next generation knowledge networks project proposal

8/9/2019 Next Generation Knowledge Networks Project Proposal

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NEXT GENERATION KNOWLEDGE NETWORKS: A DESIGN

SCIENCE PROJECT

Abstract

Networks are employed as powerful conceptualization of many aspects of organizations. Some

examples are networks of information or social networks. However, there are few tools available

which provide organizations with an integrated environment in which networks can be understood,

navigated, authored and composed. Moreover, research tends to consider networks in the

organizational context independently but not simultaneously and in an integrated fashion. This

research aspires to deliver a novel conceptualization of knowledge as a network in the organizational

context, which integrates multiple knowledge perspectives. A multi-methodological approach is

adopted, which involves the design and evaluation of chains of interrelated artefacts. This PhDresearch approximates the completion of its first year. Any feedback will be most valuable to set the

right directions for the remaining years of the study.

Next Generation Knowledge Networks Working Paper, March 2010, Max Rohde

http://nexnet.wordpress.com/


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1 INTRODUCTIONOrganizations nowadays are becoming increasingly complex systems. The complexity of

organizational knowledge hinders the theoretical enquiry into the deep structures which might governthese organizations. Networks have been found to be a powerful conceptualization for many aspects of

the physical and social world (Barabasi, 2003). Networks can potentially be a powerful vehicle in

understanding organizational knowledge better and can support organizations in their work with

unstructured information.

However, it cannot be claimed that we have one lens, which allows us to understand the knowledge of

an organization as one integrated network. Most network conceptualizations focus on a specific aspect

of organizational knowledge, such as encoded semantic information in a semantic web or the network

structure of a group of organizations sharing their knowledge and supply chains (Dyer & Nobeoka,

2000). Moreover, organizations seldom think in or work with networks. There are few management

frameworks, which have an underlying understanding of knowledge as a network. Furthermore, there

are very few software tools, which would allow organizations to navigate or compose their

information as a network.

We see a next generation knowledge network as integrating multiple organizational networks to a

degree, which allows organizations to work with key information in a network fashion. This involves

the navigation, composition and management of these networks in an integrated environment. A tool,

which could support next generation knowledge networks, could provide interesting insights into the

structure and nature of organizational knowledge.

In the following, we will first provide a brief review of the literature, introducing knowledge as

multidimensional and context-embedded construct. We then provide some examples of network

conceptualizations, which account for individual aspects of organizational knowledge. Based on this

brief literature review, we discuss our research motivation. This motivation leads to the discussion of

our research design.

2 KNOWLEDGE AS MULTIDIMENSIONAL AND CONTEXT-EMBEDDED

Organizations as a whole have a set of socially constructed knowledge capabilities, which differentiate

them from their competitors . Different kinds of knowledge capabilities have been identified in the

organizational literature (Blackler, 1995): (1) Encoded knowledge is the kind of knowledge

traditionally dealt with in the domains of artificial intelligence and knowledge representation: this

knowledge can be broken down to a distinct set of facts or statements, which can be represented in a

symbolic form, for instance databases or knowledge bases. (2) Embrained knowledge refers to

knowledge that is applied by individuals in a conscious and analytical fashion. (3) Embodied

knowledge, in contrast, is knowledge individuals apply in an intuitive way, without being explicitlyaware of what exact knowledge they apply or posses. Many managers say they based their best

decisions on intuition without being able to name what knowledge or skills they have applied (Simon,

1987). (4) Embedded knowledge refers to knowledge implicitly existent in organizational routines,

structures, and resources, which has not been explicitly formalized. (5) Encultured knowledge is a

very tacit form of knowledge, expressed in shared beliefs or understandings of groups. This a very

helpful classification of the different kinds of organizational knowledge capabilities which shows that,

when investigating organizational knowledge, far more needs to be considered than what can be

explicitly encoded in knowledge bases or knowledge repositories. In fact, only one aspect of

organizational knowledge, encoded knowledge, can be explicitly encoded while all the other kinds of

knowledge identified by Blackler are tacit and cannot be brought into a firm representation.


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Furthermore, it is argued that knowledge must not be seen apart from the context of its application

(Thompson & Walsham, 2004). Thompson and Walsham argue that each of Blacklers knowledge

types, encoded, embrained, embodied, embedded, and encultured, is to be seen as contextual

component. These components are applied in a certain context, and the experiences, which are made in

due course, again become contextual components being applied in a different context. The important

implication of this perspective is that there is no such thing as static knowledge, which lies as silent

capability inside an organization; knowledge is always to be seen relative to its application in a certain

context. Orlikowski (2002) provides a related perspective of organizational knowledge, introducing

knowing as dynamic, a distributed organizational capability that emerges from individual actions in

certain situations. These perspectives on knowledge and its application highlight that the formalization

and representation of knowledge must never be seen apart from its application. It is not advisable to

engage with knowledge solely from a static perspective, but only in combination with a dynamic

perspective, which is rooted in the application of this knowledge. Related notions can be found in the

organizational literature, where it is claimed that organizational routines should never be seen as static

but always as adapted to the context of their application (Feldman & Pentland, 2003). In fact, the

standard way of conducting a routine, is supposed to never be found in the real execution where the

complex environment forces organisations to adapt in every instantiation of a routine (Levinthal &Rerup, 2006).

3 NETWORKS IN THE ORGANIZATIONAL CONTEXTHaving provided a general perspective on organizational knowledge in the previous section, we now

want to give a brief introduction into the importance of networks for organizational knowledge.

Investigating, conceptualizing and designing complex reality based on networks has led to many

theoretical insights (Barabasi, 2003; Granovetter, 1973; Nagurney & Dong, 2002) and powerful

practical applications such as the World Wide Web, the semantic web and social networking software.

Two examples of networks, which are important for organizational knowledge, are social networks

and information networks.

Social networks in organization are found to be an important carrier of knowledge. Rich human

interactions allow effective sharing of information (Orlikowski, 2002). A lack of social interaction

between departments or affiliated companies can result in severe knowledge management problems

(Thompson & Walsham, 2004). The direct social link between individuals is further said to be an

important vehicle to share knowledge in a business network (Dyer & Nobeoka, 2000; Swan, Newell,

Scarbrough, & Hislop, 1999). Information networks are often used to encode organizational

knowledge. Corporate intranets are often employed for the purpose of knowledge management

(Ruggles, 1998) and are usually based on interlinked websites. Naturally, organizations also interact

with the World Wide Web as a source, sharing and publishing platform for their knowledge. Many

organizational models and knowledge models are organized as networks (Geoffrion, 1987;

Mylopoulos, 1981; Studer, Benjamins, & Fensel, 1998).

Doubtlessly there are numerous further examples of social networks and information networks, which

are relevant in the context of organizational information. Moreover, other forms of networks can cover

important aspects of organizational knowledge, such as process-networks (Brendel, Friedler, & Fan,

2000; Friedler, Fan, & Imreh, 1998) or decision networks (Langley, Mintzberg, Pitcher, Posada, &

Saint-Macary, 1995; Wellman, Breese, & Goldman, 1992).

4 RESEARCH MOTIVATIONWe see a very imminent practical problem for organizations in a lack of tools to work with

information networks. Though these networks exist implicitly in all organizations, there is no

integrated environment, in which these networks could be navigated, authored and managed. One

important factor for this is that the information network in organizations is conceptually, logically and


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physically divided. One divide can be seen between the networks of individuals and the organization.

Most personal information is carefully stored away on desktop computers in various files and folders

(Henderson, 2005), which are often not accessible by the organization (Ducheneaut & Bellotti, 2001).

Another divide is between structured and unstructured information. It is, for instance, difficult to link

the transactional information in ERP systems with unstructured information, which may reside in

emails or chat clients. Heterogeneous systems pose another challenge, where various standards and

systems prevent information from being interlinked (Joo & Lee, 2009). Table 1 shows an overview of

these divides.

Information Network Divides

Individual Organisation

Structured Unstructured

Heterogeneous Systems

Table 1. Information Network Divides

Furthermore, information networks are often not well-aligned with other organizational networks. For

instance, knowledge management activities are often perceived as interfering with the normal work practices (Kwan & Balasubramanian, 2003), indicating that the information networks in knowledge

management systems are not aligned with the process network of organizations

There is significant literature, which is concerned about the integration of heterogeneous information

networks (Allemang & Hendler, 2008; Stein, 2003). However, this literature often fails to recognize

that information networks are only one part of the complex organizational reality. In the literature that

does recognize that knowledge is a multidimensional and context-embedded construct, on the other

hand, little focus is often set on encoded information networks. Therefore, our study aspires to

investigate how information networks can be integrated and aligned with networks relating to more

tacit aspects of organizational knowledge, for instance social networks. Our research questions can be

formulated as:

How can multiple network conceptualizations of different aspects of organizational knowledge beintegrated into one conceptualization?

5 RESEARCH DESIGN5.1 Philosophical AssumptionsOur epistemological assumption is that the nature of knowledge is relative to its degrees of freedom.

Social theories, though they might be grounded in rigorous studies, exhibit high degrees of freedom,

implying that another theory could be equally true. Measurement of physical phenomena is subject

to fewer degrees of freedom. These different levels of abstraction interact with each other and validate

one another. This belief is grounded on general systems theory (Boulding, 1956) and, partly, multi-

level research (Kozlowski & Klein, 2000).

Following Simon (1996), we follow the mode of enquiry linked to the introduction of new artefacts.

Reflecting on and observing the process of creation and the reaction of the world to the artefacts can

lead to new insights (Gregg, Kulkarni, & Vinz, 2001; Iivari, 2007; Purao, 2002). However, the

central concepts of the science of the artificial (Simon, 1996) combined with the notion of knowledge

in multiple degrees of freedom leads us to unique challenges. Artefacts can be proposed on different

levels of abstraction (Hevner, March, Jinsoo, & Ram, 2004; March & Smith, 1995). We believe that

chains of artefacts can be used to validate one another, if their central characteristics and design

processes are interrelated and interwoven. The design process thereby itself carries an inherent notion

of validation (Newell & Simon, 1976; Rapp, 1981). Figure 1 summarizes important aspects of our

philosophical assumptions by illustrating degrees of freedom in relation to different philosophical

perspectives.


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Figure 1. Degrees of freedom and philosophical assumptions

5.2 Research MethodThis research follows a multi-methodological approach based on Nunamaker, Chen and Prudins

(1991) work. Design science must address a problem, which is practically relevant (Hevner et al.,2004). The solution itself (Nunamaker et al., 1991), the process leading to the solution (Hevner et al.,

2004), or the experiences made during the process (Nunamaker et al., 1991) should possibly make a

contribution to the body of knowledge in information systems. As we have argued under section 4, our

research question has theoretical as well as practical implications and is therefore well-suited to be

investigated with design science research.

Our research question suggests that a theory is the primary artefact, which is to be designed. Theories

are valid artefacts in the context of design science research (Purao, 2002). Our philosophical

assumptions impose, however, that a sole investigation of a theory as primary artefact is problematic,

with theories being subject to many degrees of freedom. Thereby, in difference to what is often

assumed in design science research, that the output of the research is one single artefact (Hevner et al.,

2004; Peffers, Tuunanen, Rothenberger, & Chatterjee, 2008), our research design is aimed at the

creation of an artefact chain.

Following March and Smith, (March & Smith, 1995) artefacts can be constructs, models, methods and

instantiations. The practical problem we are seeking to address proposes that the instantiation is a

software artefact. Naturally, a higher level artefact, which is interrelated with a software

implementation, is a software architecture. These, in turn, can be related to a framework as further

higher-level artefact. Frameworks can be informed by theories. A general framework, which is

employed in the domain of soft system methodology is the V model (Sheffield, 2005). Following this

model, we illustrate the artefacts on different levels of abstraction in figure 2.

Figure 2. Artefacts and degrees of freedom


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5.3 Research ProcessIn a slight adoption of Nunamakers framework, we see our research process as governed by three

modes of activity, namely design, evaluation and realignment. The research process is always initiated

by observation, which leads to the research motivation and formulation of research problems and

issues. In the activity ofdesign, central characteristics from higher level artefacts are used to drive the

objectives and creation of lower level artefacts. The lower level artefacts, in turn, are evaluatedagainst

the objectives set forth by the higher level. The possible results of the research depend on the

evaluation. In case the researcher finds the design artefacts unsatisfactory in the light of the higher

level requirements, the research process must be realigned, involving the redesign of the artefacts

(Peffers et al., 2008). Possible reiterations resolve in loops similar to the research process proposed by

Purao (2002). Figure 3 illustrates these three activities and shows one possible process, in which the

research can be conducted.

Figure 3. Research method overview

5.4 EvaluationA very critical step in design science research for the generation of valid theoretical results is the

evaluation. Artefacts should be evaluated using rigorous scientific methods (Hevner et al., 2004;

Nunamaker et al., 1991; Peffers et al., 2008). The focus of our research is on altering reality by

introducing new artefacts (Simon, 1996) the process of evaluation must be directly aligned to the

nature of the proposed artefacts.

As central component of our methodology we aim at designing artefact chains spanning multiple

levels of abstraction. Preference for either qualitative or quantitative methods dominates many fields

of research. We see this as directly linked to the level of abstraction a field usually deals with.

Consequently, different levels of abstraction propose different methods of scientific enquiry. Forinstance, hard sciences prefer quantitative methods, whereas soft sciences often employ qualitative

methods. Furthermore, we understand that the more degrees of freedom an artefact has, the more it is

subject to the interpretation of the researcher, requiring an interpretative rather than positivist

perspective. Figure 4 illustrates the relationship between qualitative/quantitative methods,

philosophical perspective and degrees of freedom.


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Figure 4. Qualitative/Quantitative Research Methods

Based on what Figure 4 proposed, we seek to investigate our different artefact using the following

methods:

Artefact Method/Data collection Data Analysis

Usage logs and user data Statistical and network analysisSoftwareImplementation Implementation based on existing

frameworks, based on rigorous

software development

methodologies; record development

progress using versioning systems

Implementation in itself an experiment (Newell

& Simon, 1976)

Demonstration by proof-of-conceptimplementation

Evaluate prototype with explicit list of

architectural requirements (Sheffield, 2005)

Software

Architecture

Survey of related software toolsusing whitepapers, web resources,

research and industry journals

Simple thematic analysis

Illustration by software architectureand implementation Evaluate prototype and architecture againstexplicit list of requirement derived from theframework (Sheffield, 2005)

ConceptualFramework

Delphi study with domain experts Qualitative analysisIllustration by conceptual

framework, architecture and

implementation as well as design

process

Analysis of the design process and findings as a

whole using hermeneutics (Klein & Myers,

1999; Purao, 2002).

Theory

Scientific review process andconference presentations

Table 2. Methods employed for evaluating the artefacts

Although each one of the employed methods for evaluation will be performed with commitment to

academic rigour, we do not understand any individual investigation as carrying our main contribution.

Our contribution is supported by the tight integration of the artefact chain and a rigours and

transparent design process, which builds on existing theories, frameworks, and software artefacts.

6 CONCLUSIONKnowledge is an inherently complex construct. Arriving at sound knowledge conceptualizations is

hindered by this complexity. In our research, we aspire to discover through design (Baskerville, 2008)

a new conceptualization of knowledge as knowledge networks of a next generation. We take a slightly

different approach to design science by focussing on the design and evaluation of artefact chains,

rather than on one central artefact.


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The research so far has developed initial versions of all major artefacts theory, framework, architecture

and implementation. Discussions of the theory, framework and architecture have been published in

peer-reviewed venues, whereby the research can rely on a sound theoretical basis to engage in a

second design iteration. A prototype has been implemented in Java and provides core functionality to

support central requirements of the higher level artefacts. However, the limited space in this article

prevents us from discussing the proposed artefacts in greater detail.

As this PhD research has not yet completed its first year, feedback on the adopted methodology as

well as on the initial artefacts will be most helpful for the further progress of this project.

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