Cost-Benefit, Energy Sustainability and Technological Assessment of Artificial Intelligence Adoption in Nigeria’s Agricultural and Waste-to-Energy Systems
ナイジェリアの農業および廃棄物発電システムにおける人工知能導入の費用便益、エネルギー持続可能性、および技術評価 (AI 翻訳)
Nathan Udoinyang, Reuben Daniel, Akarue Blessing Okiemute Okiemute, Aboh Peter Chukwuedu
🤖 gxceed AI 要約
日本語
本研究は、ナイジェリアの農業・廃棄物発電システムにおけるAI導入の費用便益、エネルギー持続可能性、技術的影響を評価。522名の調査データを分析した結果、AI導入は中程度から高水準であり、業務効率と環境持続可能性を有意に向上させることが示された。一方、インフラ不足や専門知識不足などの課題も明らかになった。
English
This study evaluates the cost-benefit, energy sustainability, and technological implications of AI adoption in Nigeria's agricultural and waste-to-energy (WTE) systems. Based on survey data from 522 respondents, findings indicate moderate-to-high AI adoption, significant improvements in operational efficiency and environmental sustainability, but barriers such as infrastructure deficiencies and high implementation costs persist.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本企業がナイジェリアなど新興国でAIを活用したグリーン事業を展開する際の参考となる可能性がある。特に農業×廃棄物発電という分野は、日本の環境技術の輸出やODA戦略に関連する。ただし、直接的な日本国内のGX議論にはつながりにくい。
In the global GX context
This paper contributes to the global literature on AI for sustainability in developing economies, offering empirical evidence on the cost-benefit and energy sustainability of AI in agriculture and waste-to-energy. It highlights the role of AI in advancing the green transition in the Global South, which is relevant for international climate finance and technology transfer discussions.
👥 読者別の含意
🔬研究者:Provides empirical evidence on AI adoption and sustainability outcomes in a developing country context, contributing to the AI-for-sustainability literature.
🏢実務担当者:Offers insights into the benefits and barriers of AI implementation in agricultural and waste-to-energy systems, useful for firms considering similar technologies.
🏛政策担当者:Presents policy recommendations for promoting AI-driven green transition in developing countries, relevant for international development agencies.
📄 Abstract（原文）
This study examines the cost-benefit, energy sustainability, and technological implications of artificial intelligence (AI) adoption in Nigeria's agricultural and waste-to-energy (WTE) systems. AI technologies are increasingly transforming agricultural production, renewable energy generation, waste management efficiency, and environmental sustainability across developing economies. Using a quantitative survey design, data were collected from 522 respondents across Nigeria's six geopolitical zones and analysed using descriptive statistics and multiple regression techniques. The findings reveal moderate-to-high AI adoption (Mean = 3.84), significant improvements in operational efficiency (Mean = 4.02), enhanced energy recovery and environmental sustainability (Mean = 3.95), and positive social impacts (Mean = 3.78). Regression results indicate that AI investment significantly improves operational efficiency (β = 0.62, p < 0.01) and sustainability outcomes (β = 0.55, p < 0.01). The study further demonstrates that AI-enabled technologies support smart energy conversion, precision agriculture, renewable energy optimisation, and efficient waste valuation. However, infrastructural deficiencies, unstable electricity supply, limited technical expertise, and high implementation costs remain major barriers. The study concludes that AI adoption provides substantial economic, technological, and energy sustainability benefits that outweigh implementation costs. The results contribute to emerging literature on AI, renewable energy systems, and sustainable technological development in developing economies while offering practical policy recommendations for Nigeria's green transition agenda.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.56556/jtie.v5i1.1464first seen 2026-07-13 04:56:29
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