Industrial Robotics, Resource Efficiency, Energy Transition, and Environmental Quality: Designing a Sustainable Development Goals Framework for G7 Countries in the Presence of Geopolitical Risk

Yuhan Xia () and Mahmood Ahmad
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Yuhan Xia: School of Marxism, Xidian University, Xi’an 710000, China
Mahmood Ahmad: Advanced Research Centre, European University of Lefke, Lefke, Northern Cyprus, TR-10, Mersin 99010, Turkey

Sustainability, 2025, vol. 17, issue 5, 1-17

Abstract: In recent years, the integration of industrial robotics has emerged as a powerful tool in reshaping industries by enhancing production efficiency, reducing waste generation, and optimizing resource utilization. However, industrial robotics, particularly in manufacturing and production, require significant energy that can potentially impact on environmental quality. Despite the growing adoption of artificial intelligence (AI)-based industrial robotics, there is a paucity of literature on the impact of industrial robotics on the ecological footprint (EF), particularly in the context of advanced economies. In this context, this study aims to investigate the impact of industrial robotics, resource efficiency, energy transition, and geopolitical risk EF in G7 countries from 1993 to 2021. The study employed advanced econometric techniques, including Kernel-based Regularized Least Squares (KRLS) and Artificial Neural Network (ANN) machine learning methods. The results unveiled that industrial robotics significantly curtail environmental degradation by impeding the EF. Resource efficiency and energy transition posed a significant and negative impact on the EF. Geopolitical risks and economic growth exacerbate the EF. Based on the results, the study proposes important policy implications for achieving sustainable development.

Keywords: industrial robotics; resource efficiency; energy transition; geopolitical risk; machine learning (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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