Skip to main content

Computational Organization Theory

Introduction

As inexpensive and massive amounts of computing power have rapidly become more widely available, the operational aspects of computational-based organizational research have become a reality. Today, the concepts of Computational Organization Theory (COT) can be easily implemented and practiced by an ever-increasingly larger group of researchers. Some foresee such computer-science related computational thinking (Wing 2006), as the future of all scholarly research, and COT is part of this broader trend.

COT involves the theorizing about, describing, understanding, and predicting the behavior of organizations and the process of organizing, using quantitative-based and structured approaches (computational, mathematical and logical models). This involves computational abstractions that are incorporated into organizational research and practice through COT tools, procedures, measures and knowledge.

The notion of an organization, as used here, spans the wide range of...

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-1-4419-1153-7_143
  • Chapter length: 7 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   849.99
Price excludes VAT (USA)
  • ISBN: 978-1-4419-1153-7
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Hardcover Book
USD   899.99
Price excludes VAT (USA)

References

  • Ashworth, M., & Carley, K. M. (2004). Toward unified organization theory: Perspectives on the state of computational modeling. Proceedings of the NAACSOS 2004 Conference, Pittsburgh, PA.

    Google Scholar 

  • Ashworth, M., & Carley, K. M. (2007). Can tools help unify organization theory? Perspectives on the state of computational modeling. Computational and Mathematical Organization Theory, 13(1), 89–111.

    CrossRef  Google Scholar 

  • Baligh, H. H., Burton, R. M., & Obel, B. (1990). Devising expert systems in organization theory: The organizational consultant. In M. Masuch (Ed.), Organization, management, and expert systems. Berlin: Walter De Gruyer.

    Google Scholar 

  • Baum, J., & Oliver, C. (1991). Institutional linkages and organizational mortality. Administrative Science Quarterly, 36, 187–218.

    CrossRef  Google Scholar 

  • Blau, P. M. (1970). A formal theory of differentiation in organizations. American Sociological Review, 35(2), 201–218.

    CrossRef  Google Scholar 

  • Blumer, H. (1969). Symbolic interactionism: Perspective and method. Englewood Cliffs, NJ: Prentice-Hall.

    Google Scholar 

  • Bond, A., & Gasser, L. (Eds.). (1988). Readings in distributed artificial intelligence. San Mateo, CA: Kaufmann.

    Google Scholar 

  • Burt, R. (1992). Structural holes: The social structure of competition. Boston: Harvard University Press.

    Google Scholar 

  • Burton, R. M., & Obel, B. (1996). Organization. In S. I. Gass & C. M. Harris (Eds.), Encyclopedia of operations research and management science. Norwood, MA: Kluwer Academic Publishers.

    Google Scholar 

  • Carley, K. M. (1991). A theory of group stability. American Sociological Review, 56(3), 331–354.

    CrossRef  Google Scholar 

  • Carley, K. M. (1992). Organizational learning and personnel turnover. Organization Science, 3(1), 20–46.

    CrossRef  Google Scholar 

  • Carley, K. M. (1995). Computational and mathematical organization theory: Perspective and directions. Computational and Mathematical Organization Theory, 1(1), 39–56.

    CrossRef  Google Scholar 

  • Carley, K. M., Kjaer-Hansen, J., Prietula, M., & Newell, A. (1992). Plural-soar: A prolegomenon to artificial agents and organizational behavior. In M. Masuch & M. Warglien (Eds.), Distributed intelligence: Applications in human organizations (pp. 87–118). Amsterdam: Elsevier Science.

    Google Scholar 

  • Carley, K. M., & Newell, A. (1994). The nature of the social agent. Journal of Mathematical Sociology, 19(4), 221–262.

    CrossRef  Google Scholar 

  • Carley, K. M., & Prietula, M. J. (Eds.). (1994). Computational organization theory. Hillsdale, IN: Lawrence Erlbaum Associates.

    Google Scholar 

  • Carley, K. M., & Svoboda, D. M. (1996). Modeling organizational adaptation as a simulated annealing process. Sociological Methods and Research, 25, 138–168.

    CrossRef  Google Scholar 

  • Cohen, M. D. (1986). Artificial intelligence and the dynamic performance of organizational designs. In J. G. March & R. Weissinger-Baylon (Eds.), Ambiguity and command: Organizational perspectives on military decision making (pp. 53–70). Marshfield, MA: Pitman.

    Google Scholar 

  • Cohen, M. D., March, J. G., & Olsen, J. P. (1972). A garbage can model of organizational choice. Administrative Science Quarterly, 17, 1–25.

    CrossRef  Google Scholar 

  • Cyert, R., & March, J. G. (1963). A behavioral theory of the firm. Englewood Cliffs, NJ: Prentice-Hall.

    Google Scholar 

  • Decker, K. (1996). TAEMS: A framework for environment centered analysis and design of coordination mechanisms. In G. M. P. O'Hare & N. R. Jennings (Eds.), Foundations of distributed artificial intelligence. New York: John Wiley.

    Google Scholar 

  • Durfee, E. H., & Montgomery, T. A. (1991). Coordination as distributed search in a hierarchical behavior space. IEEE Transactions on Systems, Man, and Cybernetics, 21, 1363–1378.

    CrossRef  Google Scholar 

  • Galbraith, J. (1973). Designing complex organizations. Reading, MA: Addison-Wesley.

    Google Scholar 

  • Gasser, L., & Huhns, M. N. (Eds.). (1989). Distributed artificial intelligence (Vol. 2). New York: Morgan Kaufmann.

    Google Scholar 

  • Gasser, L., & Majchrzak, A. (1992). HITOP-A: Coordination, infrastructure, and enterprise integration. Proceedings of the First International Conference on Enterprise Integration (pp. 373–378). Hilton Head, SC: MIT Press.

    Google Scholar 

  • Gasser, L., & Majchrzak, A. (1994). ACTION integrates manufacturing strategy, design, and planning. In P. Kidd & W. Karwowski (Eds.), Ergonomics of hybrid automated systems IV (pp. 133–136). Amsterdam: IOS Press.

    Google Scholar 

  • Gilbert, N., & Doran, J. (Eds.). (1994). Simulating societies: The computer simulation of social phenomena. London: UCL Press.

    Google Scholar 

  • Granovetter, M. (1985). Economic action and social structure: The problem of embeddedness. The American Journal of Sociology, 91, 481–510.

    CrossRef  Google Scholar 

  • Hannan, M. T., & Freeman, J. (1977). The population ecology of organizations. The American Journal of Sociology, 82, 929–964.

    CrossRef  Google Scholar 

  • Hannan, M. T., & Freeman, J. (1989). Organizational ecology. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Kang, M., Waisel, L. B., & Wallace, W. A. (1998). Team-soar: A model for team decision making. In M. Prietula, K. Carley, & L. Glasser (Eds.), Simulating organizations: Computational models of institutions and groups (pp. 23–45). Menlo Park, CA: AAAI Press/The MIT Press.

    Google Scholar 

  • Kaufer, D. S., & Carley, K. M. (1993). Communication at a distance: The effect of print on socio-cultural organization and change. Hillsdale, IN: Lawrence Erlbaum Associates.

    Google Scholar 

  • Krackhardt, D. (1987). Cognitive social structures. Social Networks, 9, 109–134.

    CrossRef  Google Scholar 

  • Lee, J-S., & Carley, K. M. (2004). OrgAhead: A computational model of organizational learning and decision making [Version 2.1.5] (Technical Report CMU-ISRI-04-117), Carnegie Mellon University, School of Computer Science, Institute for Software Research International.

    Google Scholar 

  • Lesser, D. D., & Corkill, D. D. (1988). Functionally accurate, cooperative distributed systems. In A. H. Bond & L. Gasser (Eds.), Readings in distributed artificial intelligence. San Mateo, CA: Morgan Kaufmann.

    Google Scholar 

  • Levinthal, D., & March, J. G. (1981). A model of adaptive organizational search. Journal of Economic Behavior and Organization, 2, 307–333.

    CrossRef  Google Scholar 

  • Levitt, R. E., Cohen, G. P., Kunz, J. C., Nass, C. I., Christiansen, T., & Jin, Y. (1994). The Virtual Design Team: Simulating how organization structure and information processing tools affect team performance. In K. M. Carley & M. J. Prietula (Eds.), Computational organization theory (pp. 1–18). Hillsdale, IN: Erlbaum.

    Google Scholar 

  • Majchrzak, A., & Gasser, L. (1991). On using artificial intelligence to integrate the design of organizational and process change in US manufacturing. Artificial Intelligence and Society, 5, 321–338.

    Google Scholar 

  • Majchrzak, A., & Gasser, L. (1992). HITOP-A: A tool to facilitate interdisciplinary manufacturing systems design. International Journal of Human Factors in Manufacturing, 2(3), 255–276.

    CrossRef  Google Scholar 

  • Malone, T. W. (1986). Modeling coordination in organizations and markets. Management Science, 33, 1317–1332.

    CrossRef  Google Scholar 

  • March, J., & Simon, H. (1958). Organizations. New York: John Wiley.

    Google Scholar 

  • Nersessian, N. J. (1992). How do scientists think? Capturing the dynamics of conceptual change in science. In R. N. Giere (Ed.), Cognitive models of science (Vol. 15). Minneapolis, MN: Minnesota Press.

    Google Scholar 

  • Pfeffer, J., & Salancik, G. R. (1978). The external control of organizations: A resource dependence perspective. New York: Harper and Row.

    Google Scholar 

  • Powell, W. W., & DiMaggio, P. J. (1991). The new institutionalism in organizational analysis. Chicago: University of Chicago Press.

    Google Scholar 

  • Prietula, M. J., Carley, K. M., & Gasser, L. (Eds.). (1998). Simulating organizations: Computational models of institutions and groups. Menlo Park, CA: AAAI Press/The MIT Press.

    Google Scholar 

  • Salancik, G. R., & Pfeffer, J. (1978). A social information professing approach to job attitudes and task design. Administrative Science Quarterly, 23, 224–253.

    CrossRef  Google Scholar 

  • Salanick, G. R., & Leblebici, H. (1998). Variety and form in organizing transactions: A generative grammar of organization. Research in the Sociology of Organizations, 6, 1–31.

    Google Scholar 

  • Simon, H. A. (1947). Administrative behavior. New York: Free Press.

    Google Scholar 

  • Stryker, S. (1980). Symbolic interactionism: A social structure version. Menlo Park, CA: Benjamin/Cummings Publishing.

    Google Scholar 

  • Stuart, T. E., & Podolny, J. M. (1996). Local search and the evolution of technological capabilities. Strategic Management Journal, 17, 21–38.

    CrossRef  Google Scholar 

  • Thompson, J. D. (1967). Organizations in action. New York: McGraw-Hill.

    Google Scholar 

  • Waisel, L., Wallace, W. A., & Willemain, T. (1998). Using diagrammatic reasoning in mathematical modeling: The sketches of expert modelers. Proceedings of the AAAI 1997 Fall Symposium on Reasoning with Diagrammatic Representations II. Menlo Park, CA: AAAI Press.

    Google Scholar 

  • Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. New York: Cambridge University Press.

    CrossRef  Google Scholar 

  • Wasserman, S., & Galaskiewicz, J. (Eds.). (1994). Advances in social network analysis: Research in the social and behavioral sciences. Thousand Oaks, CA: Sage.

    Google Scholar 

  • Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35.

    CrossRef  Google Scholar 

  • Zhiang, L., & Carley, K. (1995). DYCORP: A computational framework for examining organizational performance under dynamic conditions. Journal of Mathematical Sociology, 20(2–3), 193–218.

    Google Scholar 

  • Zweben, M., & Fox, M. S. (Eds.). (1994). Intelligent scheduling. San Mateo, CA: Morgan Kaufmann.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Terrill L. Frantz .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2013 Springer Science+Business Media New York

About this entry

Cite this entry

Frantz, T.L., Carley, K.M., Wallace, W.A. (2013). Computational Organization Theory. In: Gass, S.I., Fu, M.C. (eds) Encyclopedia of Operations Research and Management Science. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-1153-7_143

Download citation