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Real options valuation of an IoT based healthcare device with interval Type-2 fuzzy numbers

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  • Tolga, A. Cagri

Abstract

Medical devices have attained increasing importance in diagnosis and treatment in the healthcare system in recent years due to technological advancements. Along with this progress, the IoT property in these devices reduces the supply time, which is very critical in increasing their up periods. Often, certain medical devices used in treatment require a major portion of the investment. Such huge capital goods are generally irreversible investments. Depending on the strategic view and irreversibility, medical device assessment requires a sophisticated evaluation method called real options. However, there are many ambiguities during the investment period and while gathering the data for the evaluation. Interval type-2 fuzzy logic fits like a glove for such vague conditions and lack of data. In this study, an interval type-2 fuzzy set integrated real option analysis is offered for medical treatment device evaluation. Possibilistic mean value and possibilistic variance of interval type-2 fuzzy sets are found for the purpose of the real options analysis. This offered method is applied to a real case in a healthcare system. Sensitivity analysis provides many different viewpoints. At the end of the procedure, the institution decides whether to perform the investment now or one year later.

Suggested Citation

  • Tolga, A. Cagri, 2020. "Real options valuation of an IoT based healthcare device with interval Type-2 fuzzy numbers," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    • Handle: RePEc:eee:soceps:v:69:y:2020:i:c:s0038012118303616
    DOI: 10.1016/j.seps.2019.02.008
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    References listed on IDEAS

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    1. Rosella Levaggi & Moretto Michele, 2008. "Investment In Hospital Care Technology Under Different Purchasing Rules: A Real Option Approach," Bulletin of Economic Research, Wiley Blackwell, vol. 60(2), pages 159-181, April.
    2. Robert C. Merton, 2005. "Theory of rational option pricing," World Scientific Book Chapters, in: Sudipto Bhattacharya & George M Constantinides (ed.), Theory Of Valuation, chapter 8, pages 229-288, World Scientific Publishing Co. Pte. Ltd..
    3. Joyce Craig & Louise Carr & John Hutton & Julie Glanville & Cynthia Iglesias & Andrew Sims, 2015. "A Review of the Economic Tools for Assessing New Medical Devices," Applied Health Economics and Health Policy, Springer, vol. 13(1), pages 15-27, February.
    4. Chen, Ting-Yu & Chang, Chien-Hung & Rachel Lu, Jui-fen, 2013. "The extended QUALIFLEX method for multiple criteria decision analysis based on interval type-2 fuzzy sets and applications to medical decision making," European Journal of Operational Research, Elsevier, vol. 226(3), pages 615-625.
    5. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    6. T Sloan, 2010. "First, do no harm? A framework for evaluating new versus reprocessed medical devices," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(2), pages 191-201, February.
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    Cited by:

    1. Jorge de Andrés-Sánchez, 2023. "Fuzzy Random Option Pricing in Continuous Time: A Systematic Review and an Extension of Vasicek’s Equilibrium Model of the Term Structure," Mathematics, MDPI, vol. 11(11), pages 1-21, May.
    2. Zhang, Cheng & Gong, Xiaomin & Zhang, Jingshu & Chen, Zhiwei, 2023. "Dynamic portfolio allocation for financial markets: A perspective of competitive-cum-compensatory strategy," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 84(C).

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