TY - GEN
T1 - Interval-Valued Credibilistic Real Options Modeling Under Optimism-Pessimism Level
AU - Kinnunen, Jani
AU - Georgescu, Irina
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2022
Y1 - 2022
N2 - Fuzzy real options analysis has advanced greatly during the last decade, specifically, through the development of so-called fuzzy pay-off techniques. The practicality and intuitiveness of these methods allow their straightforward integration into any spreadsheet or other evaluation systems for easy applications of real options thinking to real investments and strategies in industry and to public policy. Real options valuation models are capable to reflect the value of flexibility, i.e., the inherent optional possible actions, which managers can take during the investment period or in public policy settings. Traditional NPV methods cannot value such optionalities. Fuzzy modeling is shown to account for high uncertainty and imprecision under which an expert evaluation is conducted. This paper generalizes the credibilistic pay-off method for real options valuation using interval-valued fuzzy numbers, IVFNs, by means of mλ -measure for the optimism–pessimism level of an expert analyst. The mλ -measure is defined using necessity and possibility measures to correspond to the optimism–pessimism level. Real options values, ROVs, will be obtained using the λ-parameter and fuzzy numbers. Similarly, ROVs are obtained using IVFNs. This paper introduces a novel credibilistic real options model, which is based on the optimism–pessimism measure and IVFNs. The model outcomes are compared to the original credibilistic real options model through a numerical case example in a merger and acquisition context.
AB - Fuzzy real options analysis has advanced greatly during the last decade, specifically, through the development of so-called fuzzy pay-off techniques. The practicality and intuitiveness of these methods allow their straightforward integration into any spreadsheet or other evaluation systems for easy applications of real options thinking to real investments and strategies in industry and to public policy. Real options valuation models are capable to reflect the value of flexibility, i.e., the inherent optional possible actions, which managers can take during the investment period or in public policy settings. Traditional NPV methods cannot value such optionalities. Fuzzy modeling is shown to account for high uncertainty and imprecision under which an expert evaluation is conducted. This paper generalizes the credibilistic pay-off method for real options valuation using interval-valued fuzzy numbers, IVFNs, by means of mλ -measure for the optimism–pessimism level of an expert analyst. The mλ -measure is defined using necessity and possibility measures to correspond to the optimism–pessimism level. Real options values, ROVs, will be obtained using the λ-parameter and fuzzy numbers. Similarly, ROVs are obtained using IVFNs. This paper introduces a novel credibilistic real options model, which is based on the optimism–pessimism measure and IVFNs. The model outcomes are compared to the original credibilistic real options model through a numerical case example in a merger and acquisition context.
KW - Credibility theory
KW - Fuzzy real options
KW - Interval-valued fuzzy numbers
KW - Mergers and acquisitions
KW - Optimism-pessimism measure
UR - http://www.scopus.com/inward/record.url?scp=85121598776&partnerID=8YFLogxK
U2 - 10.1007/978-981-16-5120-5_42
DO - 10.1007/978-981-16-5120-5_42
M3 - Conference contribution
AN - SCOPUS:85121598776
SN - 978-981-16-5119-9
T3 - Lecture Notes in Networks and Systems
SP - 551
EP - 562
BT - Proceedings of International Conference on Data Science and Applications
A2 - Saraswat, Mukesh
A2 - Roy, Sarbani
A2 - Chowdhury, Chandreyee
A2 - Gandomi, Amir H.
PB - Springer Science and Business Media Deutschland GmbH
T2 - 2nd International Conference on Data Science and Applications, ICDSA 2021
Y2 - 10 April 2021 through 11 April 2021
ER -