Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/61773
Title: The Development of a Conceptual Framework for Knowledge Sharing in Agile IT Projects
Contributor(s): de Castro, Rodrigo Oliveira (author); Sanin, Cesar  (author)orcid ; Levula, Andrew (author); Szczerbicki, Edward (author)
Publication Date: 2022
DOI: 10.1080/01969722.2021.2018541
Handle Link: https://hdl.handle.net/1959.11/61773
Abstract: 

Organizations must adapt their resources to meet the challenges associated with changes in the work environment in order to remain competitive in the information era. Several research findings identify knowledge sharing as a means for an organization to improve its competitiveness. Knowledge sharing can be defined in a variety of ways, but it essentially refers to the exchange of knowledge from an information giver to an information receiver. This is a purposeful activity that adds value to the client organization, particularly in IT system that employs Agile methodology. For the scope of this paper, we are going to consider only Agile knowledge transfer in IT projects that occurs in two angles: business knowledge transfers from client to consultant; and IT technical knowledge transfers from consultant to client. However, when interdisciplinary teams are involved in Agile IT projects, the knowledge transfer mentioned before remains inefficient once the knowledge loss persists throughout the project life cycle. The conversion of conceptual knowledge, which only exists in the brains and minds of individuals, into explicit knowledge is essential for organizations to gain and maintain competitive advantages over its competitor. This study proposes an alternative conceptual framework to address conceptual knowledge transfer in IT projects that use Agile methodology.

Publication Type: Journal Article
Source of Publication: Cybernetics and Systems, 53(5), p. 529-540
Publisher: Taylor & Francis Inc
Place of Publication: United States of America
ISSN: 1087-6553
0196-9722
Fields of Research (FoR) 2020: 4602 Artificial intelligence
Peer Reviewed: Yes
HERDC Category Description: C1 Refereed Article in a Scholarly Journal
Appears in Collections:Journal Article
School of Science and Technology

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