J 2023

A fuzzy group decision-making model for measurement of companies´ performance

PAVLAČKOVÁ, Martina, Ondřej PAVLAČKA a Tereza HORČIČKOVÁ

Základní údaje

Originální název

A fuzzy group decision-making model for measurement of companies´ performance

Autoři

PAVLAČKOVÁ, Martina (203 Česká republika, domácí), Ondřej PAVLAČKA (203 Česká republika) a Tereza HORČIČKOVÁ (203 Česká republika)

Vydání

Economic Computation and Economic Cybernetics Studies and Research, 2023, 0424-267X

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

10102 Applied mathematics

Stát vydavatele

Rumunsko

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Organizační jednotka

Moravská vysoká škola Olomouc

DOI

http://dx.doi.org/10.24818/18423264/57.2.23.08

UT WoS

001023056000008

Klíčová slova anglicky

Group Decision-making; Multi-criteria Evaluation; Fuzzy Consensus; Fuzzy Weighted Average Operation

Štítky

RIV2024
Změněno: 27. 3. 2024 10:51, Ing. Michaela Nováková

Anotace

V originále

In the paper, a fuzzy multi-criteria group evaluation model suitable for the measurement of companies & PRIME; performance is developed. The constructed model considers in addition to the traditionally used quantitative financial point of view also nonfinancial qualitative criteria such as Corporate Social Responsibility, innovation, or service level containing a considerable degree of uncertainty that can be appropriately modeled by the tools of fuzzy sets theory. Since the evaluations are often done by a group of experts with different opinions, our approach enables one to find at first a set of alternatives that are good enough for the sufficient quantity of relevant experts, and therefore to reach a consensus among evaluators. The best alternative is subsequently chosen from this set using a fuzzy weighted average operation. The model can be used for the comparison of companies in the same field, in one region, or to compare a company before and after managerial interventions.
Zobrazeno: 5. 11. 2024 10:48