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Modeling information system availability by using bayesian belief network approach

Author

Listed:
  • Semir Ibrahimovic

    (BBI Bank Sarajevo and School of Economics and Business Sarajevo, City of Sarajevo, Bosnia and Herzegovina)

  • Nijaz Bajgoric

    (School of Economics and Business Sarajevo, City of Sarajevo, Bosnia and Herzegovina)

Abstract

Modern information systems are expected to be always-on by providing services to end-users, regardless of time and location. This is particularly important for organizations and industries where information systems support real-time operations and mission-critical applications that need to be available on 24 x 7 x 365 basis.Examples of such entities include process industries, telecommunications, healthcare, energy, banking, electronic commerce and a variety of cloud services. This article presents a modified Bayesian Belief Network model for predicting information systemavailability, introduced initially by Franke, U. and Johnson, P.(in article “Availability of enterprise IT systems –an expert-basedBayesian model”. Software Quality Journal 20(2), 369-394, 2012)based on a thorough review of several dimensions of the information system availability, we proposed a modified set of determinants. The model is parameterized by using probability elicitation process with the participation of experts from thefinancial sectorof Bosnia and Herzegovina. The model validation was performed using Monte-Carlo simulation.

Suggested Citation

  • Semir Ibrahimovic & Nijaz Bajgoric, 2016. "Modeling information system availability by using bayesian belief network approach," Interdisciplinary Description of Complex Systems - scientific journal, Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu, vol. 14(2), pages 125-138.
    • Handle: RePEc:zna:indecs:v:14:y:2016:i:2:p:125-138
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    References listed on IDEAS

    as
    1. Ulrich Faisst & Oliver Prokein, 2008. "Management of Security Risks – A Controlling Model for Banking Companies," International Handbooks on Information Systems, in: Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), Handbook on Information Technology in Finance, chapter 4, pages 73-93, Springer.
    2. Neil, Martin & Fenton, Norman, 2008. "Using Bayesian networks to model the operational risk to information technology infrastructure in financial institutions," Journal of Financial Transformation, Capco Institute, vol. 22, pages 131-138.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    information systems; business continuity; availability; Bayesian belief network; Monte-Carlo simulation;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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