ORCID

Abstract

Purpose - Knowledge management is crucial for enterprise resource planning (ERP) systems implementation in real industrial environments, but this is a highly demanding task. The purpose of this paper is to examine the effectiveness of knowledge identification, categorisation and prioritisation that contributes to achieving ERP implementation success. Design/methodology/approach - This study adopts a mixed methods approach; a qualitative phase to identify and categorise knowledge types and sub-Types; conducting in-depth interviews with ERP clients and implementation partners; plus a quantitative phase to prioritise knowledge types and sub-Types based on their contribution to achieving ERP success for business performance improvement. An analytic hierarchy process-based questionnaire was used to collect empirical data for the quantitative phase. Findings - This study has been able to identify, categorise and rank various types of ERP-related knowledge based on in-depth interviews and survey responses from both ERP clients and implementation partners. In total, 4 knowledge types and 21 sub-Types were ranked based on their contribution to achieving ERP success; 4 variables of information quality, systems quality, individual impact and organisational impact were used to measure ERP success. Originality/value - The empirical findings demonstrate exactly what kinds of knowledge need to be managed, enabling knowledge prioritisation when a client organisation or an implementation partner steps into an ERP implementation, in a real industrial environment.

Publication Date

2017-07-03

Publication Title

Industrial Management and Data Systems

Volume

117

Issue

7

ISSN

0263-5577

Embargo Period

2018-07-03

Keywords

AHP, Enterprise resource planning, ERP implementation, Knowledge categorization, Knowledge identification, Knowledge prioritization

First Page

1521

Last Page

1546

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