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A hybrid knowledge-based performance measurement system

Khurshid Khan M.a, Wibisono D.b

a School of Engineering, Design and Technology, University of Bradford, United Kingdom
b School of Business & Management, Institute of Technology Bandung (ITB), Indonesia

[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]This paper aims to present a hybrid knowledge based (KB) — analytic hierarchy process (AHP) — gauging absence of pre-requisite (GAP) analysis of performance measurement system (PMS) expert system (ES) model. The KBPMS has been developed using the rule base approach of ESs. Full details are given for the customer perspective (CP). The KBPMS considers five levels of company performance: business perspective, CP, manufacturing competitive priorities perspective, internal process perspective and resource and method availability perspective. CP model of the KBPMS system, and thereafter the complete model is summarised for the different modules. Embedded within the KB is the ability to benchmark the PMS existing in a company to assist in the improvement process. The validation of the hybrid KBPMS was confirmed through three real applications in the manufacturing industry sector: aircraft component manufacturing, electronics manufacturing and telecommunication products manufacturing. The results of the validation exercise indicate that the present hybrid KBPMS model is a suitable decision-making tool to assist the practitioners of PMS and provides consistent and detailed prioritised results for actions and improvements. Future research work could consider a larger sample size and cover a wider range of industry types, including services industry. This paper presents an original and novel approach (KB/ES coupled with AHP and gap analysis) to designing and benchmarking PMS in a manufacturing environment. © 2008, Emerald Group Publishing Limited[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Analytical hierarchy process,Gap analysis,Knowledge management systems,Performance management systems[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1108/14637150810864899[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]