Skip to main content

A Firm-Growing Model and the Study of Communication Patterns’ Effect on the Structure of Firm’s Social Network

  • Conference paper
Complex Sciences (Complex 2009)

Abstract

In this article, we propose a firm-growing model, and then collect empirical data to test model validity. The simulation results agree well with the empirical data. We next explore the effect of communication patterns on the growth and structure of firm’s social network and find that the extents to which employees reluctantly interact within or across departments significantly influence the structure of firm’s social network.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Nonaka, I.: A dynamic theory of organizational knowledge creation. Organization Science 5(1), 14–37 (1994)

    Article  Google Scholar 

  2. Drucker, P.: Post-Capitalist Society. Butterworth Heinemann, London (1993)

    Google Scholar 

  3. Granovetter, M.: The strength of weak ties. American Journal of Sociology 78, 1360–1380 (1973)

    Article  Google Scholar 

  4. Burt, R.S.: Structural holes: the social structure of competition. Harvard University Press, Cambridge (1992)

    Google Scholar 

  5. Burt, R.S., Ronchi, D.: Teaching executives to see social capital: results from a field experiment. Social Science Research 36, 1156–1183 (2007)

    Article  Google Scholar 

  6. Ramasco, J.J., Morris, S.A.: Social inertia in collaboration networks. Physical Review E 73, 016122 (2006)

    Article  Google Scholar 

  7. Ebel, H., Mielsch, L.I., Borbholdt, S.: Scale-free topology of e-mail networks. Phys. Rev. E. 66, 35103 (2002)

    Article  Google Scholar 

  8. Bachnik, W., Szymczak, S., Leszczynski, P., Podsiadlo, R., Rymszewicz, E., Kurylo, L., Makowiec, D., Bykowska, B.: Acta Phys. Pol. 36, 3179 (2005)

    Google Scholar 

  9. Csányi, G., Szendröi, B.: Structure of a large social network. Physical Review E 69(3), 036131 (2004)

    Article  Google Scholar 

  10. Guimera, R., Uzzi, B., Spiro, J., Amaral, L.A.N.: Team assembly mechanisms determine collaboration network structure and team performance. Science 308, 697–702 (2005)

    Article  Google Scholar 

  11. O’Dell, C., Grayson, C.J.: If only we kew what we know: indentification and transfer of internal best practices. California Management Review 40(3), 154–174 (1998)

    Article  Google Scholar 

  12. Zalesny, M.D., Farace, F.V.: Traditional versus open offices: A comparison of sociotechnical, social Relations, and symbolic Meaning Perspectives. Academy of Management Journal 30(2), 240–259 (1987)

    Article  Google Scholar 

  13. Katz, R., Allen, T.J.: Investigating the not invented here (NIH) syndrome: a look at the performancetenure and communication patterns of 50 R&D project groups. R& D Management 12(1), 7–19 (1982)

    Article  Google Scholar 

  14. Anklam, P.: Knowledge management the collaboration thread. Bulletin of the American society for information and technology 28(6), 8–11 (2002)

    Article  Google Scholar 

  15. Cummings, J.N., Cross, R.: Structural properties of work groups and their consequences for performance. Social Networks 25, 197–210 (2003)

    Article  Google Scholar 

  16. Hansen, M.: The search-transfer problem: The role of weak ties in sharing knowledge across organizational subunits. Admin. Sci. Quart. 44, 82–111 (1999)

    Article  Google Scholar 

  17. Szulanski, G.: Exploring internal stickiness: impedements to the transfer of best practice within the firm. Strategic Management Journal 17, 27–43 (1996)

    Article  Google Scholar 

  18. Krackhardt, D., Hanson, J.R.: Informal networks: the company behind the chart. Harvard besiness review, 104–111 (July-August 1993)

    Google Scholar 

  19. Levin, D.Z., Cross, R.: The Strength of Weak Ties You Can Trust: The Mediating Role of Trust in Effective Knowledge Transfer. Management Science 50(11), 1477–1490 (2004)

    Article  Google Scholar 

  20. Cohen, R., Erez, K., ben-Avraham, D., Havlin, S.: Resilience of the internet to random breakdowns. Physical Review Letters 85, 4626–4628 (2000)

    Article  Google Scholar 

  21. Newman, M.E.J., Park, J.: Why social networks are different from other types of networks. Phys. Rev. E. 68, 036122 (2003)

    Article  Google Scholar 

  22. Newman, M.E.J.: Mixing patterns in networks. Phys. Rev. E 67, 026126 (2003)

    Article  MathSciNet  Google Scholar 

  23. Erdös, P., Rényi, A.: On random graphs. Publicationes Mathematicae 6, 290–297 (1959)

    MathSciNet  MATH  Google Scholar 

  24. Newman, M.E.J.: Assortative mixing in networks. Phys. Rev. Let. 89, 208701 (2002)

    Article  Google Scholar 

  25. Amaral, L.A.N., Scala, A., Barthlmy, M., et al.: Classes of small-world networks. Proc. Natl. Acad. Sci. USA 97, 11149–11152 (2000)

    Article  Google Scholar 

  26. Newman, M.E.J.: Scientific collaboration networks. I. Network construction and fundamental results. Phys. Rev. E 64, 016131(2001)

    Article  Google Scholar 

  27. Zhang, P.P., Chen, K., et al.: Model and empirical study on some collaboration networks. Physica A: Statistical Mechanics and its applications 360(2), 599–616 (2006)

    Article  Google Scholar 

  28. Chang, H., Su, B.B., Zhou, Y.P., He, D.R.: Assortativity and act degree distribution of some collabortation networks 383(2), 687–702 (2007)

    Google Scholar 

  29. Freeman, L.: Centrality in social networks: Conceptual clarification. Social Networks 1(3), 215–234 (1979)

    Article  Google Scholar 

  30. Albert, R., Jeong, H., Barabási, A.-L.: Attack and error tolerance in complex nerworks. Nature 406, 387–482 (2001)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering

About this paper

Cite this paper

Chen, L., Li, H., Chen, Z., Li, L., He, DR. (2009). A Firm-Growing Model and the Study of Communication Patterns’ Effect on the Structure of Firm’s Social Network. In: Zhou, J. (eds) Complex Sciences. Complex 2009. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 5. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02469-6_18

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-02469-6_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02468-9

  • Online ISBN: 978-3-642-02469-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics