TY - JOUR
T1 - Granular fuzzy pay-off method for real option valuation
AU - Cabrerizo, Francisco
AU - Heikkilä, Markku
AU - Mezei, Jozsef
AU - Juan Antonio, Morente-Molinera
AU - Enrique, Herrera-Viedma
AU - Carlsson, Christer
PY - 2020/11/30
Y1 - 2020/11/30
N2 - In the last decade, the fuzzy pay-off method has emerged as a widely used alternative approach for real option valuation thanks to its simplicity that makes it easily approachable by practitioners from various application domains. In this study, a new direction for real option valuation is pursued by proposing a granular fuzzy pay-off method. We motivate the proposal by discussing how the extension of the original approach with granular representation can further improve the fuzzy pay-off method. The design of the granular fuzzy pay-off method is founded on the principle of justifiable granularity, which in turn relies on numeric data to build information granules that are semantically sound and experimentally justified. To illustrate the method, a case study in R&D investment in manufacturing is worked out. The extended granular fuzzy pay-off method improves performance and usability in cases with uncertainty.
AB - In the last decade, the fuzzy pay-off method has emerged as a widely used alternative approach for real option valuation thanks to its simplicity that makes it easily approachable by practitioners from various application domains. In this study, a new direction for real option valuation is pursued by proposing a granular fuzzy pay-off method. We motivate the proposal by discussing how the extension of the original approach with granular representation can further improve the fuzzy pay-off method. The design of the granular fuzzy pay-off method is founded on the principle of justifiable granularity, which in turn relies on numeric data to build information granules that are semantically sound and experimentally justified. To illustrate the method, a case study in R&D investment in manufacturing is worked out. The extended granular fuzzy pay-off method improves performance and usability in cases with uncertainty.
KW - Real options
KW - Fuzzy pay-off method
KW - Granular computing
KW - Real options
KW - Fuzzy pay-off method
KW - Granular computing
KW - Real options
KW - Fuzzy pay-off method
KW - Granular computing
UR - http://www.scopus.com/inward/record.url?scp=85086499806&partnerID=8YFLogxK
U2 - 10.1016/j.eswa.2020.113597
DO - 10.1016/j.eswa.2020.113597
M3 - Article
SN - 0957-4174
VL - 159
SP - –
JO - Expert Systems with Applications
JF - Expert Systems with Applications
M1 - 113597
ER -