Multidimensional performance assessment of a sample of beef cattle ranches in the Pantanal from a data envelopment analysis perspective

Author:

Gomes Eliane Gonçalves1ORCID,Santos Sandra Aparecida2ORCID,Paula Emanuel Salgado de3ORCID,Nogueira Marcelo Augusto4ORCID,Oliveira Márcia Divina de2ORCID,Salis Suzana Maria2ORCID,Soriano Balbina Maria Araújo2ORCID,Tomas Walfrido Moraes2ORCID

Affiliation:

1. Embrapa, Brazil

2. Embrapa Pantanal, Brazil

3. Instituto Mato-grossense de Economia Agropecuária, Brasil

4. Serviço Nacional de Aprendizagem Rural, Brasil

Abstract

ABSTRACT: Beef cattle ranching is the main economic activity in the Brazilian Pantanal, undertaken in an extensive manner, mostly in natural environments and dynamic in space and time. The ongoing monitoring, assessment, and performance improvement are key aspects of the search for sustainable use of natural resources in beef cattle ranches, as these ranches are the management units in the Pantanal. In this paper we proposed a data envelopment analysis (DEA) approach to assess the performance of fourteen beef cattle ranches in the Pantanal wetland as a case study, considering financial, productive, and environmental sustainability dimensions. We modeled each dimension separately and calculated an overall performance score. We also fit fractional regression models to study the influence of potential covariates on the performance scores. The methodological approach proposed here proved to be adequate for the case study, as the results are in line with the expectations of decision-makers regarding the performance of the ranches. The overall performance analysis was influenced by the proportion of higher quality native forage resources, which depends on the dynamics and on the spatial-temporal variation of the landscapes. Therefore, overall performance requires adaptive management of ranches based on diversity conservation, which benefits the multifunctionality of products and services.

Publisher

FapUNIFESP (SciELO)

Subject

General Veterinary,Agronomy and Crop Science,Animal Science and Zoology

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