Agent‐Based Computable General Equilibrium Modeling for Environment Sustainability in a Circular Economy

ABSTRACT Growing environmental threats like carbon emissions, industrial wastes, and climate change introduce a paradigm shift toward circular economy (CE). The concept of CE offers a sustainable approach to waste reduction by extending the life of existing resources and promoting their re‐use. The present study aims to improve operational efficiency while minimizing its environmental impact. The key strategies include industrial symbiosis (sharing resources between industries), resource loop closure (reducing material loss), and non‐ownership models (like product‐as‐a‐service). The proposed framework was tested using agent‐based and computable general equilibrium (CGE) modeling across industrial sectors in Asia. In this regard, real‐time data amid region‐specific characteristics were integrated, while standardized metrics were applied to measure performance outcomes. Results indicated a 25% reduction in waste generation, a 30% increase in resource recovery, and a 15% drop in energy consumption. Furthermore, the operational performance was improved by 40% due to efficient use of resources. The study highlights how the proposed model can reduce environmental impact and improve the decision‐making of industrialists and policymakers by using data‐driven simulations. Moreover, the proposed framework is well aligned with SDG 12 (Responsible Consumption and Production) and SDG 13 (Climate Action), thus offering a sustainable path toward climate‐resilient and resource‐efficient industrial systems.