02.12.2012 Views

Web-based Learning Solutions for Communities of Practice

Web-based Learning Solutions for Communities of Practice

Web-based Learning Solutions for Communities of Practice

SHOW MORE
SHOW LESS

Create successful ePaper yourself

Turn your PDF publications into a flip-book with our unique Google optimized e-Paper software.

214<br />

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

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!