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Assessing Agri-Food Waste Valorization Challenges and Solutions Considering Smart Technologies: An Integrated Fermatean Fuzzy Multi-Criteria Decision-Making Approach

Author

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  • Qing Zhang

    (College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China)

  • Hongjuan Zhang

    (College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China)

Abstract

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.

Suggested Citation

  • Qing Zhang & Hongjuan Zhang, 2024. "Assessing Agri-Food Waste Valorization Challenges and Solutions Considering Smart Technologies: An Integrated Fermatean Fuzzy Multi-Criteria Decision-Making Approach," Sustainability, MDPI, vol. 16(14), pages 1-25, July.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:14:p:6169-:d:1438198
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    References listed on IDEAS

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    1. Luo, Na & Olsen, Tava & Liu, Yanping & Zhang, Abraham, 2022. "Reducing food loss and waste in supply chain operations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 162(C).
    2. Nathan D. DeLay & Nathanael M. Thompson & James R. Mintert, 2022. "Precision agriculture technology adoption and technical efficiency," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(1), pages 195-219, February.
    3. Bag, Surajit & Dhamija, Pavitra & Singh, Rajesh Kumar & Rahman, Muhammad Sabbir & Sreedharan, V. Raja, 2023. "Big data analytics and artificial intelligence technologies based collaborative platform empowering absorptive capacity in health care supply chain: An empirical study," Journal of Business Research, Elsevier, vol. 154(C).
    4. Ancín, María & Pindado, Emilio & Sánchez, Mercedes, 2022. "New trends in the global digital transformation process of the agri-food sector: An exploratory study based on Twitter," Agricultural Systems, Elsevier, vol. 203(C).
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    Cited by:

    1. Gonca Tuncel & Busranur Gunturk, 2024. "A Fuzzy Multi-Criteria Decision-Making Approach for Agricultural Land Selection," Sustainability, MDPI, vol. 16(23), pages 1-13, November.

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