Factors impacting knowledge transfer success in information systems outsourcing

Abstract

Despite increased research interest on knowledge transfer in information systems (IS) outsourcing, the field still lacks sound and holistic understanding of the key factors influencing knowledge transfer success. The present paper attempts to provide a synthesis of existing theoretical perspectives and empirical findings related to the factors that facilitate or hamper knowledge transfer success in IS outsourcing. The data collection method is discussed and the key findings are presented. Conclusion is drawn and further research is suggested. Keywords: knowledge transfer, Information systems (IS) outsourcing BACKGROUNDIn today's knowledge-based economy, one of the major sources of competitive advantage has been the ability of the firm to transfer external knowledge efficiently and effectively (Argote and Ingram, 2000;Pawlowski and Robey, 2004;Sambamurthy and Subramani, 2005;Pérez-Nordtvedt et al., 2008). Knowledge transfer is defined by Kumar and Ganesh (2009) as activities of exchanging explicit or tacit knowledge between two agents, during which one agent receive and apply the knowledge provided by the other agent. The agents could be an individual, team/department or an organization (Joshi et al., 2007). In the literature, knowledge transfer has been given various but related labels such as ‗knowledge sharing, ‗knowledge flows', ‗knowledge acquisition' and ‗knowledge mobilization ' (Carmel and Nicholson, 2005;Gosain, 2007;Renzl, 2008;van Wijk et al, 2008).Information systems (IS) outsourcing, where a client organization contract out some or all of its IS functions to one or more external vendors (Lee, 2001), has been regards as an important business strategy for client organizations to transfer new technical and business knowledge from the vendors (e.g. Ko et al., 2005;Tafti, 2007, Blumenberg et al., 2009). Wang et al. (2008 argued that outsourcing IS to high quality vendors has the potential to transfer knowledge that are costly or hard to develop in-house. Furthermore, IS outsourcing allows the client organizations to renew its technical and business knowledge base in order to achieve congruence with changing business environment (Bandyopadhyay and Pathak, 2007). In their (2005) reported that client organizations acquire new implementation, operational and maintenance knowledge from their consultants, so they can learn and later maintain the system independent of the consultant's team. Edguer and Pervan (2004) found that many firms are increasingly looking at IS outsourcing as a means of transferring and leveraging the vendors' superior technical and business knowledge and benefiting complementary skills and specialist expertise that are not available within the organization's boundaries. Knowledge transfer from vendors to clients in IS outsourcing projects occur through a variety of mechanisms. These mechanisms include manuals, personal movement, training, observation, presentations and close interaction with vendors' IS staff (Nicholson and Sahay, 2004;Xu et al., 2006;Chua and Pan, 2008) Knowle...

Integration of fuzzy DEMATEL and FMCDM approach for evaluating knowledge transfer effectiveness with reference to GSD project outcome

“…It is a clear indication that Gathering information and experience among teams 0.108 [7] 0.0388 [7] 0.895 [12] 0.0302 [7] C 12 Sharing knowledge and experience among team members 0.104 [11] 0.0327 [11] 0.917 [7] 0.0300 [11] C 13 Understanding goals, tasks and responsibilities over the project outcome 0.098 [16] 0.0308 [16] 0.643 [6] 0.0198 [38] C 14 Team participation and communication relationship 0.100 [14] 0.0313 [14] 0.750 [25] 0.0235 [3] C 15 Participation in helping each other 0.101 [12] 0.0317 [12] 0.685 [23] 0.0217 [25] C 16 Specialty and knowledge creation ability among teams 0.101 [12] 0.0317 [12] 0.815 [17] 0.0259 [13] C 17 Learning and sharing the technical information and work materials of teams 0.097 [2] 0.0305 [2] 0.805 [19] 0.0246 [2] C 18 Team members' ability to provide assistance in solving problems 0.099 [15] 0.0312 [15] 0.805 [19] 0.0251 [14] C 19 Clear vision to solve their professional problems towards the project outcome 0.097 [2] 0.0304 [17] 0.685 …”

“…The final section includes the conclusion of the study and addresses the significance of knowledge transfer effectiveness on GSD teams. Earlier studies have addressed the characteristics of knowledge and significance of knowledge transfer in IS outsourcing success [2,[11][12][13][14][15][16]. Moreover, most of the studies have substantially acknowledged the significance of socialization, externalization, combination, and internalization (SECI) in knowledge management theory [17][18][19].…”

“…Cooperation and competing within teams to fulfill goals 0.093 [17] 0.0292 [8] 0.773 [22] 0.0226 [22] C 22 Personal attachment and support towards the project 0.110 [16] 0.0291 [26] 0.857 [13] 0.0249 [15] C 23 Feeling of togetherness or closeness within the teams 0.112 [11] 0.0296 [3] 0.792 [4] 0.0235 [3] C 24 Participation and support to solve issues 0.112 [11] 0.0295 [20] 0.695 [9] 0.0205 [30] C 25 Mutual support of team members 0.108 [2] 0.0285 [29] 0.685 [23] 0.0195 [9] C 26 Co-ordination of teams on project outcome 0.112 [11] 0.0297 [1] 0.838 [14] 0.0249 [15] C 27 Suggestion and contribution of teams on project outcomes 0.113 [7] 0.0299 [18] 0.810 [18] 0.0242 [19] C 28 Persistent, conscientious responsiveness information of teams on project outcomes 0.111 [14] 0.0294 [21] 0.800 [20] 0.0236 [1] C 29 Establishment pertinent information towards the project outcomes 0.111 [14] 0.0292 [8] 0.783 [21] 0.0229 …”

Knowledge application in Ghanaian industries

“…The literature has argued that the factors that influence knowledge application include absorptive capacity (Al-Salti et al, 2010), trust (Gupta and Govindarajan, 2000), culture (Karlsen and Gottschalk, 2004), reward (Evaristo, 2005), willingness to apply knowledge (Liyanage et al, 2009) and expertise (Salsali et al, 2009). Among these factors, the study found trust, culture and absorptive capacity as the critical factors in knowledge application in Ghanaian industries, confirming the findings of Gupta Note: The means are determined by using a five-point Likert scale rating from strongly agree (5) to strongly disagree (1).…”

Preventing Problems in Technology Transfer: A Case Study

“…According to Al-Salti and Hackney (2011), there are a number of problems, such as the ambiguity of knowledge, the tacit knowledge, the di±cult relationship between source and the receiver, the complexity and the context of knowledge, the lack of motivation and reliability of the transmitter, the lack of motivation and retentive capacity from receiver. Albino et al (1998) describe the steps that should be taken and the restrictions that should be imposed to prevent a company losing its competitiveness during a TT due to access by third parties to certain knowledge without appropriate controls.…”