With the growth of the worldwide population and depletion of natural resources, the sustainable development of food systems cannot be ignored. The demand for agri-food waste valorization practices like high-value compounds production has received widespread attention; however, numerous challenges still exist. The present study aims to identify those challenges of agri-food waste valorization and propose effective solutions based on smart technologies. Based on a systematic review of the literature, the study combs existing challenges of agri-food waste valorization and constructs a six-dimension conceptual model of agri-food waste valorization challenges. Moreover, the study integrates a Fermatean fuzzy set (FFS) with multi-criteria decision-making (MCDM) methods including stepwise weight assessment ratio analysis (SWARA), decision-making trial and evaluation laboratory-interpretative structural modeling method (DEMATEL-ISM), and quality function deployment (QFD) to evaluate the weights of each dimension, find causal interrelationships among the challenges and fundamental ones, and rank the potential smart solutions. Finally, the results indicate that the “Government” dimension is the severest challenge and point out five primary challenges in agri-food waste valorization. The most potential smart solution is the “Facilitating connectivity and information sharing between supply chain members (S8)”, which may help government and related practitioners manage agri-food waste efficiently and also facilitate circular economy.

Remanufacturing of returned products has been increasingly recognized in industries as an effective approach to face environmental responsibility, government regulations, and increased awareness of consumers. In this paper, we address a closed-loop supply chain (CLSC) in which the manufacturer produces the brand-new products, as well as the remanufactured goods while the retailer sells these products to customers. We consider several different scenarios: the manufacturer and the retailer adopt a steady-state price or a dynamic price with reference quality effects in a centralized case; either, neither or both the manufacturer and the retailer price dynamically with reference quality effects, respectively, in a decentralized model. We solve the problem with the retailer recycling the sold copies and deduce the optimal pricing strategies while the manufacturer in charge of recovering the used items in such a CLSC. The result shows that dynamic pricing strategies are much more profitable for the supply chain and its members when compared with pricing statically; the dynamic pricing strategies with time-varying quality characterized by reference quality are more suited to a long-term and cooperative closed-loop supply chain. Moreover, the optimal recycling fraction relies on the recovery cost coefficient and proves to be uniform despite adopting a dynamic price and quality in all distinct cases.

Role of nutritional status and nutritional support in outcome of hepatitis B virus-associated acute-on-chronic liver failure