This extended abstract facilitates a discussion on the issues entailing the accuracy of information retrieval (IR) from knowledge management systems (KMS). This dissertation will be taking a multi-method approach in its investigation. First, an empirical examination of keyword usage from a representative IS research journal is performed to validate the need for this research. Second, a case study is underway with the Intel Corporation, on their satisfaction with the quality of their information retrieval capabilities. Lastly, a laboratory experiment is proposed to test the informational retrieval accuracy of two types of knowledge management system infrastructure – traditional relational-based and multidimensional-based KMS. Theories developed in cognitive psychology suggest that the hierarchical nature of multidimensional systems, through its aggregation capabilities and tree-like structures, generate more accurate information, faster, and provide more closely related information to the knowledge worker. This leads to directional hypotheses that can be tested in an experiment. The results of these hypotheses have implications for knowledge management systems design. It is posited that KMS that are properly designed with more accurate information retrieval mechanisms (I.e. Multidimensional technologies) will reduce organizational costs, in time and effort, by decreasing the wasted time spent investigating information that does not support the current knowledge requirements of the user.
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