Multicriteria decision support method CRITIC-WASPAS-N in the analysis of transportation companies on the stock exchange in the brazilian market

• Published in: GeSec : Revista de Gestão e Secretariado Vol. 14; no. 10; pp. 17560 - 17578
• Main Authors: Dos Santos, Raphael Nascimento, Da Silva, Paulo Afonso Lopes
• Format: Journal Article
• Language: English
• Published: São Paulo Sindicato das Secretárias do Estado de São Paulo 11.10.2023
• Subjects: Investments; Logistics; Securities markets; Stock exchanges
• ISSN: 2178-9010; 2178-9010
• DOI: 10.7769/gesec.v14i10.2958

The aim of this article is to identify how multi-criteria decision support (MCDA) can help investment portfolios in transportation and logistics companies on the stock exchange. To develop this article, a stratification was carried out within BM&FBOVESPA with logistics and transportation companies presented on the Brazilian Stock Exchange. 16 transportation companies in the fundamentus data source. The data was collected from 5 financial indicators, selected according to the Principal Component Analysis (PCA) carried out by Basilio et al. (2018). The CRITIC method was used to generate the weights and normalize the decision matrix and the WASPAS method is used to classify assets. At the end of this stage, it was possible to classify the best alternatives for investing in transportation. After constructing portfolios, it was possible to see which company was most suitable for positive returns on investment. The result is a safe company to invest in logistics and transportation infrastructure in the Brazilian stock market through MCDA analysis and a sensitivity analysis. Research limitations/implications - Since the study is focused only on logistics and transportation companies, the study limited the alternatives with only 15 companies.  An investor in transportation infrastructure economics can apply the conclusions of this article to other segments of the stock market. This study presents a methodology by merging the CRITIC method for generating weights and normalization and WASPAS with the normalization of the CRITIC method to build efficient investment portfolios.