A knowledge management performance measurement system for small and medium enterprises

• Main Author: Lee, Cheng Sheng
• Format: Thesis
• Language: English
• Published: 2017
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://eprints.utm.my/id/eprint/78671/1/LeeChengShengPFKM2017.pdf; http://eprints.utm.my/id/eprint/78671/; http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:106969
• Institution: Universiti Teknologi Malaysia

An important step after the implementation of knowledge management (KM) is to evaluate its effectiveness and performance. Knowledge management performance measurement (KMPM) is necessary in order to achieve effective and successful KM. Comprehensive set of constructs and metrics for KMPM have yet to be developed. In addition, a KMPM system that applies these constructs and metrics is found lacking. It is more apparent in the case of small and medium enterprises (SMEs) as most of the studies have focused on large organizations. Furthermore, as KM is characterized by an environment subject to uncertainties and fuzziness, there is a need to adopt a specific approach to address this issue. In this research, the focus is on the development of a KMPM system for the SMEs. A novel conceptual framework that categorized KM into three main aspects; knowledge resources, KM processes, and KM factors was used as a foundation for developing the system. New set of KMPM constructs and metrics were developed and tailored for the SMEs. Investigation of the developed constructs and metrics in terms of their applicability was carried out through a questionnaire survey. The constructs and metrics were validated through statistical analysis using the Statistical Package for the Social Sciences, where reliability analysis was conducted followed by validity analysis in terms of content, construct, convergent, discriminant, and criterion validities. The analysis results indicated that the developed constructs and metrics were applicable, reliable, and valid. Following this, a fuzzy logic methodology was utilized as the evaluation mechanism for the KMPM system. MATLAB software was used to develop the fuzzy inference system and Simulink was used to design and develop the system’s layout and interface. Case studies were conducted in three small and medium sized consultancy companies to evaluate the developed system. From the evaluation, the evaluators commented that the system was comprehensive, userfriendly, and suitable for SMEs application. In essence, this research has developed new set of constructs and metrics as well as a KMPM system specifically designed for SMEs.