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Agriculture
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Building Resilience Through Sustainable Agri-Food Supply Chains
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Building Resilience Through Sustainable Agri-Food Supply Chains

A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Agricultural Economics, Policies and Rural Management".

Deadline for manuscript submissions: closed (20 May 2026) | Viewed by 5894

Special Issue Editor

Dr. Samir Mili

E-Mail Website
Guest Editor
Institute of Economics, Geography and Demography (IEGD), Spanish National Research Council (CSIC), Madrid, Spain
Interests: sustainable food systems; business models; food marketing; agricultural trade; agricultural policy

Special Issue Information

Dear Colleagues,

Agri-food supply chains are facing transformative pressures derived from climate change, resource depletion, changing consumption and trade patterns, technological innovations, supply-chain disruptions, and policy uncertainty. As a result, improving the sustainability of agri-food supply chains has become a critical objective in policy and practice, given the imperative of bolstering the delivery of well-being for people and the planet. Dealing with these challenges requires us to advance our collective understanding of how to create sustainable agri-food supply chains that are profitable, resilient, and secure.

How are agri-food supply chains worldwide adapting their operations and business models to become more productive and less wasteful? How do global economic dynamics impact local agri-food supply chains? Is whole-scale supply-chain transformation required to integrate sustainability principles into corporate strategies and decision-making? What barriers and drivers exist in the transition toward sustainability, and how do they affect the achievement of this goal? What policies should be implemented to create supply chains that are more resilient in the face of unexpected events? How can approaches such as network analysis, nexus perspectives, and system modeling be mobilized to improve conceptual representations of sustainability in agri-food supply chains? How can innovative technologies contribute to more sustainable performance, fewer food losses, and less waste? How can data be used to increase sustainability and strengthen decision-making along the supply chain? How can stakeholders be involved in this process?

This Special Issue welcomes contributions that address any of the above questions or related topics of utmost societal and policy relevance. This Issue will consider articles that apply a range of methodologies, whether qualitative, quantitative, or mixed, as well as both original empirical research and reviews.

Dr. Samir Mili
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agriculture is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • sustainable food production and trade
  • sustainable business models
  • conceptual representations of sustainability
  • resilience
  • eco-innovation
  • eco-management
  • digital solutions
  • profitability–sustainability trade-offs
  • sustainability in small- and medium-sized agri-food enterprises
  • sustainable investment
  • sustainability impact assessment

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Published Papers (5 papers)

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Research

Jump to: Review

39 pages, 7225 KB  
Article
Enhancing Agri-Food Supply Chain Resilience: A FIT2 Gaussian Fuzzy FUCOM-QFD Framework for Designing Sustainable Controlled-Environment Hydroponic Agriculture Systems
by Biset Toprak and A. Çağrı Tolga
Agriculture 2026, 16(8), 901; https://doi.org/10.3390/agriculture16080901 - 19 Apr 2026
Viewed by 535
Abstract
Vulnerabilities in conventional agri-food supply chains (CAFSCs) necessitate a shift toward resilient, localized production models. Within the Agri-Food 4.0 landscape, urban Controlled-Environment Hydroponic Agriculture (CEHA) systems address these challenges by shortening supply chains and mitigating climate-induced breakdowns. However, structurally aligning Triple Bottom Line [...] Read more.
Vulnerabilities in conventional agri-food supply chains (CAFSCs) necessitate a shift toward resilient, localized production models. Within the Agri-Food 4.0 landscape, urban Controlled-Environment Hydroponic Agriculture (CEHA) systems address these challenges by shortening supply chains and mitigating climate-induced breakdowns. However, structurally aligning Triple Bottom Line (TBL)-oriented stakeholder needs with complex technical specifications remains a critical challenge in sustainable CEHA system design. To address this challenge, the present study proposes a novel framework integrating the Full Consistency Method (FUCOM) and Quality Function Deployment (QFD) within a Finite Interval Type-2 (FIT2) Gaussian fuzzy environment. This approach systematically translates TBL-oriented priorities into precise engineering specifications, mapping 17 stakeholder needs (SNs) to 30 technical design requirements (TDRs) while capturing linguistic uncertainty and hesitation. The findings reveal a clear strategic focus on environmental and social sustainability. Specifically, high product quality, food safety and traceability, consumer acceptance, and minimization of environmental impacts emerge as the primary drivers of CEHA adoption. The QFD translation identifies scalable IoT infrastructure, sensor maintenance and calibration, and AI-enabled decision support as the most critical TDRs. The framework’s reliability and structural robustness were rigorously validated through comprehensive analyses, including Kendall’s W test to confirm expert consensus, alongside a Leave-One-Out (LOO) approach, weight perturbations, and a structural evaluation of TDR intercorrelations. These findings provide a scientifically grounded roadmap for designing sustainable, intelligent urban agricultural systems. Ultimately, this framework offers actionable managerial implications for agribusiness stakeholders to bridge strategic TBL-oriented goals with practical engineering, significantly enhancing agri-food supply chain resilience. Full article
(This article belongs to the Special Issue Building Resilience Through Sustainable Agri-Food Supply Chains)
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23 pages, 721 KB  
Article
Managing Business Models for Achieving Sustainable Transition in the Dairy Industry: A Multi-Case Analysis from Spain
by Samir Mili and Siwar Chouk
Agriculture 2026, 16(3), 377; https://doi.org/10.3390/agriculture16030377 - 5 Feb 2026
Viewed by 1306
Abstract
It is largely acknowledged that the dairy industry faces momentous challenges to make progress toward major environmental goals in balance with economic and social sustainability. This study addresses this concern by examining the processes of sustainability transition in the dairy industry in Spain. [...] Read more.
It is largely acknowledged that the dairy industry faces momentous challenges to make progress toward major environmental goals in balance with economic and social sustainability. This study addresses this concern by examining the processes of sustainability transition in the dairy industry in Spain. In particular, we analyzed the process of shifting from the classical, purely economic-driven business models toward more sustainable business models and also integrating environmental and social concerns. We provide a conceptual model for assessing sustainability transformation in the dairy industry and test the applicability of this model using a combination of evidence from the literature and primary information. Primary data were obtained through a dedicated questionnaire addressed to four dairy companies purposefully selected as illustrative case studies. The findings suggest that sustainability goals in the dairy industry can be represented appropriately through the proposed framework both at the sector and company levels, facilitating the identification of concrete business areas better suited for potential innovations and improvements in terms of sustainable value creation and delivery. The results also reveal the need for activity-specific assessments and a more-focused approach to sustainability practices, including the development of more comprehensive sustainability metrics and measurement methods specifically tailored to the dairy industry. Full article
(This article belongs to the Special Issue Building Resilience Through Sustainable Agri-Food Supply Chains)
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35 pages, 25567 KB  
Article
Origin Warehouses as Logistics or Supply Chain Centers: Comparative Analysis of Business Models in Sustainable Agri-Food Supply Chains
by Yiwen Gao, Mengru Shen, Kai Yang, Xifu Wang, Lijun Jiang and Yang Yao
Agriculture 2026, 16(2), 147; https://doi.org/10.3390/agriculture16020147 - 7 Jan 2026
Viewed by 719
Abstract
Origin warehouses, positioned at the critical “first mile” of the agri-food supply chain, profoundly influence supply chain power structures and profit allocation, as well as supply chain stability and sustainable development. To explore the role of origin warehouses in the agri-food supply chain, [...] Read more.
Origin warehouses, positioned at the critical “first mile” of the agri-food supply chain, profoundly influence supply chain power structures and profit allocation, as well as supply chain stability and sustainable development. To explore the role of origin warehouses in the agri-food supply chain, this study develops a three-level game model comprising a “planter–origin warehouse operator–seller” framework. Notably, this study conceptualizes the dual-functional “origin warehouse” as observed in practice, proposing two theoretical modes: the Logistics Center (LC) and the Supply Chain Center (SCC). By treating quality level, service level, and selling price decisions as endogenous variables, this study further reveals the interconnected decision-making mechanisms under different operational modes. Overall, the LC mode performs better in quality-driven markets, generating higher system profits and greater social welfare, whereas the SCC mode is superior when consumers are more price-sensitive or place greater value on service. Based on these findings, this study provides decision-making guidance for origin warehouse operators aiming to select the optimal mode under varying market conditions and proposes targeted coordination strategies to promote the high-quality development and economic sustainability of the agri-food supply chain. Full article
(This article belongs to the Special Issue Building Resilience Through Sustainable Agri-Food Supply Chains)
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33 pages, 2279 KB  
Article
The Role of New Quality Productivity in Enhancing Agricultural Product Supply Chain Resilience: A Predictive and Configurational Analysis
by Pan Liu, Weilin Nie, Shutong Yang, Changxia Sun and Qian Liu
Agriculture 2026, 16(1), 49; https://doi.org/10.3390/agriculture16010049 - 25 Dec 2025
Cited by 1 | Viewed by 936
Abstract
Currently, factors such as geopolitical conflicts, frequent extreme weather events, and power struggles among major countries are threatening the stability of the global supply chain. Building a more resilient supply chain has received international consensus. Today, new quality productivity (NQP), spawned by disruptive [...] Read more.
Currently, factors such as geopolitical conflicts, frequent extreme weather events, and power struggles among major countries are threatening the stability of the global supply chain. Building a more resilient supply chain has received international consensus. Today, new quality productivity (NQP), spawned by disruptive innovation, is an important way for China to enhance its agricultural product supply chain resilience (SCR). However, studies often overlook the “time lag” problem of the panel data adopted, and their empowering paths require further investigation. Therefore, this study firstly constructs NQP and agricultural product SCR indicators. Based on the panel data produced by 31 Chinese provinces from 2011 to 2022, we solved the “time lag” problem by integrating a Backpropagation Neural Network (BPNN) with an Autoregressive Integrated Moving Average (ARIMA) model to predict the NQP level. Subsequently, the empowering paths through NQP-enhancing agricultural product SCR were explored via entropy weight TOPSIS and Fuzzy-Set Qualitative Comparative Analysis (fsQCA) method. Foundations: China’s agricultural product SCR exhibits a spatial differentiation characteristic of “prominent in the central region and weak in the western region”. A single factor is not a necessary condition for high resilience, and its improvement depends on the synergy of multiple factors. Three differentiated driving paths have been identified: “autonomous endogenous driving type”, “environment-enabled driving type”, and “system architecture driving type”. NQMP has become the bottleneck for improving agricultural product SCR, and the threshold of each factor has increased significantly as the resilience target is raised. High resilience stems from the synergy and functional compensation of core factors, while low resilience is mostly caused by the concurrent absence of key conditions or structural mismatch, showing distinct “multiple concurrencies” and “causal asymmetry” characteristics. Full article
(This article belongs to the Special Issue Building Resilience Through Sustainable Agri-Food Supply Chains)
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Review

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22 pages, 3055 KB  
Review
Conceptualisation of Economic Injury Level and Economic Threshold: Agricultural Management, Food Security, Climate Factors, and Value Chain
by Albert Thembinkosi Modi
Agriculture 2026, 16(5), 542; https://doi.org/10.3390/agriculture16050542 - 27 Feb 2026
Viewed by 1293
Abstract
Innovations in agricultural sciences have created opportunities for a multidisciplinary approach to explain the major reasons for yield reductions under low-cost production conditions. The aim of this review is to synthesize recent advances and explain the relationship between economic injury level (EIL) and [...] Read more.
Innovations in agricultural sciences have created opportunities for a multidisciplinary approach to explain the major reasons for yield reductions under low-cost production conditions. The aim of this review is to synthesize recent advances and explain the relationship between economic injury level (EIL) and economic threshold (ET) in the contexts of food security and agri-food value chain risk management, including pre- and post-harvest stages. Modern integrated pest management (IPM) frameworks show that pest density must never be evaluated in isolation. The presence, abundance, and effectiveness of natural enemies significantly alter the likelihood that a pest population will reach the EIL. Modern food-security strategies increasingly incorporate digital innovations that enhance ET accuracy. Results of cost-benefit analysis evaluated whether the economic value of preventing crop losses outweighs the costs associated with control actions. This information is important in that it involves comparing expected yield savings, derived from preventing pest populations from reaching damaging levels, with management of the expenses of intervention and potential environmental or ecological trade-offs. The study recommends the use of artificial intelligence (AI) models to coordinate climate and economic data to predict biological consequences associated with the main threats to sustainable food systems. Full article
(This article belongs to the Special Issue Building Resilience Through Sustainable Agri-Food Supply Chains)
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