Knowledge has emerged as the most strategically significant resource of an organisation, and not surprisingly, knowledge management (KM) is gaining attention in the academic arena as well as in the practice community. Here, we define KM as the creation, sharing and application of knowledge in a knowledge enterprise. Competitive firms can be seen as generators and transformers of different kinds of knowledge. As firms increasingly compete with a different stock of knowledge, management of the firm’s knowledge base has emerged as a major challenge in maintaining the firm’s sustainable competitive advantage.

Knowledge Reuse

Knowledge management involves the management of knowledge processes which are often categorised by whether they involve knowledge creation or knowledge reuse. Knowledge creation is typically viewed as somehow more important than knowledge reuse, more difficult to manage, and less amenable to information technology support. However, in reality, organisations are as much concerned about the reuse of knowledge since productivity benefits can be derived from leveraging existing experience and avoiding duplication of solutions. Given that knowledge reuse is a key organisational concern, it is necessary to understand the factors behind reuse success. The purpose of this research is therefore to develop a framework to explain how successful knowledge reuse can take place within an organisation. In particular, we apply the framework to investigate the reuse of knowledge in the context of information systems development. While the software engineering literature has extensively covered software code reuse, relatively little attention has been devoted to the reuse of overall software project knowledge. The framework can serve to elucidate the individual, process and technology factors behind successful reuse of information systems development knowledge.

Secure Knowledge Management

Knowledge Management and Data Mining

Methods that have been developed for data mining could be used to capture, select and refine individual knowledge into collective organisational knowledge. Traditional knowledge management methodologies have primarily focused on knowledge acquisition from individuals. The approach to building a knowledge management system is often a manual process which requires considerable efforts. It commonly involves lengthy interviews, domain ontologies readjustments and rules rewriting in consultation with domain experts. On the other hand, machine learning algorithms used in data mining search for valuable but hidden knowledge in databases. These algorithms are meant to alleviate difficulties in capturing and summarising useful knowledge from different sources. While the algorithms may be effective in analysing data in large databases and uncovering trends and patterns, they have largely been applied to structured databases governed by well-defined domain theories. Techniques such as the decision tree and the neural network method can be used to build knowledge management systems faster and more effectively. The knowledge captured by such systems can be formalised and documented in knowledge repositories, and eventually, shared by all.

Cross Cultural Study on Behavioural Intention Formation in Knowledge Sharing

Here, we investigate why many organisations face difficulties in deploying knowledge sharing practices across countries. We examine the motivational factors of different individuals, and how these factors influence knowledge sharing intention in two different cultures: oriental (China) versus western (Sweden).

Managing Multiple Identities in Organisation-wide Knowledge Management

A common but important issue with large Information Technology (IT) organisations that implement KM strategies is end-user apathy and indifference towards the KM initiative in organisational units. End-user communities associate themselves minimally with the organisation-wide KM apparatus, rarely contributing to the initiative, or/and in a few cases, completely dissociating themselves from the KM initiative. Here, we analyse the qualitative data collected from an indepth case study of the KM implementation at three of India’s largest IT organisations through the lens of the Social Identity Theory (SIT). Evidence from the case points to the dominance of multiple social identities; the enactments of these identities in everyday organisational life in the KM context are manifest. Preliminary findings from the cases suggest that evoking organisational identities in end-user communities in the context of sharing and contributing to the KM apparatus is an important challenge facing organisational KM strategies.

The faculty members involved in knowledge management research are:

• KANKANHALLI Atreyi
• PAN Shan Ling
• POO Chiang Choon, Danny
• SETIONO Rudy