experiencing it. This being

so, individuals experienced a state best described as ``cognitive disequilibrium'', which is oftendifcult to resolve. To resolve this unbalanced state of cognition, recipients often chose to reject

the information and in so doing, diminished the negative affective states experienced when new

information conicts with existing cognitive structures.

Incoming information that does not easily assimilate into existing knowledge structures may

result in an affective response so strong, that new information cannot be acquired at that point

in time. That is, individuals may reject information before they engage in the cognitive tasks

underpinning the reective processes required to determine how or where that information

might t within existing knowledge structures. However, the results showed that over time, as

individuals reect on the information, it is gradually assimilated into their knowledge structures,

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even though they may no longer be conscious of where that information originated. This

suggests that the incremental acquisition of knowledge is less challenging to an individual's

existing values and belief system than radical restructuring of knowledge networks; the affective

response associated with change is diminished and new knowledge is able to creep into

existing knowledge structures.

Members within a knowledge network bring to the network different frames of reference,

different expectations, and different knowledge bases. As a result, communication was

frequently inhibited, and while overt behavior of network members gave the appearance of

dissension, in fact, what was being sought was a common frame for understanding and

communication. Additionally, the gap between members' worldviews generated the sense that

some members were resisting or failing to understand what the network was seeking to

achieve. Consequently, in order to manage the relationship, research plans and ndings were

communicated to members in a teacher-to-student fashion, which fostered single-loop

learning, and reduced industry stakeholders' sense of ownership in the process and ndings.

During the project, industry stakeholders frequently sought to have research come pre-

packaged with ``meaning'', but the producers of that knowledge lacked the degree of

contextual knowledge necessary to specify the relevance of their information to would be users

of that information. Producers of knowledge must develop an understanding of the context in

which that knowledge applies. Accordingly, new knowledge needs to be integrated and

diffused to network members over time, and specic applications need to be formulated (and

reformulated) in response to particular and changing needs of the network.

The results of this study clearly showed that there are common factors operating within and

among the various levels of learning in a collaborative knowledge network. In identifying these, it

is then possible develop a theoretical framework through which to better understand the

relationships among knowledge creation, diffusion, and utilization in collaborative knowledge

networks, and thereby, optimize the utility of knowledge designed for organizational application.

Theoretical implications

As a result of this investigation, a theoretical framework has been developed that identies ve

common factors operating within and among the four levels of learning identied earlier. In order

to identify these factors, and the ways in which these factors inuence the ways in which

knowledge is managed, it is important to recognize the interdependence among the four levels

of learning. Figure 2 acknowledges not only the interrelatedness, but also interdependency

among these levels of learning.

The order in which the concentric circles are embedded within each other is not to accord more

importance to any one level over another, but is intended to demonstrate the interdependent

and symbiotic nature of knowledge acquisition. The results of this study show that learning at

one level cannot take place until it has occurred at the previous level; nor it is possible to

understand the process of learning at one level until understanding of the process at a previous

level has been attained. However, given the dynamics that occur in knowledge acquisition

across all levels, the relationship among these levels is not seen as linear, but rather with each

level being nested within another. This depiction of learning levels provides the foundation on

which to offer a theoretical explanation of the relationships among the creation, diffusion and

utilization of knowledge intended for organizational application. The factors identied in this

study can be classied as belonging to one of ve variables that would inuence this process:

social contingencies, communication processes, cognitive processes, affect and values. The

manner in which these ve factors relate is displayed in Figure 3. As the gure shows,

`` Members within a knowledge network bring to thenetwork different frames of reference, differentexpectations and different knowledge bases. ''

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knowledge acquisition and subsequent utilization nests within the simultaneous inuences of

cognitive, communication and social conditions.

In this instance, cognition would encompass all the functionally different collectives of

associative networks, as they operate in conjunction with personal experience and cognitive

ability. Social contingencies encompass concerns such as group think (Janis, 1982), group

polarization (Lamm, 1988; Lamm and Myers, 1978), relationship building (Seufert et al., 1999),

trust (Cvetkovich and Lo fstedt, 1999; Fulop, 2002), social validation (Hinsz, 1990; Stasser,

1999), social structures (Nonaka et al., 2000; Nooteboom, 1999; von Krogh et al., 2000; Seufert

et al., 1999), status (Cialdini and Trost, 1998), leadership (Barling et al., 2000; Chrislip and

Larson, 1994; Sogunro, 1998), power (Bendor et al., 2001; Fulop et al., 1999), and of course,

politics (Cohen and Olsen, 1975, 1976; Cohen et al., 1972; Lindblom, 1959, 1979; Simon,

1957). The third helix displayed in the model represents communication issues. This includes

not only dissemination efforts (Backer, 1993; Caws, 1998; Goldberg, 1997; Knott and

Wildavsky, 1980; Stocking, 1998), in whatever form that might take (Argyris and Scho n, 1974,

1996; Halme, 2001; Michael, 1973), but also communication of affective states (Barsade, 2001;Barsade et al., 2000; Thompson et al., 1999a,b) and the establishing of a common frame of

reference, or attainment of mutual understanding (Augier et al., 2001; Schuetz 1962, 1964,

1967).

It is only when the inuence of these three factors is acknowledged and managed effectively,

depending on the situation and specic needs accordant to it, that there exists the potential for

maximum knowledge gains. However, the degree to which knowledge is acquired is not only

dependent upon these three factors. Figure 3 shows these three factors as being embedded

within affect. The role of affect cannot be separated out from the analysis of human behavior

since it underpins our very existence (Barsade et al., 2000; Barsade, 2001; Eysenck and Keane,

Figure 2 The interrelated levels of learning

Individual

Learning

Group

Learning

OrganisationalLearning

Inter-organisationalLearning

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2000; Forgas, 2000; Lazarus, 1982; Power and Dalgleish, 1997; Zajonc, 1980, 2000).

Consequently, affect is recognized as a factor that permeates all others.

Finally, as affect is said to be an expression of underlying belief systems (Forgas and George, in

press), which are, in turn expressions of a set of values (McKnight and Sutton, 1994), values are

shown to underpin the entire process. Relationship building and trust, essential elements in an

effective knowledge network, results from individuals gradually exposing more of their values

and beliefs through words and actions that are shared over time (Maturana, 1980; Schuetz,

1962, 1964, 1967). It is only through the development of interpersonal relationships that

individuals are able to approximate the mutual understanding that is necessary to acquire,

disseminate, or create new knowledge with integrity. This demonstrates the importance of themanagement of, and care for relationships in the effective management of knowledge networks

(Seufert et al., 1999).

In combination, these two models acknowledge the multi-level complexity of knowledge

management in organizations while simultaneously, identifying the common inuences among

them. Throughout this investigation these factors have been considered across four levels of

learning. The ways in which these factors interact with the levels of learning are portrayed in

Figure 4. In this instance, social contingencies, communication, and cognitive elements are

seen as permeating all levels of learning. However, again, these elements are underpinned by

affect, which is an expression of values or belief systems.

Figure 3 Model of factors inuencing the acquisition, dissemination and utilization

of knowledge

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Accordingly, these models provide a framework through which the emergent patterns within the

complexities of a knowledge network might be recognized and harnessed. The dynamic

tensions inherent in the complexities of a knowledge network give rise to uncertainty, since

order within the system is emergent rather than predictable the system's future is

unpredictable. It is the subjective state of uncertainty that gives rise to the affective states of

distrust, suspicion, threat and fear (Kramer, 1999). This emphasizes the role of affect in

knowledge networks and challenges the ways that current theories account for the acquisition

and utilization of knowledge, since this research has shown that knowledge is constructed both

socially and emotionally. This being the case, this nding has important implications for the

management of projects where disparate parties come together pursuant to a common goal.

Practical implications

To state that affect shapes the way in which individuals construct their world is in some ways a

bold step, since there is little in the literature that acknowledges the role of affect in human

reasoning. Since the days of the Stoics, affect has often been detached from deliberations

surrounding reasoning and human thought. If, as shown in this study, emotions are

underpinned by values and belief systems, then emotions are responses to the subjective

perception of value emotions become value statements. If values underpin reasoning, then

any attempt to understand the reasoning that occurs as individuals acquire knowledge must

therefore consider affect, since emotions are inextricably intertwined with reasoning.

Figure 4 Factors inuencing the acquisition and utilization of knowledge across

levels of learning

Levels of Learning

Soci

alContingencies

Co

mmunication

Cognition

Affect

Values

IndividualGroup

Organisational

Inter-organisational

Factors of Influence

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If emotions are elemental components of cognitive functioning, rather than adjunctive events,

there is strong justication to employ processes that promote emotional health or well-being in

settings such as collaborative arrangements of knowledge production. This nding has

signicant implications for the way in which control problems and politics, inherent in

organizational life, are interpreted. The political activities and control problems often observed in

policymaking or decision-making may not be signs of resistance. Rather, they may actually be

expressions of the cognitive, emotional and social difculties an individual experiences as they

attempt to come to terms with information that does not easily t with existing knowledge

structures. The results of this study show that uncertainty will arise not just as individuals

attempt to acquire information that does not assimilate easily into existing knowledge structures

it will also arise in stakeholders where they are unsure of the objectives and agendas of those

participating in collaborative ventures. Given that the dynamic tension inherent in tri-lateral

arrangements of knowledge production will give rise to uncertainty, this has signicant practical

implications for the management of cooperative research projects. Rather than seeing lack of

stakeholder engagement or commitment to a project as resistance, perhaps it is signaling the

difculties experienced as they attempt to alter existing knowledge structures. Apparent

``resistance'' may be an indication that different communication methods are required a need

for the open and honest dialogue that characterizes a learning organization.

Based on the ndings of this study, initial stakeholder engagement in collaborative research

undertakings would be best achieved through promoting the benets of involvement. Rather

than emphasize change (which brings rise to negative affective as mentioned), greateremphasis should be placed on the value-added outcomes that the knowledge network might

produce. Fundamental to the success of a collaborative research project is that all participants

develop an understanding of the values and principles that would enhance the knowledge

assets of an organization. It is difcult to adopt a learning organization approach when group

members are not aware of the principles and values underlying it. Accordingly, this should be

the starting point of the collaborative research process. This suggestion however, involves more

than intellectual acceptance of the underlying values and principles that underpin a learning

organization it even extends past relationship building and the time that must be invested to

achieve this. Participants must also develop an understanding of how they and other members

of the group negotiate their way through these values and principles and the impact this has on

relationship building they must come to understand how and why their roles might differ from

those within their originating organization. In other words, those participating in collaborative

knowledge networks would need to develop an understanding of the ways in which individualssocially and emotionally construct and interpret their worlds. This requires an appreciation of

how emotions reect individual values and belief systems. In developing a greater awareness of

their emotional states, participants in such settings would be better equipped to identify the

values underlying their thoughts (Schwarz, 1994). This would lead to deeper processing of

information which would in turn enhance the opportunity for knowledge to be acquired.

As a result of this current study a model of ``best practice'' has been developed and is currently

being tested. It is anticipated that the ndings of this investigation will be made available in the

near future. What is apparent now is that to ignore the role of emotion and values in the process

of knowledge acquisition is to ignore a key component of an individual's reasoning capacity.

Consequently, it is the skilful management of these affective states that has a profound effect on

the overall outcome and effectiveness of a knowledge network.

Conclusions

The ndings of this study contribute to the understanding of this emerging form of scientic

knowledge through collaboration by demonstrating the interrelatedness of cognitive, social,

affective and communication in uences inherent, not only in the process of knowledge

production, but also in the eventual utility of research output.

In a world where science policies are dictating greater collaboration between science, industry

and government, the ndings of this research have direct and immediate application to any

collaborative project embracing the tenets of a knowledge-based economy. The increased

understanding of the processes underlying a collaborative knowledge network that have

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eventuated through this research, give both hope and direction to a process that is applauded

and encouraged, yet greatly misunderstood (Beesley, 2003) and, it is suggested, the benets of

which have not yet even begun to be fully realized.

Note

1. Theproject under investigation in this study provided a uniqueopportunity to investigate therelationships

among knowledge creation, diffusion and utilization in a cooperative research setting. Consent to attend

all meetings relating to the project was awarded to the author with the proviso that those responsible for

comments made at meetings would not be identied, nor would organizations involved in the project be

identied if links could be made back to individuals. This condentiality agreement was minuted at each

meeting. Accordingly, no explicit reference is made to the city, organizations, or individuals involved in

the project in this paper.

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Multi-Level Complexity Inthe Management of Knowledge Networks