**12. References**

68 New Research on Knowledge Management Technology

The success of any KMS lies in the effective input of knowledge from all stakeholders concerned. Knowledge, which transforms itself as requirements into the KMS system, has to evidently involve proactive input from experts. These experts are those who understand the organization's processes and culture better and thus able to provide valuable and imperative input. Hence, one way of analysing this human activity occurrence serving as tacit knowledge into the KMS system is by using the Activity Theory. Since AT focuses on the interaction of human activity and consciousness within its relevant environmental context, the eventual KMS developed around these fundamentals would have an achievable and sustainable success rate of enabling employees to seamlessly access the organization's

The Delphi technique utilized in this research study involved firstly gathering opinions and knowledge from selected experts concerned. The process went through a second round that led to a re-confirmation of opinions and knowledge serving as a building block for the solutions at hand. The research concluded from the Delphi process documented above evidently shows common opinions and knowledge that were gathered from the experts. It is apparent that all experts are in agreement for a blended learning initiative with the support

By using both activity theory and Delphi technique, deep analysis can be performed within the activities of the experts and from these activities, tacit and explicit knowledge can be observed and analyzed. During the interview process, especially during the second round of interviews, when the questions were asked to the panel of experts, some of the experts realized that there existed divergent approaches exist in supervision style. Not only was the knowledge engineer able to garner further insights, the exercise also proved by an eyeopener for experts themselves which would have inadvertently increased their body of

As espoused in this research, software engineering practice generally does not amalgamate people, cultural and organizations factors when gathering requirements. Since it is imperative that KM Systems consider the aforementioned factors, AT coupled with Delphi technique was applied in this research. This approach is not only holistic but also more dynamic with thorough investigations built in to the roadmap involving people, cultural, and organization dimension. The investigations details how using AT, a knowledge engineer is able to harvest tacit knowledge allowing every situation and scenes to evolve gives them different meaning and context. In conclusion, this research espouses a combination of KM practices, AT and Delphi technique in an integrated roadmap to provide

The proposed research will shed new insights on the roadmap required to implement an effective KMS that will survive the test of time. The roadmap will ensure that KMS maps the interest of its stakeholders alike since it encapsulates their interest from the onset. The roadmap embodies an interesting fusion of people, cultural and organizational aspects

However, it must be noted that even when the aforementioned system is in place, it still does not eliminate the perennial challenge of most knowledge management systems in place

a solid foundation for requirements elicitation in developing KM system.

**10. Analysis of findings and conclusion** 

documented facts, best practices and solutions.

and involvement from all stakeholders concerned.

**11. Research outcome and limitations** 

required of a successful KMS.

knowledge.


**5** 

*Malaysia* 

**Fuzzy-Monte Carlo Simulation for Cost** 

*1,2School of Computer Sciences-Universiti Sains Malaysia,3InterNetWorks Research Group* 

Nowadays, knowledge management system is not doubtful as an important tool in an enterprise business process by reason of the effective knowledge management system can give a competitive advantage. Knowledge management system (KMS) is an information technology (IT) based system, which is developed to support and enhance the processes of knowledge creation, storage or retrieval, transfer, and application (Alavi & Leidner., 2001;Tseng, 2008). There are some benefits that can be achieved by implementing KMS such as increased employee productivity, better quality of a finished product, production and labor cost saving (M.-Y. Chen et. al, 2009; Wickhorst, 2002). Many managers know these benefits, but they are still vacillating to decide for investing KMS in their structure. This vacillation comes from consideration of budget and uncertainties or risk of economic constrained. In addition, the managers do not know how to analyze cost and benefit of KMS investment correctly. Without being able to make the analysis, managers cannot determine whether investing a KMS is worthwhile or a waste for the enterprise. Therefore, the costbenefit analysis of KMS investment is necessary in order to evaluate its attractiveness. The traditional cost-benefit analysis that always used in KMS and other enterprise information system (EIS) investment evaluation such as net present value (NPV), internal rate of return (IRR), and payback period (PB) seek to adopt a monetary unit as a basis of analysis, in which all non-monetary parameters are given monetary values (TBC, 1998; Tang and Beynon, 2005). However, it is observed in (Phillips-Wren et al., 2004) that most benefits associated with EIS like KMS are mostly intangible, which makes the use of traditional quantitative financial models heavily biased towards tangible costs and benefits. In an attempt to bridging the intangible towards tangible in the benefits related decision-making process, some enterprises analyze based on subjective judgement. This approach constantly in linguistic term contains ambiguity data that has a number of weaknesses (Uzoka, 2009) such as: inaccurate representation of the uncertainty lack of historical data, inability to understand completely and reproduce the results, poor explanation of a decision process and associated reasoning, a possibility of missing out important problem details for the evaluation, high probability of different experts producing different results without the

**1. Introduction** 

**Benefit Analysis of Knowledge** 

Ferdinand Murni Hamundu1,

*College of Arts and Sciences-Universiti Utara* 

**Management System Investment** 

Ahmad Suhaimi Baharudin2 and Rahmat Budiarto3

Uden, Lorna Department of Computing, Engineering and Technology, Staffordshire University, Beaconside, Stafford, ST18 0AD, UK E-mail: l.uden@staffs.ac.uk Activity theory for designing mobile learning
