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Robots for sustainability: Evaluating ecological footprints in leading AI-driven industrial nations

Liu, L ; Sharif University of Technology | 2024

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  1. Type of Document: Article
  2. DOI: 10.1016/j.techsoc.2024.102460
  3. Publisher: Elsevier Ltd , 2024
  4. Abstract:
  5. By automating tasks with precision and efficiency, industrial robots help minimize resource utilization and emissions, making them indispensable allies in our quest to minimize our ecological footprint. The core intention of the present article is to scrutinize the impact of industrial robots on the ecological footprint in ten leading industrial artificial intelligence nations (Singapore, South Korea, Japan, Germany, Sweden, Denmark, USA, China, France, and Italy) from 2007 to 2020. Prior investigations have chosen panel data methodologies to detect the association between industrial robots and ecological footprint. Nonetheless, these studies often overlooked the variations in this relationship across different countries. In contrast, this article choses the Quantile-on-Quantile approach to assess this relationship on a country-specific basis. This methodology offers a comprehensive global perspective while delivering tailored insights relevant to each nation. The findings suggest that industrial robots improve environmental quality by decreasing ecological footprint across different data quantiles in chosen nations. The findings also underline that the asymmetries between our variables differ from country to country. These revelations underscore the importance of policymakers carefully assessing and skillfully managing strategies related to both industrial robots and the ecological footprint. © 2024 Elsevier Ltd
  6. Keywords:
  7. Ecological footprint ; Environmental quality ; Industrial nations ; Industrial robots ; Quantile estimation
  8. Source: Technology in Society ; Volume 76 , 2024 ; 0160791X (ISSN)
  9. URL: https://www.sciencedirect.com/science/article/pii/S0160791X24000083