Stefan Oppl, Christian Stary, Manuel Mühlburger,
"KMS re-contextualization ? Recognizing learnings from OMIS research"
, in VINE Journal of Information and Knowledge Management Systems, Vol. 47, Nummer 3, Emerald, Seite(n) 302-318, 2017, ISSN: 2059-5891
Original Titel:
KMS re-contextualization ? Recognizing learnings from OMIS research
Sprache des Titels:
Englisch
Original Kurzfassung:
Purpose ? Deployment of knowledge management systems (KMSs) suffers from low adoption in organizational reality that is attributed to a lack of perceivable added value for people in actual work situations. Poor task/technology fit in the process of knowledge retrieval appears to be a major factor influencing this issue. Existing research indicates a lack of re-contextualizing stored information provided by KMSs in a particular situation. Existing research in the area of organizational memory information systems (OMISs) has thoroughly examined and widely discussed the topic of re-contextualization. The purpose of this paper, thus, is to examine how KMS design can benefit from OMIS research on approaches for re- contextualization in knowledge retrieval.
Design/methodology/approach ? This paper examines OMIS literature and inductively derives a categorization scheme for KMS according to their strategy of re-contextualizing knowledge. The authors have validated the scheme validated in a multiple case study that examines the differentiatory value of the scheme for approaches with various re-contextualization strategies.
Findings ? The classification scheme allows a step-by-step selection of approaches for re-contextualization of information in KMS design and development derived from OMIS research. The case study has demonstrated the applicability of the developed scheme and shows that the differentiation criteria can be applied unambiguously.
Research limitations/implications ? Because of the chosen case study approach for validation, the validation results may lack generalizability.
Sprache der Kurzfassung:
Englisch
Journal:
VINE Journal of Information and Knowledge Management Systems