Krancher, Oliver (2013). Knowledge transfer in software-maintenance offshore outsourcing. (Thesis). Universität Bern, Bern
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Abstract
Software-maintenance offshore outsourcing (SMOO) projects have been plagued by tedious knowledge transfer during the service transition to the vendor. Vendor engineers risk being over-strained by the high amounts of novel information, resulting in extra costs that may erode the business case behind offshoring. Although stakeholders may desire to avoid these extra costs by implementing appropriate knowledge transfer practices, little is known on how effective knowledge transfer can be designed and managed in light of the high cognitive loads in SMOO transitions. The dissertation at hand addresses this research gap by presenting and integrating four studies. The studies draw on cognitive load theory, attributional theory, and control theory and they apply qualitative, quantitative, and simulation methods to qualitative data from eight in-depth longitudinal cases. The results suggest that the choice of appropriate learning tasks may be more central to knowledge transfer than the amount of information shared with vendor engineers. Moreover, because vendor staff may not be able to and not dare to effectively self-manage learn-ing tasks during early transition, client-driven controls may be initially required and subsequently faded out. Collectively, the results call for people-based rather than codification-based knowledge management strategies in at least moderately specific and complex software environments.
| Item Type: | Thesis |
|---|---|
| Dissertation Type: | Single |
| Date of Defense: | 2013 |
| Additional Information: | e-Dissertation (edbe) |
| Uncontrolled Keywords: | Knowledge transfer, Outsourcing, Offshoring, Software maintenance, Learning, Cognitive load, Control theory, Mixed methods |
| Subjects: | 600 Technology > 650 Management & public relations |
| Institute / Center: | 03 Faculty of Business, Economics and Social Sciences > Department of Business Management > Institute of Information Systems > Information Engineering 03 Faculty of Business, Economics and Social Sciences > Department of Business Management > Institute of Information Systems |
| Depositing User: | Admin importFromBoris |
| Date Deposited: | 25 Jan 2019 12:59 |
| Last Modified: | 06 Aug 2020 16:35 |
| URI: | https://boristheses.unibe.ch/id/eprint/999 |
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