Agro-food Supply Chain Research Articles

From Farm to Table Concept: The Profile and Dynamics of Urban Farming on Agrofood Supply Chain in Malaysia

From Farm to Table Concept: The Profile and Dynamics of Urban Farming on Agrofood Supply Chain in Malaysia

Supply chain risk assessment using best worst method: a case study of agro-industry skipjack tuna in Ambon - Indonesia

One of the main issues in the agro-industry supply chain is identifying and ranking different risk factors to maintain business continuity. This study discusses the agro-food supply chain risk assessment for smoked skipjack tuna in Ambon. Related literature and expert interviews identify risk factors that arise along the supply chain. These risk factors are contained in internal risk, company external operational risk, and macro-level risk. This research aims to evaluate comprehensively the risk factors of the smoked skipjack agro-industry supply chain, which are a priority to be addressed. The decision-making framework uses the BWM (Best Worst Method) to determine each risk factor's relative weight, followed by a sensitivity analysis to determine how robust the outcome is. Experts pick the risk factor assessment, and then an optimization model is modelled to obtain the weight of each risk factor, which is calculated with the help of Lingo software. The findings show that three risk factors will be prioritized to be addressed out of the eleven risk factors assessed, namely "Quality of the final product," "Financial instability," and "degradation of fish populations." Sensitivity analysis was also carried out to see the overall robustness of the results achieved. The weight of the selected risk factor ("final product quality (R1c)") has its weight value changed from 0.1 to 0.9 with an increase of 0.1. These findings are expected to help smoked skipjack tuna agro-industry managers make decisions to reduce supply chain risks and better administration management to maintain the sustainability of their business processes.

Group decision making model for selection of performance indicators for sustainable supplier evaluation in agro-food supply chain

Sustainable food production is of vital importance to ensure food security, enhanced stability, environmental protection, and economic development for any developing nation. In an Agro- Food Supply Chain (AFSC), joint efforts of all supply chain actors inclined towards sustainability can contribute significantly towards sustainable production. Suppliers, who are intermediaries between Food Processing Firm (FPF) and sub-suppliers or farmers, must follow the FPF's sustainability practices at their own level, and they must monitor the enactment of these activities at their sub-supplier level. In this regard, the study focuses on developing a group consensus mathematical model to derive a broader set of performance indicators to evaluate a supplier's competency in maintaining, monitoring, and tracing sustainable performance in his sub-supplier network. A two-phased group consensus model is presented; it selects performance indicators using the Delphi method and it utilizes a feedback mechanism rooted in Group Analytical Hierarchy Process. This system is based on an iterative algorithm to generate weights that all decision makers accept. The proposed model is illustrated with an analysis of an Indian flour milling company. Kendall's concordance coefficient is employed to understand the degree of agreement among decision makers before and after the application of the proposed model. Increase in its value post-application validates the efficacy of the model. This approach for performance indicator selection for sustainable supplier evaluation research is unique in the field of AFSC. Results of the study indicate that the top ranking indicator is ‘Food Safety’ followed by ‘Payment to Sub-suppliers’. Key policy implications are drawn from the result findings which can be further integrated to support sustainable growth and development of suppliers and sub-suppliers in any AFSC.

Agro-Food Supply Chain Risk Assessment: A Review Based on Technique and Approach

Agro-Food Supply Chain Risk Assessment: A Review Based on Technique and Approach

Digital Technology Increases the Sustainability of Cross-Border Agro-Food Supply Chains: A Review

The increasing prominence of climate change, geopolitical crises, and global economic slowdown highlights the challenges and structural deficiencies of traditional cross-border agro-food supply chains. As a result, there has been a growing consensus on the need to leverage digital technology to rebuild and innovate a safe, stable, and sustainable global food system. This study assessed the knowledge progress and development trends in the sustainable development of cross-border agro-food supply chains enabled by digital technology. A total of 352 authoritative papers from the core Web of Science database were selected for analysis. The Citespace tool was utilized to visually examine research elements. The findings reveal that research outcomes in this territory experienced a significant period of rapid growth, particularly after 2020. Sustainability and IEEE Access are the journals with the highest and second-highest number of publications. China and the France National Institute are the countries and research institutions with the largest number of publications in this field. The research hotspots are mainly the application of digital technologies, food safety, and supply chain system model innovation. In the past ten years, the research in this territory has gone through three stages: precise timeliness orientation, intelligent strategic decision-making orientation, and model predictability orientation. We further construct the ‘antecedent–practice–performance’ conceptual framework of the sustainability of the digital technology-enabled cross-border agro-food supply chain. Finally, this paper presents the potential research directions in this territory, focusing on four aspects: research method, research mechanism, research topic, and research frontier.

Circular economy in agro food supply chain: Bibliometric and network analysis

AbstractRecently, there has been growing interest among scholars and industry professionals in understanding how agro‐food supply chains can shift from a linear to a circular model. This involves managing waste, recovering resources, and adopting sustainable practices. However, knowledge on circular economies in agro‐food supply chains is scattered, with limited comprehensive studies available. To address this gap, our study conducts a bibliometric and network analysis of 364 documents from the Scopus database. We identify influential authors, contributing countries and journals, and most cited documents. Additionally, we use network analysis to visualize connections between authors and keywords, providing insights into emerging trends and critical research areas. We also uncover important keywords and themes, laying a foundation for future research directions. Overall, our study offers a comprehensive overview, serving as a basis for further exploration in this field.

Sustainable Agriculture Leveraging Artificial Intelligence Systems in Kenya's Agri-food Supply Chain

The Agro-food supply chain is crucial for achieving Sustainable Development Goal No. 2 of zero hunger and sustainable agriculture. However, Kenya faces significant post-harvest losses, mainly attributed to challenges in first and last-mile logistics. In the era of technological advancements, this research paper explores the potential of Artificial Intelligence (AI) to enhance the Kenyan agri-food supply chain. Building on existing information, the study focuses on AI's role in monitoring and controlling farmland outputs, optimizing supply chain logistics, and addressing fraud and counterfeiting. The research objectives include assessing AI's utility in monitoring and controlling outputs in farmlands improving supply chain efficiency, and combating fraud in agricultural inputs. Research methods involve a comprehensive literature review, analyzing case studies such as Project FARM and FAO's Fall Armyworm Monitoring and Early Warning System, and reviewing scholarly articles on AI applications in agriculture. The research results highlight the benefits of leveraging AI in farmland monitoring, climate change adaptation, supply chain logistics, and fraud prevention. AI technologies can enhance agricultural productivity, reduce transportation costs, and eliminate corruption in the supply chain. The findings suggest that integrating AI systems into the agri-food supply chain is vital for achieving sustainable agriculture in Kenya. The study concludes that AI offers innovative solutions to address the challenges faced by smallholder farmers, enhance supply chain efficiency, and contribute to achieving zero hunger and sustainable agricultural practices.

Agro-Food Supply Chains in Peri-Urban Agricultural Areas: Do They Contribute to Preserve Local Biodiversity? The Case of Baix Llobregat Agrarian Park

Peri-urban regions, especially in the Mediterranean, face challenges like farmland loss due to urban pressure. This study emphasizes retail stores as strategic focal points for evaluating societal, economic, and production systems. It hypothesizes that analyzing retail stores in agricultural areas provides insights into traded and cultivated agrobiodiversity. Using the Baix Llobregat Agrarian Park (Catalonia, NE Iberian Peninsula) as a case study, this research examines different food retailers from short and conventional food supply chains. Results indicate variations in plant diversity, origin, and seasonality among different retail stores. Farmers’ markets exhibit higher intraspecific diversity, contributing to local agrobiodiversity conservation. This study observes temporal changes in farmers’ markets, highlighting shifts influenced by socioeconomic factors and climate change perceptions. Finally, this research underscores certain strategies to promote sustainable peri-urban local food systems and preserve agrobiodiversity, offering valuable insights into food supply chain dynamics in peri-urban agricultural regions.

What impedes digital twin from revolutionizing agro-food supply chain? Analysis of barriers and strategy development for mitigation

What impedes digital twin from revolutionizing agro-food supply chain? Analysis of barriers and strategy development for mitigation

The relationship between the adoption of agricultural revolution 4.0 technology and business performance and sustainability in agro-food supply chain in Malaysia: a conceptual paper

The present study is based on the review of literature related to the adoption of Agricultural Revolution 4.0 (AR4.0) technology, business performance and sustainability dimensions. The new National Agro-food Policy 2.0 (DAN 2.0) was formulated to transform agriculture into a more dynamic, sustainable, and competitive industry in which the agro-food supply chain is one of the most important parts of the agricultural sector in Malaysia. In order to boost the agriculture sector’s competitiveness and sustainability, the sector is encouraged to fully utilize digital technology in agriculture. From this perspective, the adoption of the Agricultural Revolution (AR4.0) could provide numerous benefits, particularly in terms of enhancing the business performance for a sustainable agro-food supply chain. Thus, the business world today is moving towards “Digitalization 4.0” to focus on increasing the performance that will sustain the industry. Due to greater possibilities of economic, environmental, and social impacts along supply chain activities, the adoption of Agricultural Revolution 4.0 (AR4.0) into the industry supply chain is gaining more attention in the agricultural sector. The main objective of this study is hence to generate the conceptual framework between the relationship of adoption of Agricultural Revolution 4.0 (AR4.0) towards Agro-food supply chain (AFSC) business performances (flexibility, delivery, quality and cost) and AFSC sustainable agricultural performance encompassing economic, environmental and social dimensions in sustainability. The conceptual paper signifies providing academia with additional literature to use as a reference for future research. The findings of this research could help the agricultural industry to leverage Agricultural Revolution 4.0 (AR4.0) technology in order to boost their business performance. It will also be useful to policymakers in creating support mechanisms and plans to improve the overall performance of the firm.

Towards Trusted Data Sharing and Exchange in Agro-Food Supply Chains: Design Principles for Agricultural Data Spaces

In the modern agricultural landscape, realizing data’s full potential requires a unified infrastructure where stakeholders collaborate and share their data to gain insights and create business value. The agricultural data ecosystem (ADE) serves as a crucial socio-technical infrastructure, aggregating diverse data from various platforms and, thus, advertising sustainable agriculture and digitalization. Establishing trustworthy data sharing and exchange in agro-food value chains involves socioeconomic and technological elements addressed by the agricultural data space (ADS) and its trust principles. This paper outlines key challenges to data sharing in agro-food chains impeding ADE establishment based on the review of 27 studies in scientific literature. Challenges mainly arise from stakeholders’ mistrust in the data-sharing process, inadequate data access and use policies, and unclear data ownership agreements. In the ADE context, interoperability is a particularly challenging topic for ensuring the long-term sustainability of the system. Considering these challenges and data space principles and building blocks, we propose a set of design principles for ADS design and implementation that aim to mitigate the adverse impact of these challenges and facilitate agricultural data sharing and exchange.

Multi-objective optimization of agro-food supply chain networking problem integrating economic viability and environmental sustainability through type-2 fuzzy-based decision making

Balancing economic and environmental considerations in Agro-Food Supply Chain Networks (AFSCNs) is a critical challenge faced by decision-makers in developing countries. This study focuses on the Apple industry’s supply chain network problem and emphasizes the importance of environmentally friendly transportation systems. To address this concern, a multi-objective mixed-integer transportation model is developed to maximize profit by considering revenue and rewards for lower CO2 emissions while simultaneously minimizing costs associated with purchase, loading, unloading, transportation, fixed expenses, CO2 taxes, and penalties for exceeding permitted emission levels and reducing overall carbon dioxide (CO2) emissions in the AFSCN. Uncertain parameters, including revenue, purchase cost, loading cost, unloading cost, reward, fuel consumption, and CO2 emissions for different fuel-type vehicles, are handled using type-2 picture fuzzy numbers for accounting for uncertainty. The data and information used in this study were acquired from a survey conducted among Apple industry wholesalers in Shimla, Mandi, and Kothkai in Himachal Pradesh, providing authentic and reliable insights on supply chain network dynamics. The proposed multi-objective model is solved using LINGO 19.0 optimization software, utilizing diverse optimization methodologies, including the weighted sum method, fuzzy goal programming, interactive fuzzy satisfying technique, global criteria methodology, and weighted Tchebycheff metrics programming. This enables decision-makers to make informed choices and optimize the AFSCN’s problems on economic and environmental performance. Additionally, sensitivity analysis is conducted to evaluate the model’s resilience and responsiveness to changes in the carbon budget, carbon cap, and CO2 emission sources. The results demonstrate the model’s suitability for assessing different scenarios and policy measures, providing insights into the potential impact on the AFSCN’s economic viability and environmental sustainability.

Analysis of barriers for sustainable agro-food supply chain: an interpretive structural modeling and MICMAC approach

Analysis of barriers for sustainable agro-food supply chain: an interpretive structural modeling and MICMAC approach

A Bi-Objective Mixed-Integer Linear Programming Model for a Sustainable Agro-Food Supply Chain with Product Perishability and Environmental Considerations

Background: Agro-food supply chains possess specific characteristics due to the diverse nature of products involved and contribute to all three pillars of sustainability, making the optimal design of a sustainable agro-food supply chain a complex problem. Therefore, efficient models incorporating the unique characteristics of such chains are essential for making optimal supply chain decisions and achieving economically and environmentally sustainable agro-food supply chains that contribute to global food security. Methods: This article presents a multi-objective mixed-integer linear programing model that integrates agricultural-related strategic decisions into the tactical design of an agro-food supply chain. The model considers transportation, inventory, processing, demand fulfilment, and waste disposal decisions. It also accounts for seasonality and perishability, ensuring a comprehensive approach to sustainability. The model aims to maximize the total generated profits across the supply chain while simultaneously minimizing CO2 emissions as a measure of environmental impact. Results: By implementing the model on a sugar beet supply chain in the Netherlands, strategic crop rotation farm schedules for the crop rotation cycle and the optimum supply network decisions are obtained. Furthermore, different objectives are analyzed and the Pareto-efficient frontier is investigated to analyze the underlying trade-offs. Additionally, the model serves as a decision support tool for managers facilitating informed investment decisions in technologies that prolong product shelf life while maintaining profitability. Conclusions: The proposed multi-objective model offers a valuable framework for designing economically and environmentally sustainable agro-food supply chains. By aligning with sustainability goals and providing decision support, this research contributes to enhancing global food security and promoting sustainable resource utilization.

Territorial rural development strategies based on organic agriculture: the example of Valposchiavo, Switzerland

The disembedding nature of globalization is being tackled by integrated and territorial approaches that focus on local contexts and include multiple actors and sectors. One example are biodistricts that rely on values of organic agriculture to strengthen territorial agro-food systems. The remote rural mountain valley of Valposchiavo, Switzerland, follows such a territorial approach and is subject of this case study. In this article we aim to understand in detail the processes of territorial development strategies in Valposchiavo. To shed light on the development approach, we used the theoretical concept of neo-endogenous development by Ray. We conducted document analysis, secondary interview analysis as well as problem-centered interviews. The results indicate that the rural development approach follows a neo-endogenous development that renews rural–urban linkages by developing internal and external networks. The creation of a territorial brand and a regional development project contribute to the establishment of local and organic agro-food supply chains. The territorial development approach in Valposchiavo demonstrates how remote mountain areas can shape the well-being of their community and tackle negative impacts of globalization.

Supply Chain Orientation and Supply Chain Risk Management Capabilities: Mechanisms for Supply Chain Performance of Agro-Food Processing Firms in Uganda

ABSTRACT Today’s agro-food supply chains have become increasingly complex and vulnerable to risks, which affect their performance. Nevertheless, research on agro-food supply chain performance (SCP) is reportedly limited. And the mechanism through which supply chain orientation (SCO) builds SCP, especially in developing economies is less understood. Therefore, this paper explores the relationship between SCO and SCP, and incorporates the mediating role of supply chain risk management (SCRM) capabilities. Cross-sectional survey data collected from 247 agro-food processing firms in Uganda are analyzed by using Partial Least Square Structural Equation Modeling. The findings reveal that SCO positively and significantly influences both SCP and SCRM capabilities. Furthermore, SCRM capabilities partially mediate in the relationship between SCO and SCP. The novelty of this research is twofold: First, it establishes the relationship between SCO and SCP in a unique context of agro-food processing firms in a developing country. Second, it reveals the partial mediating role of SCRM capabilities, thereby addressing the gap of the need to explore the mechanisms through which SCO influences SCP. The fundamental implication of the study findings for practicing managers and other relevant stakeholders in agro-food processing firms in Uganda and other contextually similar economies is that, a focus on SCO can improve SCP, but it is important to further emphasize building SCRM capabilities as mechanisms for maximizing the overall SCP.

Recent Advances in Health Benefits of Bioactive Compounds from Food Wastes and By-Products: Biochemical Aspects.

Bioactive compounds, including terpenoids, polyphenols, alkaloids and other nitrogen-containing constituents, exert various beneficial effects arising from their antioxidant and anti-inflammatory properties. These compounds can be found in vegetables, fruits, grains, spices and their derived foods and beverages such as tea, olive oil, fruit juices, wine, chocolate and beer. Agricultural production and the food supply chain are major sources of food wastes, which can become resources, as they are rich in bioactive compounds. The aim of this review is to highlight recent articles demonstrating the numerous potential uses of products and by-products of the agro-food supply chain, which can have various applications.

Agro-Food Supply Chain Traceability using Blockchain and IPFS

Many blockchain initiatives significantly use the InterPlanetary File System (IPFS) to store user data off-chain. The centralized administration, ambiguous data, unreliable data, and ease of creating information islands are all issues with traditional traceability systems. This study develops a monitoring system using blockchain technology to record and inquire about product information in the supply network of Non-Perishable (NP) agro goods to address the above issues. The transparency and trustworthiness of traceability data were considerably improved by employing blockchain technology's distributed, tamper-proof, and traceable properties. To alleviate the strain on the blockchain and enable efficient information inquiry, a storage structure is built in which both public and private data are stored in the blockchain and the Inter Planetary File System (IPFS) using cryptography. Because of its ability to trace the origin of food, blockchain technology contributes to the development of reliable food supply chains and the establishment of rapport between farmers and their customers. Since it provides a secure location for data to be kept, it can pave the way for implementing data-driven farming techniques. In addition to improving data security, recording farm data in IPFS and storing encrypted file IPFS hashes in smart contracts solves the issue of blockchain storage explosion. And when used in tandem with smart contracts, it enables instantaneous outflows between parties in response to changes in data stored in the blockchain. The paper also offers simulations of the implementation and analysis of the performance. The findings validate that our system improves security for sensitive information, safeguards supply chain data, and meets the needs of real-world applications. Furthermore, it boosts throughput efficiency while reducing latency.

Sustainability in the agri-food supply chain: a combined digital twin and simulation approach for farmers

The paper seeks to provide a research and practical study to strengthen the resilience of smallholders to unexpected crises like COVID-19. Farmers are usually not assisted by the current technological capabilities while uncertainty is greater than ever. In comparison, with existing static assessments, digital twins use cases in the agricultural sector are still in conceptual and prototype levels. In this regard, the paper aims to provide a framework with the potentials for sustainability for farmers derived from five pillars and their modelling on a digital twin model with simulation capabilities. The goal is to develop an approach and a tool that would enhance the capabilities of smallholders to face any disruption by supporting them in all their management and control activities. Thus, the model aims to analyze the effects of risks as well as the policies that can prevent them, act to reduce their impacts, or react against any internal or external risks in three levels: farmer´s organization, supply chain, and the related environment based on the Corporate Social Sustainability. The purpose is to increase the resilience of smallholders through the improvement and optimization of the agro-food supply chain and related environment of any smallholder organization considering all related stakeholders. As a result, the final goal of the model is the development of recommendations for enhancing future capabilities to secure viability in the long-term.

Social co-governance for sustainable brand in food industry: dynamic evolutionary game among multiple stakeholders

Social co-governance is imperative for the sustainable brand building. In this paper, we establish a sustainable brand system by integrating vertical and horizontal cooperation to address the issues which include the mechanism of the social co-governance and the effects of the enforcement approaches in the brand building. First, a new vertical cooperation is considered into the current paradigm of agro-food supply chain by integrating the consumers while the social co-governance is perceived as an effective way of horizontal cooperation. Then, we investigate the dynamic changes in the profitability or utility of these stakeholders in the system. Consequently, this paper designs three evolutionary models including Government-Manufacturer-Society Game (GMSG) model, Farmer Intra-group Game (FIG) model and Consumer-Market Game (CMG) model. Finally, the systemic dynamics models examine how the system performs in the different scenes. The primary results indicate the social co-governance has maximizing utility of brand construction. And the strict enforcement performs better than creative strategies in the early stages. Whereas the creative strategies outperform as the value of sustainable raw material output increases.