Quantifying IT Impacts on Organizational Structure and Business Value with Extended Influence Diagrams

  • Pia Gustafsson
  • Ulrik Franke
  • David Höök
  • Pontus Johnson
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 15)

Abstract

This paper presents a framework for analysis of how IT systems add business value by causally affecting the structure of organizations. The well established theory of organizational behavior developed by Mintzberg combined with more recent research on business value of IT is used to develop a quantitative theoretical framework showing which business values are affected by IT in relation to the organizational structure. This framework, which is based upon a qualitative equivalent developed in an earlier paper, describes relationships in an Extended Influence Diagram for quantified conditional probability tables and open up for an empirical appliance. Hence obtained data can be mathematically expressed for more sound assessments. The intention is to create a fully functioning tool for analyses of what kind of IT system should be used by an organization with a given structure to maximize its business value.

Keywords

IT benefits organizational structure Mintzberg business value 

References

  1. 1.
    Brynjolfsson, B.: The Productivity Paradox of Information Technology. Communications of the ACM 36(1), 67–77 (1993)Google Scholar
  2. 2.
    Bergsjö, D., Malvius, D.: A Model to Evaluate Efficiency, Quality, and Innovation through User Satisfaction with Information Management Systems. In: Proceedings of CSER 2007, Hoboken, March 14-16 (2007)Google Scholar
  3. 3.
    Sneller, L., Bots, J.: A Review of Quantitative IT Value Research. Nyenrode Business University, The Netherlands (2006)Google Scholar
  4. 4.
    Dahlgren, J.: Real options and Flexibility in Organizational Design. In: Proceedings of CSER 2007, Hoboken, March 14 -16 (2007)Google Scholar
  5. 5.
    Fulk, J., DeSanctis, G.: Electronic Communication and Changing Organizational Forms. Organization Science 6(4), 337–349 (1995)CrossRefGoogle Scholar
  6. 6.
    Andersen, T.J.: Information technology, strategic decision making approaches and organizational performance in different industrial settings. The Journal of Strategic Information Systems 10(2), 101–119 (2001)CrossRefGoogle Scholar
  7. 7.
    Gurbaxani, V., Whang, S.: The impact of information systems on organizations and markets. Communications of the ACM 34(1), 59–73 (1991)CrossRefGoogle Scholar
  8. 8.
    Mintzberg, H.: The Structuring of Organizations. Prentice-Hall, Upper Saddle River (1979)Google Scholar
  9. 9.
    Shafer, G.: A mathematical theory of evidence. Princeton University Press, Princeton (1976)Google Scholar
  10. 10.
    Yang, J.-B.: Rule and utility based evidential reasoning approach for multiattribute decision analysis under uncertainties. European Journal of Operational Research 133, 31–61 (2001)CrossRefGoogle Scholar
  11. 11.
    Yu, E.S.K., Mylopoulos, J., Lesp, Y.: Ai models for business process reengineering. IEEE Expert: Intelligent Systems and Their Applications 11(4), 16–23 (1996)CrossRefGoogle Scholar
  12. 12.
    Gustafsson, P., Franke, U., Johnson, P., Lilliesköld, J.: Identifying IT impacts on organizational structure and business value. In: Proceedings of the Third International Workshop on Business/IT Alignment and Interoperability, pp. 44–57 (2008)Google Scholar
  13. 13.
    Johnson, P., Lagerström, R., Närman, P., Simonsson, M.: Enterprise Architecture Analysis with Extended Influence Diagrams. Information System Frontiers 9(2-3), 163–180 (2007)CrossRefGoogle Scholar
  14. 14.
    Henrion, M.: Some practical issues in constructing belief networks. In: Kanal, L.N., Levitt, T.S., Lemmer, J.F. (eds.) Uncertainty in Artificial Intelligence, vol. 3, pp. 161–173. Elsevier Science Publishers B.V., North Holland (1989)Google Scholar
  15. 15.
    Pearl, J.: Fusion, propagation and structuring in belief networks. Artificial Intelligence 29, 241–288 (1986)CrossRefGoogle Scholar
  16. 16.
    Katz, D., Kahn, R.: Organizations and the system concept - Classics of Organization Theory, Thomson Learning (1966)Google Scholar
  17. 17.
    Hannan, M.T., Freeman, J.: The Population Ecology of Organizations - American Journal of Sociology. Chicago Press (1977)Google Scholar
  18. 18.
    Martin, J.: Deconstructing organizational taboos: The suppression of gender conflict in organizations. Organization Science 1, 339–359 (1990)CrossRefGoogle Scholar
  19. 19.
    Shachter, R.: Evaluating influence diagrams. Operations Research Institute for Operations Research and the Management Sciences 34(6), 871–882 (1986)Google Scholar
  20. 20.
    Shachter, R.: Probabilistic inference and influence diagrams. Operations Research 36(4), 36–40 (1988)CrossRefGoogle Scholar
  21. 21.
    Neapolitan, R.: Learning Bayesian Networks. Prentice-Hall, Inc., Upper Saddle River (2003)Google Scholar
  22. 22.
    Jensen, F.V.: Bayesian Networks and Decision Graphs. Springer, New York (2001)CrossRefGoogle Scholar
  23. 23.
    Lagerström, R., Johnson, P., Närman, P.: Extended Influence Diagram Generation. In: Enterprise Interoperability II – New Challenges and Approaches, pp. 599–602. Springer, London (2007)CrossRefGoogle Scholar
  24. 24.
    Druzdzel, M., van der Gaag, L.: Building probabilistic networks: Where do the numbers come from? IEEE Transactions on knowledge and data engineering 12(4), 289–299 (2000)CrossRefGoogle Scholar
  25. 25.
    Keeney, R., von Winterfeldt, D.: Eliciting Probabilities from Experts in Complex Technical Problems. IEEE Transactions on engineering management 38(3), 191–201 (1991)CrossRefGoogle Scholar
  26. 26.
    Saaty, T.L.: Axiomatic Foundation of the Analytic Hierarchy Process. Management Science 32(7), 841–855 (1986)CrossRefGoogle Scholar
  27. 27.
    Laurene, V.: Fausett, Fundamentals of Neural Networks. Prentice Hall, Englewood Cliffs (1994)Google Scholar
  28. 28.
    Gammelgård, M., Ekstedt, M., Gustafsson, P.: A Categorization of Benefits From IS/IT Investments. In: Proceedings of the 13th European Conference on Information Technology Evaluation, ECITE (2006)Google Scholar
  29. 29.
    Farbey, B., Land, F., Targett, D.: How to assess your IT investment: A study of methods and practice. Butterworth-Heineman Ltd., Oxford (1993)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2008

Authors and Affiliations

  • Pia Gustafsson
    • 1
  • Ulrik Franke
    • 1
  • David Höök
    • 1
  • Pontus Johnson
    • 1
  1. 1.Industrial Information and Control SystemsRoyal Institute of TechnologyStockholmSweden

Personalised recommendations