A knowledge management performance measurement system for small and medium enterprises

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...

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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
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id	my-utm-ep.78671
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spelling	my-utm-ep.786712018-08-29T07:35:47Z A knowledge management performance measurement system for small and medium enterprises 2017-01 Lee, Cheng Sheng TJ Mechanical engineering and machinery 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. 2017-01 Thesis http://eprints.utm.my/id/eprint/78671/ http://eprints.utm.my/id/eprint/78671/1/LeeChengShengPFKM2017.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:106969 phd doctoral Universiti Teknologi Malaysia, Faculty of Mechanical Engineering Faculty of Mechanical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TJ Mechanical engineering and machinery
spellingShingle	TJ Mechanical engineering and machinery Lee, Cheng Sheng A knowledge management performance measurement system for small and medium enterprises
description	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.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Lee, Cheng Sheng
author_facet	Lee, Cheng Sheng
author_sort	Lee, Cheng Sheng
title	A knowledge management performance measurement system for small and medium enterprises
title_short	A knowledge management performance measurement system for small and medium enterprises
title_full	A knowledge management performance measurement system for small and medium enterprises
title_fullStr	A knowledge management performance measurement system for small and medium enterprises
title_full_unstemmed	A knowledge management performance measurement system for small and medium enterprises
title_sort	knowledge management performance measurement system for small and medium enterprises
granting_institution	Universiti Teknologi Malaysia, Faculty of Mechanical Engineering
granting_department	Faculty of Mechanical Engineering
publishDate	2017
url	http://eprints.utm.my/id/eprint/78671/1/LeeChengShengPFKM2017.pdf
_version_	1747818042788675584

A knowledge management performance measurement system for small and medium enterprises

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