Artificial intelligence, economic complexity, and clean energy productivity as drivers of SDG-7 progress and ESG uncertainty
Quality and Quantity, 2026 (Scopus)
- Yayın Türü: Makale / Tam Makale
- Basım Tarihi: 2026
- Doi Numarası: 10.1007/s11135-026-03090-5
- Dergi Adı: Quality and Quantity
- Derginin Tarandığı İndeksler: Scopus, IBZ Online, ABI/INFORM, Index Islamicus, Political Science Complete, Psycinfo, Political Science Abstract (IPSA), Social Science Premium Collection (ProQuest), Health Research Premium Collection (ProQuest), Sociology Database (ProQuest), Sociology Source Ultimate (EBSCO)
- Anahtar Kelimeler: Affordable and clean energy, Artificial intelligence, Economic complexity, ESG uncertainty, Productivity capacities
- Recep Tayyip Erdoğan Üniversitesi Adresli: Hayır
Özet
This study empirically examines whether artificial intelligence, economic complexity, and clean energy productivity reduce ESG uncertainty and enhance progress toward Sustainable Development Goal (SDG) 7. The analysis focuses on the five largest economies—China, the United States, Japan, Germany, and India—over the period 2002–2023. The Bias-Corrected Method of Moments (BCMM) estimator is used for empirical estimation. The findings indicate that artificial intelligence, economic complexity, and clean energy productivity have positive and significant effects on SDG 7 progress, facilitating renewable energy optimization and efficiency gains. For ESG uncertainty, artificial intelligence and economic complexity tend to increase uncertainty through algorithmic opacity, ethical risks, and resource-intensive structures, while clean energy productivity significantly reduces it by promoting transparent and efficient sustainability practices. These results highlight the necessity of governance-aligned technological deployment and productivity-focused policies to harness renewable energy potential, stabilize sustainability frameworks, and support equitable energy transitions in leading economies.