Transforming Business Waste Diversion through Intelligent GIS-Based Circular Economy Decision Support Platforms for Sustainability Outcomes

Author

Olayemi Aanuoluwapo Olugosi

Abstract

 Businesses face increasing pressure to adopt sustainable waste management practices that reduce environmental impacts while improving operational efficiency and resource utilisation. Conventional waste diversion systems lack spatial intelligence, predictive capability, and real-time optimisation required for effective circular economy implementation. This systematic review aims to examine existing literature on GIS-based decision support systems, artificial intelligence applications, and circular economy frameworks in business waste diversion, and to propose an integrated intelligent platform architecture for improving sustainability outcomes. A systematic literature search was conducted across Scopus, Web of Science, Google Scholar, and IEEE Xplore databases using predefined search terms related to GIS, circular economy, waste diversion, decision support systems, and artificial intelligence. Studies published between 2020 and 2026 were screened against inclusion and exclusion criteria following PRISMA guidelines. A total of 35 studies were identified and synthesised. Findings reveal that GIS-enabled platforms integrating spatial analytics, machine learning, IoT monitoring, and circular economy modelling significantly improve waste diversion rates, resource recovery, and sustainability reporting. Key gaps include limited AI integration in existing platforms, weak predictive modelling, and insufficient circular economy performance metrics. Intelligent GIS-based circular economy decision support platforms represent a transformative approach to business waste management. The proposed multi-layer framework, incorporating spatial intelligence, predictive analytics, optimisation models, and interactive dashboards, offers a scalable solution for improving national resource efficiency, reducing emissions, and supporting long-term economic competitiveness.

Keywords

GIS-based decision support; Business waste diversion; Circular economy; Spatial analytics; Sustainable resource management; Artificial intelligence; Predictive modelling.

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References

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