A model to enhance performance of knowledge management systems through semantic technologies

Finding and using organizational knowledge is a significant challenge for knowledge management systems (KMS). Unprecedented growth of knowledge and its dispersal across intranet resources, makes it difficult and time-consuming for users to access important knowledge. The importance of getting the right knowledge to the right person and at the right time has been emphasized in relation to KMS performance. However, due to several technical limitations, such timely access to important knowledge is not readily available. Hence, with the advent of semantic web (SW) technologies, several studies argue that these new technologies hold a promise to overcoming the technical limitations of KMSs. Despite these arguments, there is still insufficient understanding and empirical evidence on the adequacy of SW in relation to KMS performance. Thus, the first objective of this study is to identify the key SW features that support timely knowledge access and delivery in KMS. The second objective is to propose an exploration model for the adequacy of SW in relation to the performance of KMS. The third objective is to empirically validate the exploration model. In the beginning, a comprehensive review of existing SW-based KMS models was performed, to identify and synthesize the SW features influencing KMS performance. Three key dimensions, namely semantic-oriented interface, semantic processing, and semantic-enabled database were identified, and ten important SW features synthesized. Furthermore, four concrete dimensions of KMS performance namely, knowledge quality, searchability, perceived benefit, and user satisfaction were outlined. Accordingly, conceptual model for this study was developed. Next, experts in SW and information systems were used to review and validate the conceptual model. Also, a pilot study involving 28 participants was performed to measure the reliability and validity of the research instrument. Subsequently, an empirical study was conducted to validate the conceptual model. Academicians in Malaysian public higher institutions were the target population, but the study only used data from those who had experience of using KMS. The data collected was analysed using structural equation modelling (PLS-SEM). Empirical results revealed fitness of the conceptual model to the data, while also demonstrating a significant positive role of SW features: natural language access, refinement capability, navigation capability, personalization, contextualization, knowledge reasoning, knowledge integration, knowledge filter, ontology knowledge model, and thesauri, on the performance of KMS. Conclusively, the SW technologies were found adequate in enabling satisfactory knowledge access and usage in KMS, thereby explaining its performance. Consequently, an adequacy examination model was proposed. In addition, a prototype which implements the proposed model was developed and named, semantic technology-based knowledge management system (SemTek-KMS). Next, the conduct of an expert validation study to verify the model, revealed that the prototype inhibits SW features from the proposed model that may support adequate exploitation of knowledge resources. A KMS success study was then conducted to evaluate the performance of SemTek-KMS. Result from the study revealed that SemTek-KMS was sufficient in providing adequate quality of knowledge and searchability. Also, the prototype achieved an above average perception of benefit from users, and an overall satisfaction of use.

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