Harnessing artificial intelligence to strengthen green innovation capacity in pursuit of sustainable development goals: Evidence from Taiwan’s manufacturing sector
Sahilali Saiyed, Mahedi Hasan, Redoyan Chowdhury, K. M. Tousif Bin Parves, Eko Hariyadi, Vimal Kumar
Abstract
Research background: Artificial Intelligence (AI) is becoming a revolutionary ability that can speed up the shift towards sustainable production through re-source efficiency, optimization of processes, and low-carbon innovations. Consistent with the United Nations Sustainable Development Goals (SDGs), SDG 9 (sustainable industrialization), SDG 12 (responsible consumption and production), and SDG 13 (climate action), AI is becoming a driver of green innovation, as well as a facilitator of the same. Purpose of the article: This paper examines how AI applications affect organizational performance (OPE) in the Taiwanese manufacturing industry with a special emphasis on the mediating effect of GIC. Based on the Dynamic Capabilities Theory (DCT), the paper constructs and empirically validates a structural model that elucidates how AI adoption increases sustainable competitiveness through the development of innovation-oriented capabilities. Methods: The research used a cross-sectional, quantitative study design and gathered data on 270 professionals in the Taiwanese manufacturing sectors. The AI applications, GIC, and OPE were measured using a structured questionnaire to measure them using multi-item Likert scales. Hypotheses were tested using the Partial Least Squares Structural Equation Modeling (PLS-SEM). Findings & value added: The study shows that Artificial Intelligence (AI) adoption plays a significant role in enhancing both green innovation capabilities (GIC) and overall organizational performance (OPE). More importantly, GIC emerges as a key mechanism through which AI applications are translated into measurable sustainability outcomes, underscoring its role as a strategic bridge between digital transformation and environmental performance.