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This study maps the fast-evolving digital green nexus linking Information Technology (IT), digitalization, and Artificial Intelligence (AI) to sustainability. Using a bibliometric analysis of 635 Scopus-indexed, English-language articles published between 2020 and 2025 and processed with Bibliometrix/Biblioshiny (v5.0), this study quantifies productivity, influence, collaboration, and conceptual structures (keyword co-occurrence and thematic evolution), interpreting the field through a Sociotechnical Systems (STS) lens. Output has surged (170% annual growth), the corpus is very young (mean document age 1.1 years), dispersed across 248 outlets, and team-intensive (3.71 co-authors/paper; 40.13% international collaboration). “Digital transformation” anchors the discourse while AI is the most salient specific technology; the intellectual structure bifurcates into a tech–economy cluster (often China-anchored evidence) and an organizational performance cluster, with circular economy topics remaining peripheral and South–South ties weak. Average citations (14.8 per paper) signal rapid turnover typical of emergent domains. The study advance theory by showing digital transformation’s brokerage role. Tools (AI, IoT, Industry 4.0) translate into audited environmental performance only when embedded in capabilities, governance, and social legitimacy consistent with STS. The study argues Responsible Innovation is an operating constraint given energy intensity, bias, privacy, and surveillance risks. Practically, this study calls for a shift from capability rhetoric to measurement-first systems: built-in MRV enabling A/B or stepped-wedge evaluations in the wild; coupling digital twins to real-time carbon/water ledgers; and integrating resilience analytics with mitigation scheduling (flexible loads, storage, DER orchestration) so adaptation and decarbonization operate in a single decision loop. Future work should bridge circularity with AI/digitization and rebalance geographic concentration through comparative, outcome-verified designs across China, EU/US, and the Global South.

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Mapping the Digital-Green Nexus: A Bibliometric Analysis of Information Technology, Digitalization, and Artificial Intelligence for Sustainability

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  • 发表日期：

    2026年

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  • Sunday Olaleye

摘要

This study maps the fast-evolving digital green nexus linking Information Technology (IT), digitalization, and Artificial Intelligence (AI) to sustainability. Using a bibliometric analysis of 635 Scopus-indexed, English-language articles published between 2020 and 2025 and processed with Bibliometrix/Biblioshiny (v5.0), this study quantifies productivity, influence, collaboration, and conceptual structures (keyword co-occurrence and thematic evolution), interpreting the field through a Sociotechnical Systems (STS) lens. Output has surged (170% annual growth), the corpus is very young (mean document age 1.1 years), dispersed across 248 outlets, and team-intensive (3.71 co-authors/paper; 40.13% international collaboration). “Digital transformation” anchors the discourse while AI is the most salient specific technology; the intellectual structure bifurcates into a tech–economy cluster (often China-anchored evidence) and an organizational performance cluster, with circular economy topics remaining peripheral and South–South ties weak. Average citations (14.8 per paper) signal rapid turnover typical of emergent domains. The study advance theory by showing digital transformation’s brokerage role. Tools (AI, IoT, Industry 4.0) translate into audited environmental performance only when embedded in capabilities, governance, and social legitimacy consistent with STS. The study argues Responsible Innovation is an operating constraint given energy intensity, bias, privacy, and surveillance risks. Practically, this study calls for a shift from capability rhetoric to measurement-first systems: built-in MRV enabling A/B or stepped-wedge evaluations in the wild; coupling digital twins to real-time carbon/water ledgers; and integrating resilience analytics with mitigation scheduling (flexible loads, storage, DER orchestration) so adaptation and decarbonization operate in a single decision loop. Future work should bridge circularity with AI/digitization and rebalance geographic concentration through comparative, outcome-verified designs across China, EU/US, and the Global South.