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.
Chapter PDF
References
Brynjolfsson, B.: The Productivity Paradox of Information Technology. Communications of the ACM 36(1), 67–77 (1993)
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)
Sneller, L., Bots, J.: A Review of Quantitative IT Value Research. Nyenrode Business University, The Netherlands (2006)
Dahlgren, J.: Real options and Flexibility in Organizational Design. In: Proceedings of CSER 2007, Hoboken, March 14 -16 (2007)
Fulk, J., DeSanctis, G.: Electronic Communication and Changing Organizational Forms. Organization Science 6(4), 337–349 (1995)
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)
Gurbaxani, V., Whang, S.: The impact of information systems on organizations and markets. Communications of the ACM 34(1), 59–73 (1991)
Mintzberg, H.: The Structuring of Organizations. Prentice-Hall, Upper Saddle River (1979)
Shafer, G.: A mathematical theory of evidence. Princeton University Press, Princeton (1976)
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)
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)
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)
Johnson, P., Lagerström, R., Närman, P., Simonsson, M.: Enterprise Architecture Analysis with Extended Influence Diagrams. Information System Frontiers 9(2-3), 163–180 (2007)
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)
Pearl, J.: Fusion, propagation and structuring in belief networks. Artificial Intelligence 29, 241–288 (1986)
Katz, D., Kahn, R.: Organizations and the system concept - Classics of Organization Theory, Thomson Learning (1966)
Hannan, M.T., Freeman, J.: The Population Ecology of Organizations - American Journal of Sociology. Chicago Press (1977)
Martin, J.: Deconstructing organizational taboos: The suppression of gender conflict in organizations. Organization Science 1, 339–359 (1990)
Shachter, R.: Evaluating influence diagrams. Operations Research Institute for Operations Research and the Management Sciences 34(6), 871–882 (1986)
Shachter, R.: Probabilistic inference and influence diagrams. Operations Research 36(4), 36–40 (1988)
Neapolitan, R.: Learning Bayesian Networks. Prentice-Hall, Inc., Upper Saddle River (2003)
Jensen, F.V.: Bayesian Networks and Decision Graphs. Springer, New York (2001)
Lagerström, R., Johnson, P., Närman, P.: Extended Influence Diagram Generation. In: Enterprise Interoperability II – New Challenges and Approaches, pp. 599–602. Springer, London (2007)
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)
Keeney, R., von Winterfeldt, D.: Eliciting Probabilities from Experts in Complex Technical Problems. IEEE Transactions on engineering management 38(3), 191–201 (1991)
Saaty, T.L.: Axiomatic Foundation of the Analytic Hierarchy Process. Management Science 32(7), 841–855 (1986)
Laurene, V.: Fausett, Fundamentals of Neural Networks. Prentice Hall, Englewood Cliffs (1994)
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)
Farbey, B., Land, F., Targett, D.: How to assess your IT investment: A study of methods and practice. Butterworth-Heineman Ltd., Oxford (1993)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 IFIP International Federation for Information Processing
About this paper
Cite this paper
Gustafsson, P., Franke, U., Höök, D., Johnson, P. (2008). Quantifying IT Impacts on Organizational Structure and Business Value with Extended Influence Diagrams. In: Stirna, J., Persson, A. (eds) The Practice of Enterprise Modeling. PoEM 2008. Lecture Notes in Business Information Processing, vol 15. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89218-2_11
Download citation
DOI: https://doi.org/10.1007/978-3-540-89218-2_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89217-5
Online ISBN: 978-3-540-89218-2
eBook Packages: Computer ScienceComputer Science (R0)