Implementation of circularity in food supply chain based on big data techniques using Einstein's fuzzy methods
Rohham Farzadnia1, Payam Shojaei2, Seyed Hadi Mirghaderi1
1Department of Management, Shiraz University, Shiraz, Iran.
Scientific Reports
|August 30, 2025
Summary
Circular supply chains reduce waste, but face barriers. Big data solutions, particularly social network analysis and optimization models, are key to overcoming these challenges in Iran's food industry.
Area of Science:
- Supply Chain Management
- Industrial Engineering
- Data Science
Background:
- Circularity in supply chains enhances efficiency but faces adoption risks.
- Limited research exists on circularity barriers in Iran's food supply chain.
- Big data analytics and Industry 4.0 technologies are proposed solutions.
Purpose of the Study:
- Identify and validate barriers to circular supply chains in Iran's food industry.
- Prioritize big data-driven solutions to overcome identified barriers.
- Apply novel fuzzy MCDM methods for uncertainty management.
Main Methods:
- Literature review and content validity ratio analysis for barrier identification.
- Fuzzy SWARA (Step-wise Weight Assessment Ratio Analysis) for barrier weighting.
- Einstein's fuzzy WASPAS (Weighted Aggregated Sum Product Assessment) for big data technique prioritization.
Main Results:
- Key barriers include lack of organizational infrastructure and traceability systems.
- Social network analysis (SNA) and optimization models are most effective big data solutions.
- The study is the first to apply Einstein's fuzzy WASPAS in CSCM.
Conclusions:
- Big data techniques, especially SNA and optimization, can mitigate circular supply chain barriers.
- Findings guide food industry managers in adopting smart technologies for circularity.
- This research provides a framework for managing uncertainty in CSCM.
Related Concept Videos
01:14Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches
Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
01:29Microbes in Food Production
Microbial fermentation is central to food biotechnology, enhancing flavor, texture, preservation, and stability. Fermentative microorganisms metabolize carbohydrates into organic acids, alcohols, and other metabolites that inhibit spoilage organisms and improve digestibility while contributing distinctive sensory qualities.In baking, amylases naturally present in flour hydrolyze starch into monosaccharides such as glucose, which Saccharomyces cerevisiae ferments anaerobically. Through...