HMP-Coffee: A Hierarchical Multicriteria Model to Estimate the Profitability for Small Coffee Farming in Colombia

• Published in: Applied sciences 2021-08, Vol.11 (15), p.6880
• Main Authors: Casilimas, Leidy, Corrales, David Camilo, Solarte Montoya, Mayra, Rahn, Eric, Robin, Marie-Hélène, Aubertot, Jean-Noël, Corrales, Juan Carlos
• Format: Article
• Language: English
• Subjects: Accounting records; Agricultural economics; Agricultural production; Agricultural sciences; Agriculture; Coffee; coffee crop; Coffee industry; Crops; Decision making; Decision trees; Developing countries; economic sustainability; Economics; Engineering Sciences; Farmers; Farms; hierarchical multicriteria model; Information management; Knowledge; LDCs; Life Sciences; Multiple criterion; Precipitation; Production costs; Profitability; Rice; small coffee productions; Stakeholders; Sustainability; Utility functions
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app11156880

Existing models to estimate profitability in small-scale coffee production are based on limited information leading to precision problems in the estimations and, therefore, fail to represent the real economic return. This leads smallholders to make decisions based on inaccurate information with negative consequences on their financial status. This paper introduces a novel hierarchical approach called HMP-Coffee (Hierarchical Model Profitability Coffee) to estimate the profitability level in small-scale coffee productions, supporting smallholders, in decision-making, to improve their income and, consequently, their economic sustainability. HMP-Coffee considers a Contextual Knowledge Phase, based on expert knowledge, to create a conceptual model about the profitability in small-scale coffee productions and a Hierarchical-Multicriteria Phase responsible for translating such a conceptual model into an understandable hierarchical qualitative model able to estimate the level of profitability in small coffee productions precisely. HMP-Coffee was developed by considering the La Sultana farm’s operation in Cauca, Colombia and evaluated with independent data from the Costa Rican Coffee Institute. In the evaluation results, HMP-Coffee achieved 81.72% accuracy, 81.33% precision, 92.30% recall, and 83.46% F-Score. From the results obtained, we conclude that HMP-Coffee is a reliable model to estimate the profitability of small-scale coffee production. Its reliability improves the decision-making for obtaining crops with better economic sustainability.