Engineering systems thinking for sustainable agricultural transformation in Sub-Saharan Africa: A framework for integrating mechanisation, logistics optimisation, and digital decision tools

Naming fragmentation as the reason agricultural systems underperform in Sub-Saharan Africa is well-established. What isn't established is how to build integration where infrastructure, data, and institutional capacity are all simultaneously constrained. This article addresses that gap directly. The Integrated Agricultural Systems Framework (IASF) proposed here is a design instrument, not a diagnosis. It specifies how three functional domains, namely mechanisation, logistics optimisation, and digital decision tools, connect through defined interfaces, in what sequence those interfaces should be built, and how system-level sustainability outcomes emerge from their interaction rather than from the performance of any single domain. The framework draws on systems thinking methodology, specifically feedback loop analysis and intervention point theory. It is applied across four commodity systems widely produced in south-west Nigeria, covering cassava, rice, oil palm, and groundnut, to demonstrate that the integration architecture holds across crop types and chain structures. Each application identifies which interface layer is the binding constraint, what minimum viable data the real-time information layer requires, and what sustainability co-benefits integration produces that no single-domain intervention can achieve. Transferability conditions are stated explicitly so the framework can be applied and tested in other low-income agricultural contexts.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-06-18
DOI
https://doi.org/10.5281/zenodo.20744787
Primary Topic
Complex Systems and Decision Making
Type
article
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article

Engineering systems thinking for sustainable agricultural transformation in Sub-Saharan Africa: A framework for integrating mechanisation, logistics optimisation, and digital decision tools

Gabriel Eboseta Peter
Zenodo (CERN European Organization for Nuclear Research)
Complex Systems and Decision Making
article

Engineering systems thinking for sustainable agricultural transformation in Sub-Saharan Africa: A framework for integrating mechanisation, logistics optimisation, and digital decision tools

Gabriel Eboseta Peter
article en

Abstract

Naming fragmentation as the reason agricultural systems underperform in Sub-Saharan Africa is well-established. What isn't established is how to build integration where infrastructure, data, and institutional capacity are all simultaneously constrained. This article addresses that gap directly. The Integrated Agricultural Systems Framework (IASF) proposed here is a design instrument, not a diagnosis. It specifies how three functional domains, namely mechanisation, logistics optimisation, and digital decision tools, connect through defined interfaces, in what sequence those interfaces should be built, and how system-level sustainability outcomes emerge from their interaction rather than from the performance of any single domain. The framework draws on systems thinking methodology, specifically feedback loop analysis and intervention point theory. It is applied across four commodity systems widely produced in south-west Nigeria, covering cassava, rice, oil palm, and groundnut, to demonstrate that the integration architecture holds across crop types and chain structures. Each application identifies which interface layer is the binding constraint, what minimum viable data the real-time information layer requires, and what sustainability co-benefits integration produces that no single-domain intervention can achieve. Transferability conditions are stated explicitly so the framework can be applied and tested in other low-income agricultural contexts.

Zenodo (CERN European Organization for Nuclear Research)
Zero hunger
Openalex Percentile: Top 3%
Complex Systems and Decision Making
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