Knowledge prioritisation for ERP implementation success Perspectives of clients & implementation partners in UK industries

Smith, Melanie Hudson; Jayawickrama, Uchitha; Liu, Shaofeng

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.

Citation

Smith, M. H., Jayawickrama, U., & Liu, S. (2017). Knowledge prioritisation for ERP implementation success Perspectives of clients & implementation partners in UK industries. Industrial Management and Data Systems, 117(7), 1521-1546. https://doi.org/10.1108/IMDS-09-2016-0390

• Journal Article Type: Review
• Acceptance Date: Apr 12, 2017
• Online Publication Date: Jul 3, 2017
• Publication Date: Jul 3, 2017
• Deposit Date: Apr 12, 2017
• Publicly Available Date: Jul 3, 2018
• Journal: Industrial Management and Data Systems
• Print ISSN: 0263-5577
• Publisher: Emerald
• Peer Reviewed: Peer Reviewed
• Volume: 117
• Issue: 7
• Pages: 1521-1546
• DOI: https://doi.org/10.1108/IMDS-09-2016-0390
• Public URL: https://uwe-repository.worktribe.com/output/882437
• Publisher URL: http://dx.doi.org/10.1108/IMDS-09-2016-0390