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Financial performance evaluation by multi-criteria decision-making techniques

A thorough review of techniques for the experts invested in capital markets is necessary to take the decision-making process on the stock. When it comes to profiting from the capital markets, timing is crucial. The accurate evaluation of the financial performance of the businesses in the tourism sec...

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Detalles Bibliográficos
Autor principal: Türegün, Nida
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9092991/
https://www.ncbi.nlm.nih.gov/pubmed/35574203
http://dx.doi.org/10.1016/j.heliyon.2022.e09361
Descripción
Sumario:A thorough review of techniques for the experts invested in capital markets is necessary to take the decision-making process on the stock. When it comes to profiting from the capital markets, timing is crucial. The accurate evaluation of the financial performance of the businesses in the tourism sector is of great importance both in socio-economic and strategic terms in all countries in the world. As a result, the majority of investors use multi-criteria decision-making techniques to choose the best stocks. Thus, this paper aims to perform analysis on the TOPSIS, and VIKOR multi-criteria decision-making methods by taking base as an entropy method across companies that operate in the tourism industry and are publicly traded on the Borsa Istanbul by covering the data from 2018 to 2020, and to uncover the performance results of the companies and rank them by these main criteria. In the analysis results regarding the evaluation of the financial performance of tourism companies traded in BIST, it was seen that the ranking results made with TOPSIS and VIKOR methods were similar in 2018 and 2019. It is slightly different in 2020. It was seen that AVTUR was the most important alternative in both methods, whereas MARTI had the lowest ranking alternative. Moreover, MERIT, KSTUR, and PKENT have been determined as fluctuating companies.