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Information Systems Frontiers

, Volume 14, Issue 2, pp 343–361 | Cite as

Inter-organisational knowledge transfer in social networks: A definition of intermediate ties

  • Silke RetzerEmail author
  • Pak Yoong
  • Val Hooper
Article

Abstract

A social network perspective helps identify and analyse informal knowledge transfer among people and organisations with the aim to recommend organisational interventions and improvements, for example in the form of Information and Communication Technology (ICT) support. This paper particularly focuses on a key concept of social network analysis (SNA), the concept of tie strength, in an inter-organisational knowledge transfer context. Tie strength describes the strength of a social relationship. In the past, SNA literature with a knowledge management context has often emphasized the importance of strong and/or weak ties rather than of intermediate (medium strong) ties in a social network. Nevertheless, in this study, intermediate ties are identified as the dominant links among key groups of organisation in a social network. Intermediate ties also help connect otherwise weakly linked organisations. Moreover, a definition of intermediate ties in the context of knowledge management is introduced. With the help of cluster analysis and an investigation into the levels of reciprocity, intermediate ties can be clearly defined in a social network. Due to their importance for knowledge transfer in a social network, intermediate ties should be primarily supported, for example by appropriate ICT.

Keywords

Knowledge transfer Social network analysis Tie strength Intermediate ties 

References

  1. Adams, J. S. (1976). The structure and dynamics of behavior in organizational boundary roles. In M. D. Dunnette (Ed.), Handbook of Industrial and Organizational Psychology (pp. 1175-1199). Chicago: Rand McNally.Google Scholar
  2. Aldrich, H., & Herker, D. (1977). Boundary-spanning roles and organization structure. Academy of Management Review, 2, 217–230.Google Scholar
  3. Allen, J., James, A. D., & Gamlen, P. (2007). Formal versus informal knowledge networks in R&D: a case study using social network analysis. R&D Management, 37(3), 179–196.CrossRefGoogle Scholar
  4. Anklam, P. (2002). Social network analysis for knowledge management. Paper presented at the KMWorld, Santa Clara, California.Google Scholar
  5. Borrego, M., Osborne, L., Streveler, R., Smith, K., & Miller, R. (2007). Quantitative and qualitative measures of community development through a structured workshop curriculum. West Lafayette: American Society for Engineering Education.Google Scholar
  6. Bresman, H., Birkinshaw, J., & Nobel, R. (1999). Knowledge transfer in international acquisitions. Journal of International Business Studies, 30(3), 439–462.CrossRefGoogle Scholar
  7. Calloway, M., Morrissey, J. P., & Paulson, R. I. (1993). Accuracy and reliability in self-reported data in interorganizational networks. Social Networks, 15, 377–398.CrossRefGoogle Scholar
  8. Chan, K., & Liebowitz, J. (2006). The synergy of social network analysis and knowledge mapping: a case study. International Journal of Management and Decision Making, 7(1), 19–35.CrossRefGoogle Scholar
  9. Chaturvedi, A., Carroll, J. D., Green, P. E., & Rotondo, J. A. (1997). A feature-based approach to market segmentation via overlapping K-centroids clustering. Journal of Marketing Research, 34, 370–377.CrossRefGoogle Scholar
  10. Chen, X., & Wang, L. (2009). Integrating biological knowledge with gene expression profiles for survival prediction of cancer. Journal of Computational Biology, 16(2), 265–278.CrossRefGoogle Scholar
  11. Dodds, P. S., Muhamad, R., & Watts, D. J. (2003). An experimental study of search in global social networks. Science, 301(5634), 827–829.CrossRefGoogle Scholar
  12. Easterby-Smith, M., Lyles, M., & Tsang, E. (2008). Inter-organizational knowledge transfer: current themes and future prospects. Journal of Management Studies, 45(4), 677–690.CrossRefGoogle Scholar
  13. Foster-Fishman, P. G., Salem, D. A., & Allen, N. A. (2001). Facilitating interorganizational collaboration: the contributions of interorganizational alliances. American Journal of Community Psychology, 29(6), 875–905.CrossRefGoogle Scholar
  14. Friedkin, N. (1980). A test of structural features of Granovetter’s strength of weak ties theory. Social Networks, 2, 411–422.CrossRefGoogle Scholar
  15. Garton, L., Haythornthwaite, C., & Wellman, B. (1997). Studying online social networks [Electronic Version]. Journal of Computer Mediated Communication, 3. Retrieved 10 May 2009 from http://jcmc.indiana.edu/vol3/issue1/garton.html.
  16. Granovetter, M. (1973). The strength of weak ties. American Journal of Sociology, 78(6), 1360–1380.CrossRefGoogle Scholar
  17. Granovetter, M. (1974). Getting a job: A study of contacts and careers (1st ed.). Cambridge: Harvard University Press.Google Scholar
  18. Hansen, M. T. (1999). The search-transfer problem: the role of weak ties in sharing knowledge across organisational subunits. Administrative Science Quarterly, 44(1), 82–111.CrossRefGoogle Scholar
  19. Haythornthwaite, C. (1996a). Media use in support of communication networks in an academic research environment. Toronto: University of Toronto.Google Scholar
  20. Haythornthwaite, C. (1996b). Social network analysis:An approach and technique for the study of information exchange. Library and Information Science Research, 18, 323–342.CrossRefGoogle Scholar
  21. Haythornthwaite, C. (1999). A social network theory of tie strength and media use: a framework for evaluating multi-level impacts of new media (No. Technical Report UIUCLIS-2002/1+DKRC). Champaign, IL: Graduate School of Library and Information Science, University of Illinois at Urbana-Champaign.Google Scholar
  22. Haythornthwaite, C., & Wellman, B. (1998). Work, friendship, and media use for information exchange in a networked organization. Journal of the American Society for Information Science, 49(12), 1101–1114.CrossRefGoogle Scholar
  23. Hexmoor, H., Wilson, S., & Bhattaram, S. (2006). A theoretical inter-organizational trust-based security model. The Knowledge Engineering Review, 21(2), 127–161.CrossRefGoogle Scholar
  24. Langlois, S. (1977). Les Réseaux Personnels et la Diffusion des Informations sur les Emplois. Recherches Sociographiques, 2, 213–245.Google Scholar
  25. Levin, D. Z., & Cross, R. (2004). The strength of weak ties you can trust: the mediating role of trust in effective knowledge transfer. Management Science, 50(11), 1477–1490.CrossRefGoogle Scholar
  26. Liebowitz, J. (2005). Linking social network analysis with the analytic hierarchy process for knowledge mapping in organizations. Journal of Knowledge Management, 9(1), 76–86.CrossRefGoogle Scholar
  27. Lin, N., Dayton, P. W., & Greenwald, P. (1978). Analyzing the instrumental use of relations in the context of social structure. Sociological Methods and Research, 7, 149–166.CrossRefGoogle Scholar
  28. Maier, R. (2001). Knowledge management systems (1st ed.). Berlin: Springer.Google Scholar
  29. Marsden, P. V., & Campbell, K. E. (1984). Measuring tie strength. Social Forces, 63(2), 482–501.Google Scholar
  30. Mitchell, V. L. (2006). Knowledge integration and information technology project performance. MIS Quarterly, 30(4), 919–939.Google Scholar
  31. Mladenić, D., Grobelnik, M., Fortuna, B., & Grćar, M. (2009). Knowledge discovery for semantic web. In J. Davies, M. Grobelnik, & D. Mladenić (Eds.), Semantic knowledge management (pp. 21–36). Berlin: Springer.CrossRefGoogle Scholar
  32. Onnela, J. P., Saramäki, J., Hyvönen, J., Szabó, G., Lazer, D., Kaski, K., et al. (2007). Structure and tie strengths in mobile communication networks. Proceedings of the National Academy of Sciences of the United States of America, 104(18), 7332–7336.CrossRefGoogle Scholar
  33. Petróczi, A., Nepusz, T., & Bazsó, F. (2007). Measuring tie-strength in virtual social networks. Connections, 27(2), 39–52.Google Scholar
  34. Scott, J. (2000). Social network analysis: A handbook. London: Sage.Google Scholar
  35. Teddlie, C., & Yu, F. (2007). Mixed methods sampling. Journal of Mixed Methods Research, 1(1), 77–100.CrossRefGoogle Scholar
  36. Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge: Cambridge University Press.Google Scholar
  37. Weatherill, G., & Burton, P. W. (2009). Delineation of shallow seismic source zones using K-means cluster analysis, with application to the Aegean region. Geophysical Journal International, 176(2), 565–588.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.School of Information ManagementVictoria University of WellingtonWellingtonNew Zealand

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