Analysing the key drivers and barriers for implementing circular economy practices in waste management systems using ISM and MICMAC analysis

Abstract

The transition toward a circular economy (CE) offers a sustainable alternative to traditional waste management systems but faces significant challenges due to technological, policy, economic, and behavioural barriers. Addressing the fragmented understanding of these factors, this study presents a structured, data-driven framework by integrating Interpretive Structural Modelling (ISM) and MICMAC analysis, validated through Structural Equation Modelling (SEM). Through systematic literature review and expert consultation, the research identifies and prioritises twelve key drivers and barriers influencing CE adoption in waste management. The findings reveal that advanced recycling technologies, policy support, and waste-to-energy opportunities act as pivotal enablers, while infrastructure limitations and high investment costs emerge as major barriers. The ISM model constructs a hierarchical structure of interdependencies, and MICMAC analysis categorises factors based on their driving and dependence powers, offering strategic insights. SEM validation confirms the robustness of the proposed framework, with significant causal relationships (e.g., β = 0.72 between technological advancements and infrastructure development). This study contributes a state-of-the-art decision-support model to guide policymakers and industry stakeholders in designing targeted interventions, accelerating the transition toward sustainable and circular waste management systems.