**2.1 Costs**

72 New Research on Knowledge Management Technology

ability to decide which one is correct, difficulty in exploiting past evaluations, and the risk of

In this paper, a fuzzy rule based system is proposed to bridging the tangibles and intangible benefits of KMS investment. The fuzzy component addresses the vagueness associated with human judgement, especially of intangible parameters. Furthermore, a Monte-Carlo simulation method is used to consider the uncertainty of economic in calculating an expected net present value (NPV). The Monte Carlo simulation is a method that appropriate for estimating the impact of KMS critical factors to the financial result by randomizing value from each of the uncertain variables and calculating the objective or target value of an

This paper starts with an introduction about problem of KMS investment decision in section 1, and then followed by discussion about cost and benefit of KMS investment, related works in cost-benefit analysis of KMS investment, and including the Fuzzy-Monte Carlo simulation as the proposed approach for this paper in section 2. Section 3 provides a framework for cost benefit analysis of KMS investment. The real life problem that the authors dealt with and intangible benefit analysis due to this problem are introduced in Sections 4 and 5, respectively. Section 6 provides a mathematical model of cost-benefit impact to KMS investment. In Section 7, the results of the Monte-Carlo simulation are analyzed and discussed. Finally, Section 8 presents the conclusions and outlines for further

As managers became aware that the power of knowledge is the most valuable strategic resource, knowledge management (KM) became widely recognized as essential for the success or failure of enterprises. Consequently, over the past 20 years, KM has progressed from an emergent concept to an important factor in sustainable competitive advantage of business (Wagner et al., 2011). According to one estimate, 81% of the leading organizations in Europe and the U.S. are utilizing some form of KM (Grossman, 2006). Knowledge is based on data and information. Data represents the raw facts without meaning; information symbolized to what is obtained when data is organized in a meaningful context, while knowledge is characterized as the meaningfully organized accumulation of information (Zack, 1999). Nonaka (1994) points out that there are two different types of knowledge in an organization: explicit and tacit knowledge. Explicit knowledge is formal and systemic, while tacit knowledge is highly personal and difficult to formalize. These two types of knowledge are both essential to the organization and must be captured and shared for others to benefit.

Thus, knowledge in the organization should be managed properly and carefully.

The KMS refers to the set of processes or practice to develop the ability of an employee in creating, acquiring, capturing, storing, maintaining and disseminating the enterprise's knowledge (Hamundu & Budiarto, 2010). Many companies are building KMS to manage their organizational learning and business "know-how". For instance, a software engineer is able to know immediately the algorithm of a security system in prior software development. Sharing this information organization widely can lead to more effective security design, and it could also lead to ideas for new or improved software. Indeed, the ability to perform all functions of KMS depends on the information technology (IT) role. Facing a tremendous amount of data on a daily basis, enterprises only use IT to integrate each division of various tools, such as intranet, data warehouse, electronic whiteboard, artificial intelligence and

producing meaningless or highly faulty results.

investment model.

research.

**2. Literature review** 

The first step of cost-benefit analysis for a KMS investment is to determine the costs. On the surface, this may seem deceptively simple, but there are costs involved in a knowledge management investment that may not be readily obvious to the manager. In fact, investment cost of EIS likes KMS is a common factor influencing the purchaser to choose the EIS (Davis & Williams, 1994). Obviously, the project will incur the cost of whatever EIS to be used. This can range from free, to nearly free, to several thousand dollars for an EIS. In addition, any technical infrastructure for the EIS that is needed will also have to be counted in the costs.

Investment costs of KMS include, but are not limited to the costs of software, hardware, incentive programs, implementing and maintaining. Technically, these costs can be grouped under two major criteria, namely, capital expenditures and operating expenditures (Ngai & Chan, 2005). Capital expenditures are the non-recurring costs involved in setting up the KMS such as product costs (the basic cost of the KM tool), license costs (the cost of the KM tools in terms of number of users) and training costs. Operating expenditures are the recurring costs involved in operating the KMS, which include maintenance costs and software subscription costs (the annual, pre-paid cost of upgrading the product to a major software release when it is launched).
