Web-based Learning Solutions for Communities of Practice
Web-based Learning Solutions for Communities of Practice
Web-based Learning Solutions for Communities of Practice
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A Proposed Framework <strong>for</strong> Designing Sustainable <strong>Communities</strong> <strong>for</strong> Knowledge Management Systems<br />
cally different from other in<strong>for</strong>mation systems<br />
(Alavi & Leidner, 1999). The difference between<br />
knowledge management systems and other systems<br />
such as group decision support systems<br />
(GDSS), electronic meeting systems (EMS), and<br />
expert systems lies not primarily in the technology,<br />
but in the purpose <strong>for</strong> their use. GDSS focus<br />
on connecting a particular group <strong>of</strong> employees<br />
<strong>for</strong> the goal <strong>of</strong> solving particular problems, or arriving<br />
at a decision. EMS focuses on facilitating<br />
meetings and collaborative work among a certain<br />
group <strong>of</strong> people. Expert systems are typically<br />
rule-<strong>based</strong>, where the knowledge <strong>of</strong> an expert/s<br />
(where experts are identified by the organization)<br />
is captured in the system’s knowledge base, and<br />
then queried by users. The goal <strong>of</strong> KMS, as we<br />
conceptualize them, is to connect all employees<br />
in an organization at all times. Unlike in expert<br />
systems, the roles <strong>of</strong> knowledge producers (experts)<br />
and consumers (users) are flexible. Groups<br />
are not dictated by organizational structures, but<br />
emerge ad-hoc as communities <strong>of</strong> employees<br />
with common interests and problems. Interaction<br />
within these communities may yield solutions to<br />
specific problems, but it is the interaction <strong>for</strong> the<br />
purpose <strong>of</strong> tacit knowledge exchange that is the<br />
goal <strong>of</strong> the system.<br />
Since the central problem <strong>of</strong> KM is the creation<br />
and transfer <strong>of</strong> tacit knowledge, it is necessary to<br />
look at what facilitates these processes. Experiences<br />
and contextual insights have been traditionally<br />
transferred through methods such as story-telling<br />
(Brown & Duguid, 2000), sense-making (Brown<br />
& Duguid, 1999), or through conversations in in<strong>for</strong>mal<br />
social networks. <strong>Communities</strong> <strong>of</strong> practice<br />
are in<strong>for</strong>mal networks <strong>of</strong> like-minded individuals,<br />
where the process <strong>of</strong> learning and transfer <strong>of</strong><br />
tacit knowledge is essentially social, involving<br />
a deepening process <strong>of</strong> participation (Lave &<br />
Wenger, 1991). Research shows that in the absence<br />
<strong>of</strong> decisive first-hand knowledge, an individual<br />
looks at successful decisions made by other likeminded,<br />
similarly-situated people (Nidumolu &<br />
Subramani, 2001) as filters or guides to identify<br />
potentially good choices (Hill et al., 1995). Prior<br />
case studies have shown that even <strong>for</strong> individuals<br />
armed with extensive know-what (explicit knowledge),<br />
collective know-how (tacit knowledge) can<br />
be highly significant (Brown & Duguid, 1999; Orr,<br />
1989). KM practitioners and researchers recognize<br />
the importance <strong>of</strong> communities that foster<br />
collaborative learning in organizations (Pan &<br />
Leidner, 2003) and almost all knowledge management<br />
systems have a ‘network’ component that<br />
facilitates connecting people in communities <strong>of</strong><br />
practice (Faraj & Wasko, Forthcoming). The community<br />
perspective <strong>of</strong> knowledge management,<br />
which acknowledges the importance <strong>of</strong> in<strong>for</strong>mal<br />
networks and emphasizes collaboration, started<br />
in the late 1990s (Cross et al., 2006). Evidence<br />
has shown that communities have been a key<br />
element in knowledge management systems <strong>of</strong><br />
many companies including Xerox PARC, British<br />
Petroleum Co., Shell Oil Company, Halliburton,<br />
IBM, Proctor and Gamble, and Hewlett Packard<br />
(Brown & Gray, 1995; Cohen, 2006; Cross et<br />
al., 2006; McDermott, 1999a, 1999b). Most <strong>of</strong><br />
the companies that used IBM’s first <strong>Web</strong>-<strong>based</strong><br />
knowledge management system organized their<br />
activities around communities, an element that<br />
IBM had not deliberately implemented in the<br />
system initially (McDermott, 1999b).<br />
While studying design characteristics <strong>of</strong> communities,<br />
defining what is meant by a community<br />
and its sustainability is important. In attempting<br />
to do so, we refer to prior IS literature on virtual<br />
communities, since we consider communities in<br />
knowledge management systems as virtual. The<br />
term ‘virtual’ has been used here to distinguish<br />
these communities from real-life communities<br />
with face-to-face interaction. Borrowing from<br />
biology, virtual community sustainability has<br />
been regarded as the ‘intrinsic longevity’ <strong>of</strong> the<br />
membership (e.g., Butler, 2001; Porra & Parks,<br />
2005). Hence research has been devoted to studying<br />
how members can be encouraged to stay in a