Modeling family farming sustainability in Huambo (Angola): alternative scenarios explored through ethnographic linear programming

Purpose This study aimed to develop an ethnographic linear programming (ELP) model for family farmers in Huambo to estimate their current household incomes and assess alternative sustainability scenarios. The analysis focused on the economic and social dimensions, addressing both the potential and constraints of family farming systems. Design/methodology/approach The model was developed in four stages: (1) designing a questionnaire to gather relevant data; (2) pre-testing and refining the instrument; (3) selecting a representative household to validate and adjust the model; and (4) constructing the ELP model. Findings The results reveal that very small and small farmers remain below the poverty line under current conditions, whereas medium and large farmers exceed it. The adoption of certified high-yield seed varieties and improved livestock practices, specifically, goats with two births per year, significantly increased farm income and enhanced economic sustainability. Research limitations/implications Results show how technology adoption can raise annual and per capita net income, providing evidence to support policies that strengthen sustainable family farming in Angola. Originality/value This study contributes a novel methodological framework that integrates ethnographic insights with linear programming to evaluate household economic performance.