Unraveling interdependencies in circular business models for renewable energy: A novel MCDM approach to systemic challenges

Abstract

The adoption of Circular Business Models (CBMs) in the Renewable Energy Industry (REI) is pivotal for advancing the United Nations Sustainable Development Goals (SDGs), particularly Goal 7 (affordable and clean energy), Goal 12 (responsible consumption and production), and Goal 13 (climate action). However, it faces complex systemic and economic challenges. This study introduces a novel Interval-Valued Spherical Fuzzy Interpretive Structural Modeling (IVSF-ISM) and MICMAC framework to analyze the interdependencies among challenges, derived from a PRISMA-guided systematic literature review of 42 peer-reviewed articles. The proposed methodology captures uncertainty in expert judgments, structuring challenges into a six-level hierarchy and classifying them into driving, linkage, dependent, and autonomous categories based on their influence and dependence. Key findings highlight regulatory uncertainty, lack of interoperability, and fragmented value chain collaboration as primary driving challenges, amplifying barriers such as high initial investment and customer resistance to non-ownership models. Linkage challenges, including revenue unpredictability and data privacy risks, create feedback loops that exacerbate systemic risks. This research contributes to technological forecasting by offering a systemic perspective on CBM adoption and its societal impact. By addressing root causes, this study advances REI for optimizing resource allocation and fostering equitable, scalable energy transitions, contributing to sustainable energy. © 2026 Elsevier B.V.