Fatores socioeconômicos, políticos e institucionais na determinação da eficiência logística dos países

The globalization of markets, driven by the evolution of buying and selling technologies, has made monitoring the logistical efficiency of countries essential. This measurement also allows the main players in global logistics to compare themselves and helps governments and policy makers in carrying...

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Bibliographic Details
Main Author: Bernardino, Flávia Ferreira Marques
Other Authors: Tavares, Marcelo, http://lattes.cnpq.br/4142478901587907, Brasil, Janaina Siegler Marques Batista, http://lattes.cnpq.br/7912595631597081, Martins, Ricardo Silveira, http://lattes.cnpq.br/4225299693291986, Paula, Verônica Angélica Freitas de, http://lattes.cnpq.br/0116513470932691, Pimenta, Márcio Lopes, http://lattes.cnpq.br/3026927581342826
Format: Thesis
Language:Portuguese
Published: Universidade Federal de Uberlândia 2021
Subjects:
DEA
Online Access:https://repositorio.ufu.br/handle/123456789/32591
https://doi.org/10.14393/ufu.te.2021.372
Description
Summary:The globalization of markets, driven by the evolution of buying and selling technologies, has made monitoring the logistical efficiency of countries essential. This measurement also allows the main players in global logistics to compare themselves and helps governments and policy makers in carrying out the necessary reforms in the pursuit of economic advantage and efficiency. Since logistics is considered a system, its measurement goes beyond aspects related to infrastructure quality or any other operational aspect. Thus, the objective of this research is to propose a model for measuring the logistical efficiency of countries, considering socioeconomic, political and institutional factors pointed out in the literature. For this, the countries belonging to the LPI index were analyzed for the year 2018, applying the non-parametric technique Data Envelopment Analysis (DEA) in order to process the factors and establish the Decision Making Units (DMUs) more efficient through scores. In addition, it was decided to group countries into clusters with common characteristics so that the result of the efficiency analysis indicated the benchmarks within each grouping. The results obtained show that the ranking obtained brings considerable variations in the positions of the countries, in relation to the LPI. To give robustness to the results, it was decided to measure efficiency using three different structures, checking the sensitivity of the models to different inputs and outputs. It was observed that, even using different proxies, the results of the DEA models used are well related to each other. Regarding the decision to group countries with similar economic characteristics, a test of agreement of the models showed that, within each cluster, the agreement between the three models is higher than that found in the total set of countries. In the analysis of the complete set of countries, Egypt, Georgia, Iceland, Iran, Malta, Mongolia, Trinidad and Tobago and Uruguay, in Model A, and Brazil and Azerbaijan, in Model C, ...