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Communication and organizational social networks: a simulation model

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Abstract

Recent management research has evidenced the significance of organizational social networks, and communication is believed to impact the interpersonal relationships. However, we have little knowledge on how communication affects organizational social networks. This paper studies the dynamics between organizational communication patterns and the growth of organizational social networks. We propose an organizational social network growth model, and then collect empirical data to test model validity. The simulation results agree well with the empirical data. The results of simulation experiments enrich our knowledge on communication with the findings that organizational management practices that discourage employees from communicating within and across group boundaries have disparate and significant negative effect on the social network’s density, scalar assortativity and discrete assortativity, each of which correlates with the organization’s performance. These findings also suggest concrete measures for management to construct and develop the organizational social network.

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Notes

  1. The excess degree is the number of remaining edges connected to the vertex when we choose a random edge and follow it to one of its vertices. This number is one less than the total degree of the vertex.

References

  • Abelson H, Sussman GJ, Sussman J (1996) Structure and interpretation of computer programs. MIT Press, Cambridge

    Google Scholar 

  • Ahrweiler P, Gilbert N, Pyka A (2011) Agency and structure: a social simulation of knowledge-intensive industries. Comput Math Organ Theory 17(1):59–76

    Article  Google Scholar 

  • Allen TJ (1971) Communication networks in R&D laboratories. R & D Manag 1(1):14–21

    Article  Google Scholar 

  • Allen TJ (1977) Managing the flow of technology. MIT Press, Cambridge

    Google Scholar 

  • Andrighetto G, Boella G, Sichman J, Verhagen H (2011) Preface. Comput Math Organ Theory 17(4):315–317

    Article  Google Scholar 

  • Barabási A-L, Albert R (1999) Emergence of scaling in random networks. Science 286:509–512

    Article  Google Scholar 

  • Boissevain J (1974) Friends of friends: networks, manipulators and coalitions. St. Martin’s Press, New York

    Google Scholar 

  • Borgatti SP, Cross R (2003) A relational view of information seeking and learning in social networks. Manag Sci 49:432–445

    Article  Google Scholar 

  • Bulte CVD, Moenaert RK (1998) The effects of R&D team co-location on communication patterns among R&D, marketing, and manufacturing. Manag Sci 44(11):S1–S18

    Article  Google Scholar 

  • Burkhardt ME, Brass DJ (1990) Changing patterns or patterns of change: the effects of a change in technology on social network structure and power. Adm Sci Q 35:104–127

    Article  Google Scholar 

  • Burton RM (2003) Computational laboratories for organization science: question, validity and docking. Comput Math Organ Theory 9:91–108

    Article  Google Scholar 

  • Campbell DT, Stanley JC (1966) Experimental and quasi-experimental designs for research. Rand McNally, Chicago

    Google Scholar 

  • Carroll G, Harrison JR (1998) Organizational demography and culture: insights from a formal model and simulation. Adm Sci Q 43:637–667

    Article  Google Scholar 

  • Catania JA, Coates TJ, Kegels S, Fullilove MT (1992) Condom use in multi-ethnic neighborhoods of San Francisco: the population-based AMEN (AIDS in Multi-Ethnic Neighborhoods) study. Am J Publ Health 82:284–287

    Article  Google Scholar 

  • Catanzaro M, Caldarelli G, Pietronero L (2004) Assortative model for social networks. Phys Rev E 70:037101

    Article  Google Scholar 

  • Chang H, Su BB, Zhou YP, He DR (2007) Assortativity and act degree distribution of some collaboration networks. Physica A 383:687–702

    Article  Google Scholar 

  • Conley TG, Topa G (2002) Socio-economic distance and spatial patterns in unemployment. J Appl Econom 17:303–327

    Article  Google Scholar 

  • Cross R, Prusak L (2002) The people who make organizations go or stop. Harv Bus Rev 104–112

  • Cummings JN (2004) Work groups, structural diversity, and knowledge sharing in a global organization. Manag Sci 50:352–364

    Article  Google Scholar 

  • Davis JP, Eisenhardt KM, Bingham CB (2007) Developing theory through simulation methods. Acad Manag Rev 32(2):480–499

    Article  Google Scholar 

  • De Meyer A (1991) Tech talk: how managers are stimulating global R&D communication. Sloan Manag Rev 32(3):49–58

    Google Scholar 

  • Diamond MA, Stein HF, Allcorn S (2002) Organizational silos: horizontal organizational fragmentation. J Psychoanal Cult Soc 7(2):280–296

    Google Scholar 

  • Downs CW, Hazen MD (1977) A factor analytic study of communication satisfaction. J Bus Commun 14(3):63–73

    Article  Google Scholar 

  • Elmore KL, Richman MB (2001) Euclidean distance as a similarity metric for principal component analysis. Am Meteorol Soc J 129(3):540–549

    Google Scholar 

  • Falcone R, Castelfranchi C (2011) Trust and relational capital. Comput Math Organ Theory 17(4):402–418

    Article  Google Scholar 

  • Fenner T, Levene M, Loizou G (2007) A model for collaboration networks giving rise to a power-law distribution with an exponential cutoff. Soc Netw 29:70–80

    Article  Google Scholar 

  • Freeman L (1979) Centrality in social networks: conceptual clarification. Soc Netw 1:215–234

    Article  Google Scholar 

  • Freeman LC, Romney AK, Freeman S (1987) Cognitive structure and informant accuracy. Am Anthropol 89:310–325

    Article  Google Scholar 

  • Gardner WL, Avolio BJ, Walumbwa FO (2005) Authentic leadership theory and practice: origins, effects and development. Elsevier, Oxford, pp 126–128

    Google Scholar 

  • Gibb JR (1961) Defensive and supportive communication. J Commun 11:141–148

    Article  Google Scholar 

  • Goh K-I, Oh E, Kahng B, Kim D (2003) Betweenness centrality correlation in social networks. Phys Rev E 67(1):017101

    Article  Google Scholar 

  • Granovetter M (1973) The strength of weak ties. Am J Sociol 78:1360–1380

    Article  Google Scholar 

  • Grow A, Flache A (2011) How attitude certainty tempers the effects of faultlines in demographically diverse teams. Comput Math Organ Theory 17(2):196–224

    Article  Google Scholar 

  • Guo W, Li X, Wang X (2007) Epidemics and immunization on Euclidean distance preferred small-world networks. Physica A 380:684–690

    Article  Google Scholar 

  • Hansen M (1999) The search-transfer problem: the role of weak ties in sharing knowledge across organizational subunits. Adm Sci Q 44:82–111

    Article  Google Scholar 

  • Hirshman BR, St. Charles J, Carley KM (2011) Leaving us in tiers: can homophily be used to generate tiering effects? Comput Math Organ Theory 17(4):318–343

    Article  Google Scholar 

  • Holme P, Edling CR, Liljeros F (2004) Structure and time evolution of an Internet dating community. Soc Netw 26:155–174

    Article  Google Scholar 

  • Ibarra H (1992) Homophily and differential returns: sex differences in network structure and access in an advertising firm. Adm Sci Q 37:422–447

    Article  Google Scholar 

  • Ibarra H (1995) Race, opportunity and diversity of social circles in managerial networks. Acad Manag J 38:673–703

    Article  Google Scholar 

  • Jehn KA, Northcraft GB, Neale MA (1999) Why differences make a difference: a field study of diversity, conflict, and performance in workgroups. Adm Sci Q 44:741–763

    Article  Google Scholar 

  • Jin EM, Girvan M, Newman MEJ (2001) Structure of growing social networks. Phys Rev E 64:046132

    Article  Google Scholar 

  • Johnson DJ, Donohue WA, Atkin CK, Johnson S (1994) Differences between formal and informal communication channels. J Bus Commun 31:111–122

    Article  Google Scholar 

  • Jonassen DH, Kwon H (2001) Communication patterns in computer mediated versus face-to-fact group problem solving. Educ Technol Res Dev 49(1):35–51

    Article  Google Scholar 

  • Katz R, Allen TJ (1982) Investigating the not invented here (NIH) syndrome: a look at the performance tenure and communication patterns of 50 R&D project groups. R & D Manag 12:7–19

    Article  Google Scholar 

  • Katz R, Allen TJ (2004) Organizational issues in the introduction of new technologies. In: Katz R (ed) The human side of managing technological innovation. Oxford University Press, Oxford, pp 450–477

    Google Scholar 

  • Kiesler S, Cummings JN (2002) What do we know about proximity and distance in work groups? In: Hinds PJ, Kiesler S (eds) Distributed work. MIT Press, Cambridge, pp 57–80

    Google Scholar 

  • Kirmeyer SL, Lin T (1987) Social support its relationship to observed communication with peers and superiors. Acad Manag J 30(1):138–151

    Article  Google Scholar 

  • Latora V, Marchiori M (2001) Efficient behavior of small-world networks. Phys Rev Lett 87:198701

    Article  Google Scholar 

  • Latour B, Woolgar S (1979) Laboratory life. Sage, Beverly Hills

    Google Scholar 

  • Levin DZ, Cross R (2004) The strength of weak ties you can trust: the mediating role of trust in effective knowledge transfer. Manag Sci 50:1477–1490

    Article  Google Scholar 

  • Marsden P (1990) Network data and measurement. Annu Rev Sociol 16:435–463

    Article  Google Scholar 

  • Mcfadyen MA, Cannella AA Jr (2004) Social capital and knowledge creation: diminishing returns of the number and strength of exchange relationships. Acad Manag J 47(5):735–746

    Article  Google Scholar 

  • Mollica KA, Gray B, Trevino LK (2003) Racial homophily and its persistence in newcomers’ social networks. Organ Sci 14:123–136

    Article  Google Scholar 

  • Newman MEJ (2002) Assortative mixing in networks. Phys Rev Lett 89:208701

    Article  Google Scholar 

  • Newman MEJ (2003a) Mixing patterns in networks. Phys Rev E 67:026126

    Article  Google Scholar 

  • Newman MEJ (2003b) The structure and function of complex networks. SIAM Rev 45:167–256

    Article  Google Scholar 

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

    Article  Google Scholar 

  • O’Dell C, Grayson CJ (1998) If only we knew what we know: identification and transfer of internal best practices. Calif Manag Rev 40(3):154–174

    Article  Google Scholar 

  • Putnis P, Petelin R (1996) Professional communication: principles and applications. Prentice Hall, Sydney

    Google Scholar 

  • Quayle AP, Siddiqui AS, Jones SJM (2006) Modeling network growth with assortative mixing. Eur Phys J B 50:617–630

    Article  Google Scholar 

  • Ravasz E, Barabási A-L (2003) Hierarchical organization in complex networks. Phys Rev E 67(2):026112

    Article  Google Scholar 

  • Reagans R, McEvily B (2003) Network structure and knowledge transfer: the effects of cohesion and range. Adm Sci Q 48:240–267

    Article  Google Scholar 

  • Reagans R, Zuckerman EW (2001) Networks, diversity, and productivity: the social capital of corporate R&D teams. Organ Sci 12:502–517

    Article  Google Scholar 

  • Rogers E, Kincaid D (1981) Communication networks. Free Press, New York

    Google Scholar 

  • Rulke DL, Galaskiewicz J (2000) Distribution of knowledge, group network structure, and group performance. Manag Sci 46:612–625

    Article  Google Scholar 

  • Sastry MA (1997) Problems and paradoxes in a model of punctuated organizational change. Adm Sci Q 42:237–275

    Article  Google Scholar 

  • Sparrowe RT, Liden RC, Karaimer ML (2001) Social networks and the performance of individuals and groups. Acad Manag J 44:316–325

    Article  Google Scholar 

  • Szulanski G (1996) Exploring internal stickiness: impediments to the transfer of best practice within the firm. Strateg Manag J 17:27–43

    Google Scholar 

  • Tourish D, Hargie O (2004) Key issues in organizational communication. Routledge, New York, pp 205–210

    Google Scholar 

  • Van den Bulte C, Moenaert RK (1998) The effects of R&D team co-location on communication patterns among R&D, marketing, and manufacturing. Manag Sci 44(11):S1–S51

    Article  Google Scholar 

  • Wang W-X, Hu B, Wang B-H, Yan G (2006) Mutual attraction model for both assortative and disassortative weighted networks. Phys Rev E 73:016133

    Article  Google Scholar 

  • Wasserman S, Faust K (1994) Social network analysis: methods and applications. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Watts DJ, Strogatz SH (1998) Collective dynamics of ‘small-world’ networks. Nature 393(4):440–442

    Article  Google Scholar 

  • Weedman J (1992) Informal and formal channels in boundary-spanning communication. J Am Soc Inf Sci 43:257–267

    Article  Google Scholar 

  • Yilmaz L (2006) Validation and verification of social processes within agent-based computational organization models. Comput Math Organ Theory 12:283–312

    Article  Google Scholar 

  • Zalesny MD, Farace FV (1987) Traditional versus open offices: a comparison of sociotechnical, social relations, and symbolic meaning perspectives. Acad Manag J 30:240–259

    Article  Google Scholar 

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Acknowledgements

We thank the financial grants from the National Natural Science Foundation of China (project No. 71001040 and No. 71102167). We acknowledge the highly professional assistance and intellectual input of Research Assistant Karen Stark.

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Authors and Affiliations

  1. School of Business, East China University of Science and Technology, Shanghai, 200237, China

    Liang Chen & Haibo Hu

  2. Faculty of Science and Technology, Queensland University of Technology, Brisbane, Queensland, 4001, Australia

    Guy G. Gable

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  1. Liang Chen
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Correspondence to Liang Chen.

Additional information

The Chinese version of this paper with minor changes has been published in Journal of Systems & Management 19(1):37–44 (2010).

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Chen, L., Gable, G.G. & Hu, H. Communication and organizational social networks: a simulation model. Comput Math Organ Theory 19, 460–479 (2013). https://doi.org/10.1007/s10588-012-9131-0

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