27.06.2013 Views

Information and Knowledge Management using ArcGIS ModelBuilder

Information and Knowledge Management using ArcGIS ModelBuilder

Information and Knowledge Management using ArcGIS ModelBuilder

SHOW MORE
SHOW LESS

You also want an ePaper? Increase the reach of your titles

YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.

Nelly Todorova<br />

knowledge. This link between tacit <strong>and</strong> explicit knowledge implies that only individuals with sufficient<br />

common knowledge base can exchange knowledge, underst<strong>and</strong> each other <strong>and</strong> correctly interpret the<br />

exchanged knowledge. This view limits the impact of IT on knowledge sharing (Alavi <strong>and</strong> Leidner<br />

2001).<br />

Based on these main assumptions the social view concludes that knowledge sharing requires a<br />

mutual underst<strong>and</strong>ing of tacit assumptions, immersion in practice <strong>and</strong> social interaction. It places<br />

strong emphasis on management <strong>and</strong> leadership practices to support social interaction <strong>and</strong> trust.<br />

While technology can still play a role, it is focused more on connection people to people rather than<br />

people to explicit knowledge.<br />

KM strategies <strong>and</strong> initiatives<br />

Different perspectives of knowledge define different approaches to knowledge management. When<br />

knowledge is viewed as an object the focus of KM initiatives is on building knowledge stocks <strong>and</strong><br />

providing access to them. When knowledge is viewed as a process, the focus of KM is on knowledge<br />

flows <strong>and</strong> supporting the creation <strong>and</strong> sharing of knowledge. Finally, when knowledge is considered<br />

as a capability, KM initiatives aim to build competences, gain strategic advantage from know-how <strong>and</strong><br />

create intellectual capital (Alavi <strong>and</strong> Leidner, 2001).<br />

KM strategies can be divided into two main categories – personalization <strong>and</strong> codification strategies<br />

(Hansen et al 1999). Companies <strong>using</strong> the codification strategy concentrate primarily on transfer <strong>and</strong><br />

reuse of explicit knowledge. The objective is to capture <strong>and</strong> codify knowledge for broader access<br />

within the organization. Such initiatives focus on the design <strong>and</strong> use of searchable repositories of<br />

explicit knowledge <strong>using</strong> technologies such as intranets, groupware <strong>and</strong> document management<br />

systems. <strong>Knowledge</strong> repositories typically contain best practices, lessons learned from past<br />

experiences, knowledge about products, services <strong>and</strong> customers. Some companies include within<br />

their knowledge management activities projects <strong>and</strong> systems that aim to transform data into usable<br />

information through data mining <strong>and</strong> statistical analysis.<br />

Personalization strategies assume that a lot of important knowledge is tacit <strong>and</strong> the main mode of<br />

knowledge transfer is through personal interaction. KM initiatives focus on improving social processes<br />

to facilitate knowledge sharing between individuals. Some of these initiatives rely on the support of IT<br />

to bring people together. For example, organizations work on creation of corporate directories of<br />

internal expertise to connect people to the right experts within the organization; creation of knowledge<br />

networks which allow people to communicate virtually or face to face. Other initiatives may not use<br />

technology at all <strong>and</strong> concentrate on the creation of organizational culture which motivates people to<br />

share their knowledge <strong>and</strong> on providing regular social interactions between employees.<br />

Value of KM systems<br />

The studies on KM value are very fragmented. If we consider the value models from the previous<br />

sections, these studies focus on only one part of the models- outcomes, resources or capabilities in<br />

terms of enabling sharing <strong>and</strong> retrieval. It is very important to consider KM value in the context of KM,<br />

IT <strong>and</strong> other organizational resources required to derive value from KM initiatives <strong>and</strong> the paths that<br />

are taken to produce this value. Based on the review of the literature on value creation <strong>and</strong> IT<br />

business value, a preliminary model is presented to transfer some of the findings to the context of KM<br />

initiatives (Fig 3). It maps out possible resources, outcomes <strong>and</strong> capabilities.<br />

5. Conclusions<br />

<strong>Knowledge</strong> management is an emerging field which draws on theories established in different<br />

disciplines such as information systems, organizational behaviour, economics <strong>and</strong> human resources.<br />

Research in the field is fragmented as researchers represent the individual perspectives of their<br />

discipline. Current research recognizes the need for integration of these perspectives <strong>and</strong> of creating<br />

unified definitions <strong>and</strong> frameworks (Green, Stankosky, & V<strong>and</strong>ergriff, 2010; Laverne&Earl, 2006). The<br />

aim of knowledge management is to leverage knowledge as a strategic asset to gain <strong>and</strong> sustain<br />

strategic advantage <strong>and</strong> to create value for organizations. There are many different approaches to<br />

knowledge management on the continuum between strong technocratic to predominantly humanistic<br />

approaches. There is considerable variety of objectives. Based on the definition of knowledge as a<br />

480

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

Saved successfully!

Ooh no, something went wrong!