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bioRxiv · 10.64898/2026.03.02.708951

Structural financial ambiguity in climate-smart agriculture research: A bibliometric analysis of African knowledge systems

Abstract

Climate-smart agriculture (CSA) dominates African agricultural policy discourse, yet fifteen years post-conceptualization, its transformative potential remains unrealized. Bibliometric analysis of 161 Scopus-indexed publications (2014-2025) reveals exponential field growth (31.3% annually) coupled with on technical dimensions and systemic neglect of financial mechanisms. Network analysis (VOSviewer), semantic mapping and citation bibliometrics expose cognitive oligopolisation--wherein 1.8% of authors generate 45% of output--geographical fragmentation into weakly connected regional clusters, and critical underrepresentation of the vulnerable Sahel. Despite 46.6% of publications addressing economic themes, merely 5.6% rigorously integrate financial analysis with adoption variables; terms including investment, cost-benefit and climate finance remain absent from major semantic clusters. The concept of structural financial ambiguity is introduced to characterize the maintenance of CSA in operational indeterminacy through academic discourse that substitutes description for actionable financial theorization. Paradigmatic transformation conditions are identified through emerging scholarship employing discrete choice experiments and cost-benefit evaluations to construct requisite knowledge foundations. Findings indicate that without comprehensive theorization of microfinance, digital finance, index-based insurance and payments for environmental services, international climate commitments risk implementation failure due to absence of scientifically validated financial instruments rather than technical solutions.

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BibTeXRIS

Chimi, P. M., Yonga, G., Tchopwe Menkamla, A., Maralossou, B., Ngon Dikoume, A. M., Mazak Nguihi, L., Mvondo Effa, U. D., Bell, J. M., Mala, W. A.. 2026-03-10. Structural financial ambiguity in climate-smart agriculture research: A bibliometric analysis of African knowledge systems. https://doi.org/10.64898/2026.03.02.708951

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