Modelled Adoption Trajectories of Vertical Farming Systems in Two African Cities Using the ADOPT Tool

Vertical farming (VF) holds potential for urban food security in African cities, yet adoption of VF systems by farmers remains poorly understood across diverse urban contexts. This study modeled VF system diffusion across three settlement types in Lagos and Nairobi using the ADOPT Tool framework. A total of 60 urban farmers from the 2 cities participated in the focus group discussions at six sites. The study provides an exploratory, model-based contribution to understanding context-specific adoption of vertical farming in selected African urban settings. Predictions revealed substantial spatial heterogeneity. Peak adoption ranged from 2 to 98%, with time-to-peak spanning 10–25 years. Intra-city variation in basic system adoption exceeded inter-city differences (61–97% in Nairobi versus 16–52% in Lagos). CEA systems approached saturation in affluent neighborhoods (Langata 98%, Lekki 95%) while remaining constrained in informal settlements (<25%). Sensitivity analysis identified three population-level binding constraints: Financial Capacity, Management Skill, and Environmental Orientation. Each constraint generated an 18–24 percentage-point impact in resource-constrained settlements but less than 6 percentage points in affluent areas. On the other hand, four innovation-level factors (Complexity, Trialability, Observability, Training Requirements) accelerated the diffusion rate by 1.2–1.4 years across all sites. These findings demonstrate that adoption is determined by context-specific constraint configurations rather than uniform urban conditions. Effective scaling requires settlement-differentiated interventions: in informal settlements, finance and extension; in high-density areas, space-efficient design and market linkages; in affluent zones, regulatory enablement. The study illustrates that technology adoption models developed in wealthy contexts often fail to apply to resource-constrained African cities where local constraints vary dramatically over short distances. The study also finds that adoption can be improved by implementing targeted policies and strengthening supporting infrastructure. These findings provide actionable pathways to increase vertical farming adoption in rapidly growing African megacities.

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Publication Details

Journal
Sustainability
Published
2026-08-03
DOI
https://doi.org/10.3390/su18157837
Primary Topic
Urban Agriculture and Sustainability
Type
article
Field-Weighted Citation Impact
0.00

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article

Modelled Adoption Trajectories of Vertical Farming Systems in Two African Cities Using the ADOPT Tool

Cristina Lenz, Monika Egerer, Mitchell Mahachi
Sustainability
Urban Agriculture and Sustainability
article

Modelled Adoption Trajectories of Vertical Farming Systems in Two African Cities Using the ADOPT Tool

Cristina Lenz, Monika Egerer, Mitchell Mahachi
article en

Abstract

Vertical farming (VF) holds potential for urban food security in African cities, yet adoption of VF systems by farmers remains poorly understood across diverse urban contexts. This study modeled VF system diffusion across three settlement types in Lagos and Nairobi using the ADOPT Tool framework. A total of 60 urban farmers from the 2 cities participated in the focus group discussions at six sites. The study provides an exploratory, model-based contribution to understanding context-specific adoption of vertical farming in selected African urban settings. Predictions revealed substantial spatial heterogeneity. Peak adoption ranged from 2 to 98%, with time-to-peak spanning 10–25 years. Intra-city variation in basic system adoption exceeded inter-city differences (61–97% in Nairobi versus 16–52% in Lagos). CEA systems approached saturation in affluent neighborhoods (Langata 98%, Lekki 95%) while remaining constrained in informal settlements (<25%). Sensitivity analysis identified three population-level binding constraints: Financial Capacity, Management Skill, and Environmental Orientation. Each constraint generated an 18–24 percentage-point impact in resource-constrained settlements but less than 6 percentage points in affluent areas. On the other hand, four innovation-level factors (Complexity, Trialability, Observability, Training Requirements) accelerated the diffusion rate by 1.2–1.4 years across all sites. These findings demonstrate that adoption is determined by context-specific constraint configurations rather than uniform urban conditions. Effective scaling requires settlement-differentiated interventions: in informal settlements, finance and extension; in high-density areas, space-efficient design and market linkages; in affluent zones, regulatory enablement. The study illustrates that technology adoption models developed in wealthy contexts often fail to apply to resource-constrained African cities where local constraints vary dramatically over short distances. The study also finds that adoption can be improved by implementing targeted policies and strengthening supporting infrastructure. These findings provide actionable pathways to increase vertical farming adoption in rapidly growing African megacities.

SustainabilityVol. 18(15)
Weihenstephan-Triesdorf University of Applied Sciences (DE), Technical University of Munich (DE)
Bayerische Wissenschaftsforum
Openalex Percentile: Top 11%
Urban Agriculture and Sustainability
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