Application of Multi-Dimensional Metric Model, Database, and WAM for KM System Evaluation

A Knowledge Management (KM) System plays a crucial role in every industry as well as in Higher Learning Institutions. Based on the earlier research works, the authors have identified the gaps, and challenges in order to develop a comprehensive KM System framework, Hybrid Evaluation method which are helpful to assess any given KM system. The primary goal of this research paper is to propose the methodology for ranking and rating of the KM system using Multi-dimensional Metric Model, Metric Database and Weighted Arithmetic Mean (WAM) method. This paper first provides the background for KM System Technology Framework and then enlists some of the significant research works, carried out in the past two decades especially on the KM Success Factors and Models, which support and validate their success. Secondly, this paper describes and illustrates how a Multi-dimensional Metric Model and Metric Database can be formed. Finally, this paper discusses how the KM Systems are evaluated and ranked for their effectiveness through the proposed evaluation methodology. DOI: 10.4018/jkm.2012100101 2 International Journal of Knowledge Management, 8(4), 1-21, October-December 2012 Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. processes, practices, and norms. Knowledge is viewed as a justification of personal belief that increases an individual’s capacity to take certain action. Knowledge resides in the user and not in the collection of information as quoted by Churchman (1971). Alavi and Leider (1999) defines Knowledge management (KM) as a process for systematically acquiring, organizing, and communicating knowledge of employees so that other employees may make use of it to be more effective and productive in their work. Knowledge Management (KM) and Knowledge Engineering (KE) have become very important concepts in recent years. KE is an information technology configuration control management tool used to exploit intellectual and technology assets for the benefit of the organization. KE can also be defined as the aspect of systems engineering which addresses uncertain process requirements by emphasizing the acquisition of knowledge about a process, product or technology, and representing this knowledge in a Knowledge-Based System. Knowledge Management (KM) comprises a range of practices used by organizations for reuse, awareness and learning. KM also aims to provide an innovative methodology for creating and modifying to promote knowledge creation and sharing. Subramanian and Geetha (2011), pointed out that the underlying psychological, cultural, social, security and economical issues that are considered to be important when thinking about Knowledge Sharing and Knowledge Management. Knowledge Management System (KMS), defined by Alavi and Leidner (2001), as an ITbased system developed to support and enhance the processes of knowledge creation, storage/ retrieval, transfer and application. The KM framework further advanced by Van der Spek and Spijkervet (1997) identifies a cycle of four KM stages. Fennessy (2002) avers that, the roles, values and norms of the knowledge workers will cause an impact on the development and implementation of any solution that is arrived at by the organization. There are different architectures and techniques have been proposed to design and implement KMS. Some of the techniques which are found to be useful are, Intelligent Agents based system proposed by Van Elst, Dignum, and Abecker (2003), multi-agentbased architecture developed by Gandon (2000) and KMS technology Framework proposed by Subramanian and Geetha (2011). Maier (2002) indicates that IT solution will not be suitable for all KM initiatives and hence expands the supporting enabler as ICT system that supported the functions of knowledge creation, construction, identification, capturing, acquisition, selection, valuation, organization, linking, structuring, formalization, visualization, distribution, retention, maintenance, refinement, evolution, access, search, and application. Jennex and Olfman (2003) further enriched and extended the definition by incorporating the Organizational Memory System into the KM System, and adding strategy and service components to the KMS. The Technology Acceptance Model (TAM) is an information systems theory that models how users come to accept and use a technology. The model suggests that when users are presented with a new technology, a number of factors influence their decision about how and when they will use it, notably, Perceived usefulness (PU) and perceived ease-of-use (PEOU). These factors would be also applied for KM Systems evaluation. There are many benefits with a well designed KM System and Knowledge Management Portal, which includes time savings, cost savings and extended knowledge base for improving technical issues handling with products, projects and processes inside the organization. So, KM system should also deal with all the concerned products, projects and processes knowledge apart from functional or technical domain specific knowledge assets. According to the current trend in Industries, it is believed that KMS is the supporting power of any organization. One of the key challenges with the KMS is the evaluation of knowledge available within the organization and assessing the capabilities and effectiveness of the KMS infrastructure as found by Jennex (2008) and Subramanian and Geetha (2011). Measurement is the assignment 19 more pages are available in the full version of this document, which may be purchased using the "Add to Cart" button on the product's webpage: www.igi-global.com/article/application-multi-dimensionalmetric-model/75164?camid=4v1 This title is available in InfoSci-Journals, InfoSci-Journal Disciplines Library Science, Information Studies, and Education. Recommend this product to your librarian: www.igi-global.com/e-resources/libraryrecommendation/?id=2