Leveraging clustering techniques to drive sustainable economic innovation in the India–Gulf interchange

Abstract

AbstractThe collaboration between India and the Gulf regions presents a promising opportunity for sustainable economic innovation amidst global challenges. However, there is a notable research gap in understanding how machine learning techniques, particularly clustering, can drive such innovation effectively in this context. Existing literature lacks tailored models for the India–Gulf interchange’s specific needs. This study aims to fill this gap by investigating the application of machine learning clustering models to identify factors and opportunities for sustainable economic innovation. Specifically, it seeks to leverage these techniques to foster strategic partnerships and address environmental, social, and governance factors. Through SWOT analysis and clustering, the study identifies integration elements and proposes a forward-looking Paradigm for Future Development. The findings advocate for strategic collaborations and offer a model methodology for sustainable development, with broader policy implications. The study reveals that Current Saudi Arabia’s progress is linked to strategies akin to India’s, suggesting India as a model for Gulf countries.

Keywords

• Clustering analysis
• India–Gulf interchange
• sustainable economic
• ESG (environmental, social, governance)
• Armando Aliu, Faculty of International and Political Studies, Jagiellonian University, Krakow, Poland
• Sustainable Development