Proceedings of the 12th European Conference on Knowledge ...

Max Erik Rohde and David Sundaram
While knowledge undeniably requires <strong>the</strong> consideration <strong>of</strong> complex and multidimensional
contexts, a negligence <strong>of</strong> any ‘material’ manifestations results in an underutilization <strong>of</strong> <strong>the</strong>
potential capabilities <strong>of</strong> information systems (Orlikowski 2006).
Although static knowledge repositories <strong>of</strong>ten find little adoption and use, <strong>the</strong>ir potential benefits for
organizations are still substantial. The search engine Google, for instance, provides access to <strong>the</strong>
more or less static repository <strong>of</strong> information accessible through <strong>the</strong> World Wide Web; a repository
<strong>of</strong> significant usefulness for many knowledge-intensive activities.
Both <strong>the</strong> individual knowledge worker as well as <strong>the</strong> coordination <strong>of</strong> groups have been identified
as important sources <strong>of</strong> knowledge capability. However, few approaches investigate how <strong>the</strong>
‘personal knowledge management’ <strong>of</strong> individuals can be linked with coordinating mechanisms to
enable collective capabilities.
While technological mechanisms might be difficult to adapt to <strong>the</strong> complexity <strong>of</strong> knowledge work,
using systems primarily as means to establish and manage social networks might not do justice to
<strong>the</strong>ir full potential. For instance, many knowledge workers spent a significant amount <strong>of</strong> <strong>the</strong>ir time
working with technologies such as email, word processors or web browsers.
These problems motivate <strong>the</strong> objective <strong>of</strong> this research: How can information-intensive systems be
designed which (1) appreciate both <strong>the</strong> tacit context and material manifestations <strong>of</strong> organizational
knowledge, (2) account for <strong>the</strong> dynamic and static dimension <strong>of</strong> knowledge, and (3) link <strong>the</strong> work <strong>of</strong>
individuals with work <strong>of</strong> groups.
3. Methodology
In order to approach <strong>the</strong> objective mentioned in <strong>the</strong> previous section, a multi-methodological system
development approach based on Nunamaker, Chen and Purdin (1991) is adopted. This approach
defines <strong>the</strong> interdependent and non-sequential phases <strong>of</strong> observation, <strong>the</strong>ory building, system
development and experimentation. For <strong>the</strong> initial phase <strong>of</strong> observation, case studies and fur<strong>the</strong>r
academic studies have been consulted to understand contemporary perspectives on <strong>the</strong> problem
area (Section 2). Fur<strong>the</strong>rmore, current technological approaches have been observed through fur<strong>the</strong>r
academic sources and various industry blogs (Section 3). Web resources for each possible
technology have been recorded and categorized using <strong>the</strong> tool diigo.com. Theory building is
conducted through a syn<strong>the</strong>sis <strong>of</strong> claims in <strong>the</strong> literature into implementable guidelines (Section 4).
For <strong>the</strong> phase <strong>of</strong> system development, a s<strong>of</strong>tware prototype has been implemented (Section 5). The
process <strong>of</strong> system development has been extensively documented in source code management
systems, handwritten notes and blog posts. For <strong>the</strong> phase <strong>of</strong> experimentation, <strong>the</strong> behavior <strong>of</strong> <strong>the</strong>
prototype has been constantly verified using an automated test framework. At <strong>the</strong> current stage <strong>of</strong>
development, <strong>the</strong> important ‘last mile’ (Winter 2010) <strong>of</strong> deployment <strong>of</strong> <strong>the</strong> prototype to end users has
not been reached; however, <strong>the</strong> prototype is designed using industry-standard practices and
technologies with a clear intention to disseminate later iterations to possible end users.
4. Guidelines for designing information intensive knowledge support systems
Researchers and practitioners attempting to design systems to facilitate sustained knowledge
capability can build on a rich foundation provided in <strong>the</strong> organizational, knowledge management and
information systems literature in some measure discussed in <strong>the</strong> previous sections. However, few
studies explicitly address all four abovementioned problems. Based on our discussions <strong>of</strong>
perspectives on sustained knowledge capability and technological approaches to enhance
knowledge-related performances, a number <strong>of</strong> guidelines for designing information intensive
knowledge support systems is syn<strong>the</strong>sized. Each <strong>of</strong> <strong>the</strong>se guidelines is aligned to address one <strong>of</strong> <strong>the</strong>
problems mentioned in <strong>the</strong> previous section.
Design Guideline 1: Connect versatile contexts through information
Knowledge is both seen in an objectivist fashion as well as uniquely bound to complex contexts.
Systems handling knowledge as an object have lead to unarguably useful applications, such as <strong>the</strong>
Google search engine, which is part <strong>of</strong> <strong>the</strong> essential repertoire <strong>of</strong> many knowledge workers. However,
<strong>the</strong> negligence <strong>of</strong> important contextual information has led to <strong>the</strong> failure <strong>of</strong> many organizational
knowledge management systems. The first guideline proposes that systems should focus on
connecting invariably tacit and versatile contexts through necessarily explicit information. In that,
designers should acknowledge that information systems ultimately cannot process knowledge but
only link contexts separated by space and time through information. Many successful knowledge
management applications are built upon this principle. For instance, emails can be <strong>the</strong> link between
852