Performance Analysis of the Main Coffee-Producing Regions in Brazil: A Methodological Triangulation Based on Principal Component Analysis and Data Envelopment Analysis

This study aimed to evaluate the performance of the main Arabica and Conilon coffee-producing regions in Brazil in the 2018–2019 and 2020–2021 harvest years, through the triangulation of the principal component analysis (PCA) and data envelopment analysis (DEA) techniques. To this end, the study followed a qualitative–quantitative approach, with descriptive character and inductive logic. The timeframe for this was 12 months to complete all methodological stages. Regarding efficiencies, six inefficient producers were identified for 2018–2019 and nine for 2020–2021. The results showed, in the 2018–2019 biennium, that production effectiveness is related to reductions in labor hiring and the creation of mechanisms to increase income on inefficient properties. On the other hand, in the 2020–2021 biennium, the intensive use of organic fertilizer and government credit were the most impactful aspects on the efficiency of properties. The contributions of this study were related to the identification of inefficient producers and, above all, the variables that most impact the performance of these sampling units so that they can reestablish their efficiencies. This study allowed for the generation of sustainable indicators to measure producers’ performance. For the agenda of future studies, it is suggested to replicate this study for other cultures and to expand the sample set.

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Publication Details

Journal
Sustainability
Published
2025-11-28
DOI
https://doi.org/10.3390/su172310688
Primary Topic
Coffee research and impacts
Type
article
Field-Weighted Citation Impact
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article

Performance Analysis of the Main Coffee-Producing Regions in Brazil: A Methodological Triangulation Based on Principal Component Analysis and Data Envelopment Analysis

Maria Cristina Angélico Mendonça, Juliana dos Santos Costa, André Luiz Marques Serrano, Lucas Oliveira Gomes Ferreira et al.
Sustainability
Coffee research and impacts
article

Performance Analysis of the Main Coffee-Producing Regions in Brazil: A Methodological Triangulation Based on Principal Component Analysis and Data Envelopment Analysis

Maria Cristina Angélico Mendonça, Juliana dos Santos Costa, André Luiz Marques Serrano, Lucas Oliveira Gomes Ferreira, Maria Gabriela Mendonça Peixoto, Marcelo Carneiro Gonçalves, Gustavo Alves de Melo, Samuel Borges Barbosa, Luiz Gonzaga de Castro
article en

Abstract

This study aimed to evaluate the performance of the main Arabica and Conilon coffee-producing regions in Brazil in the 2018–2019 and 2020–2021 harvest years, through the triangulation of the principal component analysis (PCA) and data envelopment analysis (DEA) techniques. To this end, the study followed a qualitative–quantitative approach, with descriptive character and inductive logic. The timeframe for this was 12 months to complete all methodological stages. Regarding efficiencies, six inefficient producers were identified for 2018–2019 and nine for 2020–2021. The results showed, in the 2018–2019 biennium, that production effectiveness is related to reductions in labor hiring and the creation of mechanisms to increase income on inefficient properties. On the other hand, in the 2020–2021 biennium, the intensive use of organic fertilizer and government credit were the most impactful aspects on the efficiency of properties. The contributions of this study were related to the identification of inefficient producers and, above all, the variables that most impact the performance of these sampling units so that they can reestablish their efficiencies. This study allowed for the generation of sustainable indicators to measure producers’ performance. For the agenda of future studies, it is suggested to replicate this study for other cultures and to expand the sample set.

SustainabilityVol. 17(23)
Universidade Federal de Lavras (BR), Universidade Federal de Viçosa (BR), Universidade de Brasília (BR), Universidade Federal da Paraíba (BR)
Fundação de Apoio à Pesquisa do Distrito Federal, Universidade Federal de Lavras
Openalex Percentile: Top 59%
Coffee research and impacts
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