Implementation of circularity in food supply chain based on big data techniques using Einstein's fuzzy methods

By emphasizing the principles of recycling, refurbishing, and reusing materials, circularity in supply chain management plays a pivotal role in waste reduction and resource efficiency enhancement. However, the adoption and implementation of circular supply chains (CSCs) remain limited due to the substantial associated risks. Research in Circular Supply Chain Management (CSCM) suggests that integrating Fourth Industrial Revolution technologies and big data analytics may offer a viable solution. Despite growing interest in CSCM, the lack of field-specific data and a predominant focus on macro-level studies have resulted in insufficient exploration of circularity barriers within Iran's food supply chain. This study seeks to address this gap by prioritizing big data-driven solutions to overcome these barriers. The research objectives include identifying and validating key obstacles within Iran's food industry through an extensive literature review and content validity ratio analysis. The barriers were classified into five primary categories, with their respective weights determined using the fuzzy SWARA (Step-wise Weight Assessment Ratio Analysis) method. The most critical barriers identified were the absence of organizational infrastructure to support circular supply chain initiatives and the lack of essential systems for product traceability. Subsequently, big data-based techniques were evaluated and prioritized using Einstein's fuzzy WASPAS (Weighted Aggregated Sum Product Assessment) method. Combining the robustness of fuzzy logic with MCDM (Multi-Criteria Decision-Making) techniques, this approach offers an effective framework for weighting circular supply chain barriers and prioritizing big data techniques under conditions of uncertainty. Notably, this study represents the first application of Einstein's fuzzy WASPAS method in circular supply chain management. The findings reveal that SNA (social network analysis) and optimization models exert the most significant influence in mitigating implementation barriers. These insights can guide food industry managers in strategically adopting smart technologies to address key challenges in circular supply chain adoption.