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https://doi.org/10.1080/1331677X.2020.1736117

Pythagorean fuzzy combinative distance-based assessment with pure linguistic information and its application to financial strategies of multi-national companies

Jinming Zhou
Kevin W. Li
Tomas Baležentis orcid id orcid.org/0000-0002-3906-1711
Dalia Streimikiene


Puni tekst: engleski pdf 2.774 Kb

str. 974-998

preuzimanja: 446

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Sažetak

This article addresses the issue of selecting Financial Strategies in
Multi-National companies (F.S.M.). The F.S.M. typically has to consider
multiple factors involving multiple stakeholders and, hence,
can be handled by applying an appropriate Multi-Criteria Group
Decision-Making (M.C.G.D.M.) approach. To address this issue, we
develop an M.C.G.D.M. framework to tackle the F.S.M. problem. To
handle inherent uncertainty in business decisions as reflected by
linguistic reasoning, we embark on constructing a Linguistic
Pythagorean Fuzzy (L.P.F.) M.C.G.D.M. framework that is capable
of tackling both uncertain decision information and linguistic variables.
The proposed approach extends the combinative distancebased
assessment (C.O.D.A.S.) method into the L.P.F. environment,
and processes decision input expressed as Pythagorean fuzzy sets
(P.F.S.) and pure linguistic variables (rather than converting linguistic
information into fuzzy numbers). The developed L.P.F.-
C.O.D.A.S. technique aggregates the L.P.F. information and is
applied to the F.S.M. problem with uncertain linguistic information.
A comparative analysis is carried out to compare the results
obtained from the proposed L.P.F.-C.O.D.A.S. approach with those
from other extensions of C.O.D.A.S. Furthermore, a sensitivity analysis
is conducted to check the impact of changes in a distance
threshold parameter on the ranking results.

Ključne riječi

Linguistic Pythagorean fuzzy (L.P.F.) set; combinative distance-based assessment (C.O.D.A.S.); multi-criteria group decision-making (M.C.D.G.M.)

Hrčak ID:

254430

URI

https://hrcak.srce.hr/254430

Datum izdavanja:

9.2.2021.

Posjeta: 796 *