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An agent-based model of the impact of computer-mediated communication on organizational culture and performance: an example of the application of complex systems analysis tools to the study of CIS

  • Research Article
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Journal of Information Technology

Abstract

Organizations that make use of computer information systems (CIS) are prototypical complex adaptive systems (CAS). This paper shows how an approach from Complexity Science, exploratory agent-based modeling (ABM), can be used to study the impact of two different modes of use of computer-mediated communication (CMC) on organizational culture (OC) and performance. The ABM includes stylized representations of (a) agents communicating with other agents to complete tasks; (b) an OC consisting of the distribution of agent traits, changing as agents communicate; (c) the effect of OC on communication effectiveness (CE), and (d) the effect of CE on task completion times, that is, performance. If CMC is used in a broad mode, that is, to contact and collaborate with many, new agents, the development of a strong OC is slowed, leading to decreased CE and poorer performance early on. If CMC is used in a local mode, repeatedly contacting the same agents, a strong OC develops rapidly, leading to increased CE and high performance early on. However, if CMC is used in a broad mode over longer time periods, a strong OC can develop over a wider set of agents, leading to an OC that is stronger than an OC which develops with local CMC use. Thus broad use of CMC results in overall CE and performance that is higher than is generated by local use of CMC. We also discuss how the dynamics generated by an ABM can lead to a deeper understanding of the behavior of a CAS, for example, allowing us to better design empirical longitudinal studies.

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Notes

  1. For this study, we define a stable network of contacts as a network in which, over time, individuals usually keep the same communication partners. On the other hand, an unstable network is characterized by a frequent change in communication partners.

References

  • Alge, B., Wiethof, C. and Klein, H. (2003). When Does the Medium Matter? Knowledge-Building Experiences and Opportunities in Decision-Making Teams, Organizational Behavior & Human Decision Processes 91(1): 26–37.

    Article  Google Scholar 

  • Anderson, P. (1999). Complexity Theory and Organization Science, Organization Science 10(3): 216–232.

    Article  Google Scholar 

  • Axelrod, R. and Cohen, M.D. (2000). Harnessing Complexity, Chicago: The Free Press.

    Google Scholar 

  • Axelrod, R. (1997a). Advancing the Art of Simulation in the Social Sciences, in R. Conte, R. Hegselmann and P. Terna (eds.) Lecture Notes in Economics and Mathematical Systems: Simulating Social Phenomena, Berlin: Springer-Verlag.

    Google Scholar 

  • Axelrod, R. (1997b). The Dissemination of Culture: A model with local convergence and global polarization, Journal of Conflict Resolution 41: 203–226.

    Article  Google Scholar 

  • Bankes, S.C. (1993). Exploratory Modeling for Policy Analysis, Operations Research 41(3): 435–449.

    Article  Google Scholar 

  • Bankes, S.C. (2002a). Agent-Based Modeling: A revolution? PNAS 99(3): 7199–7200.

    Article  Google Scholar 

  • Bankes, S.C. (2002b). Tools and Techniques for Developing Policies for Complex and Uncertain Systems, PNAS 99(3): 7263–7266.

    Article  Google Scholar 

  • Bonabeau, E. (2002). Agent-Based Modeling: Methods and techniques for simulating human systems, PNAS 99(3): 7280–7287.

    Article  Google Scholar 

  • Burke, K. and Chidambaram, L. (1999). How Much Bandwith is Enough? A Longitudinal Examination of Media Characteristics and Group Outcomes, MIS Quarterly 23(4): 557–580.

    Article  Google Scholar 

  • Canessa, E. (2002). Computer Mediated Communication and Organizational Culture: A survey-based study and agent based simulation model, Ph.D. Thesis, Rackham Graduate School, University of Michigan.

  • Canessa, E. and Riolo, R.L. (2003). The Effect of Organizational Communication Media on Organizational Culture and Performance: An agent-based simulation model, Computational and Mathematical Organization Theory 9(2): 147–176.

    Article  Google Scholar 

  • Chatman, J. (1988). Matching People and Organizations: Selection and socialization in public accounting firms, Ph.D. Thesis, University of California, Berkeley.

  • Chin, K., Pun, K., Ho, A. and Lau, H. (2002). A Measurement-Communication-Recognition Framework of Corporate Culture Change: An empirical study, Human Factors & Ergonomics in Manufacturing 12(4): 365–382.

    Article  Google Scholar 

  • Clark, H.H. (1996). Using Language, New York: Cambridge University Press.

    Book  Google Scholar 

  • Conte, R., Hegselmann, R. and Terna, P. (eds.) (1997). Simulating Social Phenomena, Berlin: Springer-Verlag.

    Book  Google Scholar 

  • Cornelius, C. and Boos, M. (2003). Enhancing Mutual Understanding in Synchronous Computer-Mediated Communication by Training: Trade-offs in judgmental tasks, Communication Research 30(2): 147–177.

    Article  Google Scholar 

  • Daft, R., Lengel, R. and Trevino, L. (1987). Message Equivocality, Media Selection, and Manager Performance: Implications for information systems, MIS Quarterly 11(3): 355–366.

    Article  Google Scholar 

  • Daft, R.L. and Lengel, R.H. (1986). Organizational Information Requirements, Media Richness and Structural Design, Management Science 32(5): 554–571.

    Article  Google Scholar 

  • Denison, D. (1990). Corporate Culture and Organizational Effectiveness, New York: John Wiley & Sons.

    Google Scholar 

  • Fulk, J. and DeSanctis, G. (1995). Electronic Communication and Changing Organizational Forms, Organization Science 6(4): 337–349.

    Article  Google Scholar 

  • Gilbert, N. and Troitzsch, K. (1999). Simulation for the Social Scientist, UK: Open University Press.

    Google Scholar 

  • Grimm, V. and Railsback, S.F. (2005). Individual-Based Modeling and Ecology, Princeton, NJ: Princeton University Press.

    Book  Google Scholar 

  • Grimm, V., Revilla, E., Berger, U., Jeltsch, F., Mooij, W.M., Railsback, S.F., Thulke, H.-H., Weiner, J., Wiegand, T. and DeAngelis, D.L. (2005). Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from ecology, Science 310(5750): 987–991.

    Article  Google Scholar 

  • Gurbaxani, V. and Whang, S. (1991). The Impact of Information Systems on Organizations and Markets, Communications of the ACM 34(1): 59–73.

    Article  Google Scholar 

  • Hersleb, J.D. and Mockus, A. (2003). An Empirical Study of Speed and Communication in Globally Distributed Software Development, IEEE Transactions on Software Engineering 29(6): 481–494.

    Article  Google Scholar 

  • Holland, J.H. (1995). Hidden Order: How adaptation Builds Complexity, Redwood City, CA: Addison-Wesley.

    Google Scholar 

  • Jarvenpaa, S., Knoll, K. and Leidner, D. (1998). Is Anybody Out There? Antecedents of Trust in Global Virtual Teams, Journal of Management Information Systems 14(4): 29–64.

    Article  Google Scholar 

  • Kreijns, K., Kirschner, P.A. and Jochems, W. (2003). Identifying the Pitfalls for Social Interaction in Computer-Supported Collaborative Learning Environments: A review of the research, Computers in Human Behavior 19(3): 335–353.

    Article  Google Scholar 

  • Lee, A. (1994). Electronic Mail as a Medium for Rich Communication: An empirical investigation using hermeneutic interpretation, MIS Quarterly 18: 143–157.

    Article  Google Scholar 

  • Leenders, R., van Engelen, J.M.L. and Kratzer, J. (2003). Virtuality, Communication, and New Product Team Creativity: A social network perspective, Journal of Engineering and Technology Management 20: 69–92.

    Article  Google Scholar 

  • March, J. (1991). Exploration and Exploitation in Organizational Learning, Organization Science 2(1): 122–125.

    Google Scholar 

  • McKelvey, B. (2002). Model-Centered Organization Science Epistemology, in J.A.C. Baum (ed.) The Blackwell Companion to Organizations, Oxford: Blackwell, pp. 752–780.

    Google Scholar 

  • Meyer, A.D., Gaba, V. and Colwell, K.A. (2005). Organizing Far from Equilibrium: Nonlinear change in organizational frontiers, Organization Science 16(5): 456–475.

    Article  Google Scholar 

  • Newlands, A., Anderson, A. and Mullin, J. (2003). Adapting Communicative Strategies to Computer-Mediated Communication: An analysis of task performance and dialogue structure, Applied Cognitive Psychology 17(3): 325–348.

    Article  Google Scholar 

  • Ngwenyama, O. and Lee, A. (1997). Communication Richness in Electronic Mail: Critical social theory and the contextuality of meaning, MIS Quarterly 21: 145–167.

    Article  Google Scholar 

  • Olson, G. and Olson, J. (2000). Distance Matters, Human Computer Interaction 15(2/3): 139–178.

    Article  Google Scholar 

  • Oreskes, N., Shrader-Frechette, K. and Belitz, K. (1994). Verification, Validation and Confirmation of Numerical Models in the Earth Sciences, Science 263(5147): 641–646.

    Article  Google Scholar 

  • Parunak, V., Savit, R and Riolo, R (1998). Agent-based Modeling i Equation-based Modeling: A case study and users guide, in Proceedings of Workshop on Multi-Agent Systems and Agent-based Simulation; Berlin: Springer.

  • Rykiel, E. (1996). Testing Ecological Models: The meaning of validation, Ecologila Modelling 90(3): 229–244.

    Article  Google Scholar 

  • Schein, E. (1990). Organizational Culture, American Psychologist 45(2): 109–119.

    Article  Google Scholar 

  • Schein, E.H. (1985). Organizational Culture and Leadership, San Francisco, California: Jossey-Bass Inc.

    Google Scholar 

  • Smith, A.D. and Rupp, W.T. (2002). Communication and Loyalty Among Knowledge Workers: A resource of the firm theory view, Journal of Knowledge Management 6(3): 250–261.

    Article  Google Scholar 

  • Sproull, L. and Kiesler, S. (1986). Reducing Social Context Cues: The case of electronic mail, Management Science 32: 1492–1512.

    Article  Google Scholar 

  • Valacich, J., Mennecke, B., Wachter, R and Wheeler, B (1994). Extensions to Media Richness Theory: A test of the task-media fit hypothesis, in Proceedings of the Twenty-Seven Annual Hawaii International Conference on System Sciences. 11–20.

  • van Laere, K. and Heene, A. (2003). Social Networks as a Source of Competitive Advantage for the Firm, Journal of Workplace Learning 15(6): 248–258.

    Article  Google Scholar 

  • Williams, E. (1977). Experimental Comparisons of Face-To-Face and Mediated Communication: A review, Psychological Bulletin 84(5): 963–976.

    Article  Google Scholar 

  • Zwijze-Koning, K.H. and de Jong, M.D.T. (2005). Auditing Information Structures in Organizations: A review of data collection techniques for network analysis, Organizational Research Methods 8(4): 429–453.

    Article  Google Scholar 

Download references

Acknowledgements

We wish to thank the Center for the Study of Complex Systems, University of Michigan, for providing computing resources and support for Rick L. Riolo. We also want to thank Robert Axelrod and Michael Cohen, University of Michigan, for their valuable comments regarding the development of the original model and three anonymous referees and the editors of JIT for their observations and suggestions, which helped us greatly improve this paper.

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Authors and Affiliations

  1. Faculty of Science and Technology, Universidad Adolfo Ibáñez, Balmaceda, Viña del Mar, Chile

    Enrique Canessa

  2. Center for the Study of Complex Systems, University of Michigan, Ann Arbor, MI, USA

    Rick L Riolo

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  1. Enrique Canessa
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  2. Rick L Riolo
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Correspondence to Enrique Canessa.

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Canessa, E., Riolo, R. An agent-based model of the impact of computer-mediated communication on organizational culture and performance: an example of the application of complex systems analysis tools to the study of CIS. J Inf Technol 21, 272–283 (2006). https://doi.org/10.1057/palgrave.jit.2000078

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