RELIABLE EVALUATION FRAMEWORKS AND METRICS FOR KNOWLEDGE MANAGEMENT SYSTEMS

Abstract

The proposed research work focuses on developing a flexible and reliable technology, with evaluation frameworks and metrics for assessing the effectiveness of any Knowledge Management System (KMS). The evaluation of KMS is a time consuming and complex process, considering the multidimensional, intangible and subjective nature of knowledge assets and KMS. Though there are many new collaboration methods and architecture models for KMS, there are very few effective quantitative evaluation models. Significant Key Performance Indicators (KPIs) are not fully established for KM Systems, though there are KPIs for software product and project management. The detailed literature survey has also confirmed the same. This research aims at the design and development of a hybrid evaluation method and multidimensional metric model. This research also illustrates the methodology of applying Weighted Arithmetic Mean (WAM), ranking and rating KM Systems along with correlation for the relationship analysis. The final part of the thesis focuses on the development of KM metrics, using three primary dimensions namely Usability, Availability and Relevance of knowledge assets, along with other pertinent supporting factors. The evaluation frameworks and metrics can help the organization to assess and report the effectiveness of KMS and knowledge sharing portals to identify the gaps. The results of the KMS evaluation will further help to archive the unused knowledge assets and also upgrade the interfaces for improving the KMS, KM portals, search engine, knowledge maps, the supporting Infrastructure and KM processes. newline