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Valuing the flexibility of investing in security process innovations

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  • Khansa, Lara
  • Liginlal, Divakaran

Abstract

In this paper, we develop a decision model of a firm's optimal strategy for investment in security process innovations (SPIs) when confronted with a sequence of malicious attacks. The model incorporates real options as a methodology to capture the flexibility embedded in such investment decisions. SPIs, when seamlessly integrated with the organization's overall business dynamics, induce organizational learning and provide the flexibility of switching to more suitable technologies as the environment of malicious attacks changes. The theoretical contribution of this paper is a mathematical model of the invest-to-learn and switching options generated upon early investment in flexible SPIs. The practical significance of the paper is the application of a binomial lattice model to approximate the continuous-time model, resulting in an easy to use decision aid for managers.

Suggested Citation

  • Khansa, Lara & Liginlal, Divakaran, 2009. "Valuing the flexibility of investing in security process innovations," European Journal of Operational Research, Elsevier, vol. 192(1), pages 216-235, January.
    • Handle: RePEc:eee:ejores:v:192:y:2009:i:1:p:216-235
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    Cited by:

    1. Khansa, Lara & Liginlal, Divakaran, 2012. "Whither information security? Examining the complementarities and substitutive effects among IT and information security firms," International Journal of Information Management, Elsevier, vol. 32(3), pages 271-281.
    2. Daniel Schatz & Rabih Bashroush, 0. "Economic valuation for information security investment: a systematic literature review," Information Systems Frontiers, Springer, vol. 0, pages 1-24.
    3. Michel Benaroch, 2018. "Real Options Models for Proactive Uncertainty-Reducing Mitigations and Applications in Cybersecurity Investment Decision Making," Information Systems Research, INFORMS, vol. 29(2), pages 315-340, June.
    4. Niu, Wenju & Shen, Houcai, 2022. "Investment in process innovation in supply chains with knowledge spillovers under innovation uncertainty," European Journal of Operational Research, Elsevier, vol. 302(3), pages 1128-1141.
    5. Jürgen Harrer & Andreas Wald, 2016. "Levers of enterprise security control: a study on the use, measurement and value contribution," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 27(1), pages 7-32, February.
    6. Lara Khansa & Reza Barkhi & Soumya Ray & Zachary Davis, 2018. "Cyberloafing in the workplace: mitigation tactics and their impact on individuals’ behavior," Information Technology and Management, Springer, vol. 19(4), pages 197-215, December.
    7. Zhang, Sizhe & Cardin, Michel-Alexandre, 2017. "Flexibility and real options analysis in emergency medical services systems using decision rules and multi-stage stochastic programming," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 107(C), pages 120-140.
    8. Lee, Sangjae & Costello, Francis Joseph & Lee, Kun Chang, 2021. "Hierarchical balanced scorecard-based organizational goals and the efficiency of controls processes," Journal of Business Research, Elsevier, vol. 132(C), pages 270-288.
    9. Daniel Schatz & Rabih Bashroush, 2017. "Economic valuation for information security investment: a systematic literature review," Information Systems Frontiers, Springer, vol. 19(5), pages 1205-1228, October.
    10. Trigeorgis, Lenos & Tsekrekos, Andrianos E., 2018. "Real Options in Operations Research: A Review," European Journal of Operational Research, Elsevier, vol. 270(1), pages 1-24.
    11. Nadarajah, Selvaprabu & Margot, François & Secomandi, Nicola, 2017. "Comparison of least squares Monte Carlo methods with applications to energy real options," European Journal of Operational Research, Elsevier, vol. 256(1), pages 196-204.

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