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Does it Matter the Loss of Tacit Knowledge in IT Outsourcing? A Study in a Swedish Governmental Agency
Stockholms universitet, Samhällsvetenskapliga fakulteten, Institutionen för data- och systemvetenskap.
Stockholms universitet, Samhällsvetenskapliga fakulteten, Institutionen för data- och systemvetenskap.
2017 (Engelska)Ingår i: Procedia Computer Science, ISSN 1877-0509, E-ISSN 1877-0509, Vol. 121, s. 491-502Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

There is an extensive scientific research on the disadvantages of losing competencies in IT Outsourcing (ITO). In this study we have looked exclusively at “tacit” knowledge (knowledge that is hard to transfer to another person practically or in writing) and a analyzed the skill lose in ITO in a medium-sized, governmental agency in Sweden. The tacit knowledge of the primary processes and how the information systems are used in the organization, are considered to have significant value for ITO decisions. The research problem is the lack of knowledge about how loss of tacit knowledge influences ITO. To address the problem a case study research has been used as research method and the data was collected through interviews with decision makers in a Swedish governmental agency in the process of outsourcing their IT. The study has found a few justifications for keeping tacit knowledge of secondary processes in-house, only in organizations with a high uncertainty. In fact, for highly specified primary processes, it is of advantage to keep tacit knowledge in-house. Otherwise, the focus should be on standardization and the use of best practices. The results of this research could provide guidelines to IT managers of other governmental agencies in Sweden that are having a similar organization size.

Ort, förlag, år, upplaga, sidor
2017. Vol. 121, s. 491-502
Nyckelord [en]
IT outsourcing, govermental agency, tacit knowledge, knowledge transfer, transaction cost theory
Nationell ämneskategori
Systemvetenskap, informationssystem och informatik
Forskningsämne
data- och systemvetenskap
Identifikatorer
URN: urn:nbn:se:su:diva-150352DOI: 10.1016/j.procs.2017.11.066OAI: oai:DiVA.org:su-150352DiVA, id: diva2:1167136
Tillgänglig från: 2017-12-18 Skapad: 2017-12-18 Senast uppdaterad: 2018-01-13Bibliografiskt granskad

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Hodosi, GeorgRusu, Lazar
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Institutionen för data- och systemvetenskap
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Procedia Computer Science
Systemvetenskap, informationssystem och informatik

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