アフリカのエネルギー転換:5カ国の比較分析
Energy Transition in Africa: A Comparative Analysis of Five African Countries (原題)
Boluwatife G. Ayankojo
🤖 gxceed AI 要約
日本語
エジプト・ガーナ・ケニア・ナイジェリア・南アフリカの5カ国を対象に、太陽光エネルギーへの転換がなぜ国ごとに異なるかを、エージェントベースモデリング(ABM)と比較分析の混合手法で解明する研究。世帯の太陽光採用意思決定がシステム全体の普及パターンにどう影響するかをシミュレーションし、コスト・予算制約、太陽光の伝播性、ネットワーク密度といった社会経済要因が採用格差を大きく左右することを示す。普及が遅れる国には導入インセンティブ政策を、飽和に近づく国には持続可能性課題への対応政策を提言する。
English
This study examines why solar energy adoption differs across Egypt, Ghana, Kenya, Nigeria, and South Africa, using agent-based modeling and comparative case analysis. It simulates how household adoption decisions generate system-level diffusion patterns, finding that cost and budget constraints, transmissibility of solar, and network density strongly shape uptake. Lagging countries are urged to adopt incentive policies, while saturated markets should address underlying sustainability challenges.
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
日本企業にとって直接の開示規制接続は薄いが、アフリカ新興国での分散型太陽光・オフグリッド事業の市場形成要因を理解する材料となる。商社・電力・インフラ企業の途上国エネルギー事業リスク評価や、JCM等の二国間クレジット案件形成の文脈で参考になる。
In the global GX context
Adds to the global energy-transition literature by modeling household-level solar diffusion in emerging markets, relevant to transition finance and just-transition debates where grid reliability and access gaps drive decarbonization pathways. It complements ISSB/TCFD-aligned transition planning by highlighting socioeconomic adoption barriers that disclosure frameworks rarely capture.
👥 読者別の含意
🔬研究者:ABMと比較事例分析を組み合わせ、普及理論(DOI)を新興国太陽光市場に適用する手法の実例として参考になる。
🏢実務担当者:アフリカ新興国での分散型太陽光・オフグリッド事業の市場参入や普及阻害要因の把握に活用できる。
🏛政策担当者:普及段階に応じたインセンティブ設計と飽和後の持続可能性政策の使い分けを示唆する。
📄 Abstract(原文)
Global energy transition remains a critical challenge for reducing carbon emissions and protecting the environment, with solar energy adoption driving improvements in both energy efficiency and conservation. This research focuses on Africa's transition from fossil fuels to solar energy. As population growth and blackouts increase, African countries must transition from unreliable, centralized national grids to decentralized, low-carbon alternatives that ensure quality household electricity. While some countries have advanced in this transition to sustainable solar energy, others lag behind. The limited access to electricity hinders the African continent's healthcare, education, economic growth, and mortality rates. This research establishes the importance of solar energy adoption in addressing these developmental challenges by asking: why does the transition to renewable energy sources (solar) differ among African countries? Consequently, this study aims to uncover the socioeconomic and political factors that impede or facilitate these disparities. Using a mixed-methods approach to understand this complex phenomenon in a real-world setting, this study employs Agent-Based Modeling (ABM) and comparative analysis. ABM simulates how household decision-making regarding solar uptake produces broader system-level results, while a comparative analysis of five country case studies - Egypt, Ghana, Kenya, Nigeria, and South Africa - identifies patterns and develops robust explanations. Finally, this research contributes to the international political economy literature by comparing solar adoption outcomes across five unique African nations to facilitate a quicker regional transition. It introduces Diffusion of Innovations (DOI) theory to illustrate how the number of adopters grows over time and to determine the ongoing progression of the transmission process. The findings show that socioeconomic factors such as cost and budget constraints, transmissibility of solar, and network density are highly influential in shaping adoption patterns across the five selected countries. These results imply that lagging African countries need to implement policies that incentivize solar uptake. Meanwhile, countries reaching a saturation point should develop policies addressing underlying sustainability challenges. This can be achieved by learning from the success stories of countries with similar profiles and tailoring those insights into country-specific needs.
🔗 Provenance — このレコードを発見したソース
- openalex https://digitalcommons.odu.edu/gpis_etds/258first seen 2026-10-30 04:45:47 · last seen 2026-11-06 04:35:10
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