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

Dados Bibliográficos

ID15067656
AutoresJinming Zhou (0000-0002-1485-6884, Anhui Polytechnic University), Kui-Wai Li (0000-0001-7756-9797, University of Windsor), Tomas Balezentis (0000-0002-3906-1711, Lithuanian Institute of Agrarian Economics, autor correspondente), Dalia Streimikiene (0000-0002-3247-9912, Lithuanian Institute of Agrarian Economics)
Ano2020
Volume33
Fascículo1
Páginas974-998
Data de publicação2020-01-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoEconomic Research-Ekonomska Istraživanja (JOURNAL)
Identificadores do periódicoISSN: 1331-677X • E-ISSN: 1848-9664
EditoraInforma UK Limited (PUBLISHER • GB)
DOI10.1080/1331677x.2020.1736117
OpenAlexW3014409699
IdiomaEN
Referências citadas41

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 distance-based 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

Business · Fuzzy logic · Linguistics · Natural language processing · Pythagorean theorem · Advanced Algebra and Logic · Computer Science · Mathematics · Multi-Criteria Decision Making · Philosophy · Rough Sets and Fuzzy Logic · Artificial Intelligence

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