{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T21:41:47Z","timestamp":1770414107809,"version":"3.49.0"},"reference-count":48,"publisher":"Emerald","issue":"7","license":[{"start":{"date-parts":[[2017,8,14]],"date-time":"2017-08-14T00:00:00Z","timestamp":1502668800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IMDS"],"published-print":{"date-parts":[[2017,8,14]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>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.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>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.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>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.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>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.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/imds-09-2016-0390","type":"journal-article","created":{"date-parts":[[2017,7,3]],"date-time":"2017-07-03T19:14:42Z","timestamp":1499109282000},"page":"1521-1546","source":"Crossref","is-referenced-by-count":17,"title":["Knowledge prioritisation for ERP implementation 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