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Achieving Business Excellence by Optimizing Corporate Forensic Readiness

Author

Listed:
  • Gojko Grubor

    (Sinergija University, Bijeljina, Bosnia and Herzegovina)

  • Ivan Barac

    (Singidunum University, Beograd, Serbia)

  • Nataša Simeunovic

    (Sinergija University, Bijeljina, Bosnia and Herzegovina)

  • Nenad Ristic

    (Sinergija University, Bijeljina, Bosnia and Herzegovina)

Abstract

In order to improve their business excellence, all organizations, despite their size (small, medium or large one) should manage their risk of fraud. Fraud, in today’s world, is often committed by using computers and can only be revealed by digital forensic investigator. Not even small or medium-sized companies are secure from fraud. In the light of recent financial scandals that literary demolished not just economies of specific countries but entire world economy, we propose in this paper an optimal model of corporative computer incident digital forensic investigation (CCIDFI) by using adopted mathematic model of the greed MCDM – multi-criteria decision-making method and the Expert Choice software tool for multi-criteria optimization of the CCIDFI readiness. Proposed model can, first of all, help managers of small and medium-sized companies to justify their decisions to employ digital forensic investigators and include them in their information security teams in order to choose the optimal CCIDFI model and improve forensic readiness in the computer incident management process that will result with minimization of potential losses of company in the future and improve its business quality.

Suggested Citation

  • Gojko Grubor & Ivan Barac & Nataša Simeunovic & Nenad Ristic, 2017. "Achieving Business Excellence by Optimizing Corporate Forensic Readiness," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 19(44), pages 197-197, February.
  • Handle: RePEc:aes:amfeco:v:s10:y:2017:i:18:p:197
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    References listed on IDEAS

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    1. H. Roland Weistroffer & Charles H. Smith & Subhash C. Narula, 2005. "Multiple Criteria Decision Support Software," International Series in Operations Research & Management Science, in: Multiple Criteria Decision Analysis: State of the Art Surveys, chapter 0, pages 989-1009, Springer.
    2. Murat Köksalan & Jyrki Wallenius & Stanley Zionts, 2016. "An Early History of Multiple Criteria Decision Making," International Series in Operations Research & Management Science, in: Salvatore Greco & Matthias Ehrgott & José Rui Figueira (ed.), Multiple Criteria Decision Analysis, edition 2, chapter 0, pages 3-17, Springer.
    3. Keeney,Ralph L. & Raiffa,Howard, 1993. "Decisions with Multiple Objectives," Cambridge Books, Cambridge University Press, number 9780521438834, September.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    computer incident; forensic readiness; forensic alternatives; forensic criteria; greed multi-criteria method; Expert Choice evaluation.;
    All these keywords.

    JEL classification:

    • C39 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Other
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management

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