Agricultural Supply Chain Management Research Articles

Public-Private Partnerships in Supply Chain Resilience

Purpose: This study examines the importance of PPPs in supply chain resilience, particularly their collaboration with the example of Microsoft and the US Department of Agriculture (USDA). More notably, the study reports on the improvement of agricultural supply chain management and food safety through the use of cloud and soft computing technologies in the context of climate change and market volatility. Methodology: The study uses case study methods based on secondary data obtained from various reports and studies in the industry. In order to measure the impact of these strategies on their ability to reduce the risk of disruptions in supply chains. Data analysis shows measurable attributes to supply chain management and sustainability in agriculture against the backdrop of technology penetration. Findings: The findings highlight that their adoption has a positive effect on the operation and flexibility of the agricultural supply chain. The data, further, indicates that as part of the collaboration, there was an improvement in data integration, prediction, and resourcing for the USDA and Microsoft partnership, which enhanced food security and adaptation to climate change. Unique Contribution to Theory, Practice and Policy: The report suggests extending the usage of such public-private collaborations for enhancement of resilient supply chains to other areas. For present and future disruptions there is need for better partnership among the government, private technology companies and adoption of sustainable practices in supply chain management.

Advanced agricultural supply chain management: integrating blockchain and young’s double-slit experiment for enhanced security

Advanced agricultural supply chain management: integrating blockchain and young’s double-slit experiment for enhanced security

The Role of Precision Agriculture, Climate-Smart Farming, and Sustainable Supply Chain Management in Boosting Agricultural Productivity in 2024

This study explores the role of precision agriculture, climate-smart farming, and sustainable supply chain management in boosting agricultural productivity in 2024. The primary objective is to qualitatively analyze the literature to understand how these innovative practices contribute to enhancing agricultural productivity and sustainability. The research employs a qualitative literature review methodology, synthesizing findings from academic articles, industry reports, case studies, and empirical studies to provide a comprehensive overview of the current state of knowledge in this field. The literature review methodology involves systematically collecting and analyzing scholarly sources that discuss various aspects of precision agriculture, climate-smart farming, and sustainable supply chain management. The study categorizes the literature into key themes, such as the technological advancements in precision agriculture, the principles and practices of climate-smart farming, and the impact of sustainable supply chain management on agricultural productivity and sustainability. Thematic analysis is used to identify patterns and trends in how these practices interact to influence agricultural outcomes. The findings indicate that precision agriculture, through the use of advanced technologies like GPS, IoT, and AI, enables farmers to optimize field-level management regarding crop farming. This leads to increased yield, reduced waste, and better resource utilization. Climate-smart farming practices, including crop diversification, improved irrigation techniques, and soil health management, are essential for adapting to climate change and mitigating its impacts on agriculture. Sustainable supply chain management ensures that agricultural products are produced, processed, and distributed in ways that minimize environmental impact and enhance economic viability.

Application of blockchain technology in agricultural supply chain management: economic implications and challenges

This study investigates the impact of blockchain technology adoption on agricultural supply chains, focusing on transaction costs, supply chain efficiency, and farmer income. Utilizing panel data from 500 agricultural enterprises across 10 countries over a five-year period, we employ fixed effects and dynamic panel models to analyze the economic effects of blockchain implementation. Our findings reveal that blockchain adoption is associated with significant reductions in transaction costs, improvements in supply chain efficiency, and increases in farmer income. The study addresses endogeneity concerns through instrumental variable estimation and conducts extensive robustness checks to validate the results. Our analysis provides empirical evidence for the transformative potential of blockchain technology in addressing key challenges in agricultural supply chains, including information asymmetries and inefficiencies. The findings have important implications for policymakers and practitioners seeking to enhance the competitiveness and sustainability of agricultural systems through technological innovation. This research contributes to the growing literature on digital agriculture and offers insights into the role of blockchain in shaping the future of global food systems.

Research on dynamic pricing and coordination model of fresh produce supply chain based on differential game considering traceability goodwill

This study aims to solve the current pricing and coordination problems in the fresh produce supply chain by proposing a dynamic pricing and coordination differential game model based on traceability goodwill to optimize the operational efficiency and profitability of the supply chain. Freshness and traceability are critical consumer trust and brand value factors incorporated into the dynamic pricing and coordination model in the agricultural supply chain. The research methodology of this paper integrates critical factors such as supply chain cost and market demand to construct a comprehensive differential game model. It also highlights the motivation of dynamic pricing strategy and coordination mechanism based on traceability goodwill. Through traceability goodwill, operating companies can better assess and manage product quality and improve consumer trust in agricultural products, thus enhancing brand value. The dynamic pricing strategy based on traceability goodwill can flexibly adjust prices according to changes in the quality characteristics of agricultural products and market demand, realizing a dynamic balance between supply and demand. On the other hand, the mutual cost-sharing and coordination mechanism promotes the synergy between the various links of the supply chain. It improves overall efficiency through cooperation coo, coordination, and other means. The validity and reliability of the model are verified through numerical simulation experiments. The numerical simulation results show that the dynamic pricing and coordination model based on traceability will significantly improve supply chain efficiency and profitability compared with the traditional model. Specifically, the interests of supply chain participants are balanced, and the overall supply chain operational efficiency is improved. The main contribution of this study is to propose a dynamic pricing and coordination model based on traceability goodwill and verify its superiority through numerical simulation experiments. This study provides a valuable reference for fresh agricultural products supply chain management and offers new ideas for improving supply chain efficiency and profitability.

Blockchain Based Deep Learning for Sustainable Agricultural Supply Chain Management

Food supply chain (FSC) is an important part of the food supply chain. It is essential to establish food supply chains that are open to the public, accountable for their actions, and available in real time. The development of blockchain technology has led to an increase in the amount of data that is passed between customers and businesses, as well as the data that are passed between them. Blockchain technology is a new type of information technology that has the ability to be decentralized, safe, and trusted, which makes it an excellent option for storing sensitive data. The purpose of this study is to evaluate how blockchain with deep learning is used to find the quality evaluation of food supply chain technology. The use of BC has improved the accuracy of food traceability, while the utilization of Deep Random Forest (DRF) has boosted the efficacy of computing and shortened the reaction time. The research compares the quality evaluation system that is based on BC-DRF with some of the most common existing methods in terms of accuracy, reaction time, and sensitivity, when applied to a variety of block sizes.

Blockchain Empowered: Revolutionizing Agro-Based Supply Chain Management

Agriculture, the mainstay of rural India, provides livelihoods to 70% of the rural populace. However, it is beleaguered by supply chain inefficiencies, leading to losses of up to 5.99% in cereals and a whopping 60% yield loss for farmers. The prevailing supply chains are often shrouded in obscurity, with a scant 6% of businesses having complete visibility. This lack of transparency culminates in inefficient processes and potential delays in order fulfilment, engendering customer dissatisfaction and financial losses. The emergence of blockchain technology, however, offers a beacon of hope. Blockchain provides a transparent platform where all stakeholders can access and verify the movement of goods. This transparency not only bolsters customer trust but also enhances their satisfaction levels. Moreover, blockchain technology optimises inventory management and logistics, thereby reducing waste and boosting productivity. These enhancements translate into substantial cost savings. The advent of blockchain could revolutionise agricultural supply chains in India. By providing a transparent and efficient system for tracking the movement of goods, blockchain could eliminate many of the current inefficiencies. This would not only lead to increased profits for farmers but also ensure that consumers have access to fresh and high-quality produce. Furthermore, the use of blockchain could also promote sustainable farming practices by making it easier to track and verify the use of environmentally friendly methods. In conclusion, blockchain technology has the potential to transform the agricultural sector in India, making it more efficient, transparent, and sustainable. Keywords— Blockchain, Agriculture Supply chain management, Agriculture-based industries, Traceability, Smart contracts, Food quality monitoring, Sustainability.

Adoption Factors of Blockchain in Indian Agriculture Supply Chain Management Analysis using EFA

<p class="MsoNormal" style="margin-top: 10pt; line-height: 12pt; text-align: justify;"><span lang="EN-US" style="font-family: 'times new roman', times, serif; font-size: 14pt;">The global agricultural supply chain grapples with inherent challenges, including opacity, inefficiency, and ethical concerns, necessitating innovative solutions, particularly within Indian Agriculture Supply Chain Management. Despite these challenges, a notable research gap emerges due to the limited exploration of adoption factors specific to the Indian agricultural context. To bridge this gap, a comprehensive investigation is initiated to delve into the nuanced dynamics of blockchain technology adoption in the Indian agricultural supply chain. The primary aim of this study is to provide insights into these adoption dynamics, employing a three-stage methodology. Starting with an extensive literature review to identify key adoption factors, the study then distributed a well-crafted questionnaire to 200 respondents, yielding 150 complete and analyzable responses. The chosen methodologies, including a one-sample t-test and exploratory factor analysis, allow for a quantitative assessment of the significance of various factors. The study's findings reveal crucial dimensions influencing blockchain adoption, such as perceived benefits, ease of use, trust, efficiency, ethical considerations, data security, integrity, regulatory compliance, and collaboration and stakeholder engagement, providing a comprehensive understanding of the adoption landscape. In conclusion, this research significantly contributes to comprehending the nuanced adoption dynamics of blockchain technology in the Indian agricultural supply chain, supported by a substantial sample size and robust methodological choices. The implications extend to stakeholders navigating the evolving agricultural supply chain, offering valuable insights for future research, policy considerations, and practical strategies, with a central focus on fostering transparency, efficiency, and ethical standards to address global agricultural supply chain challenges.</span></p>

Impact of Internet of Things (IoT) on Enhancing Transparency and Efficiency in Bangladesh's Agri-food Supply Chain

Background: The agri-food supply chain in Bangladesh is crucial for the nation's sustenance and economic stability but faces challenges like lack of transparency, inefficiencies, and information asymmetry. The integration of Internet of Things (IoT) technologies offers transformative potential, enhancing the Transparent Physical and Information Flow (PHF) and thereby influencing the Transparency in the Agri-food Supply Chain (TASC). Objective: This study aims to investigate the impact of IoT integration on PHF and its subsequent effect on TASC in Bangladesh, framed around two core hypotheses: the significant influence of IoT on PHF and the consequent impact of an IoT-enhanced PHF on TASC. Methods: Employing a comprehensive methodological framework, the study utilized IBM SPSS for exploratory factor analysis and IBM AMOS for confirmatory factor analysis (CFA) and structural equation modeling (SEM) to assess the relationships between IoT technologies, PHF, and TASC. The analysis was based on data collected from 400 respondents in Bangladesh's agriculture sector. Results and Conclusion: The findings validate both hypotheses, demonstrating a significant and positive impact of IoT technologies on PHF and, subsequently, on TASC. The results highlight the crucial role of IoT in enhancing supply chain transparency and operational efficiency. Implications of the Research: This research provides empirical evidence on the effectiveness of IoT technologies in addressing transparency issues within the agri-food supply chain. It underscores the potential of IoT to foster improved decision-making, efficiency, and consumer trust in the agricultural sector, particularly in developing contexts like Bangladesh. Originality/Value: This study contributes original insights into the role of IoT technologies in enhancing the agri-food supply chain's transparency and efficiency. By focusing on the context of Bangladesh, it offers valuable implications for policymakers, industry practitioners, and researchers, emphasizing the transformative potential of IoT in agricultural supply chain management.

Big data-driven risk decision-making and safety management in agricultural supply chains

In the era of digitization, the integration of big data technologies has become instrumental in advancing agricultural supply chain management and bolstering risk decision-making processes. Agricultural supply chains, critical to ensuring food security and bolstering rural economies, face vulnerabilities stemming from a myriad of internal and external elements, including natural disasters and market dynamics. Consequently, the urgency to adopt effective risk management strategies is paramount. Contemporary studies have explored the utilization of big data in decision-making processes specific to agricultural supply chain risks, predominantly concentrating on preliminary risk prediction and characterization. Nonetheless, there exists a shortfall in comprehensively analyzing the intricate interplay among risk factors and establishing a holistic risk management decision-making framework based on such analyses. This research addresses these deficiencies through two principal investigative components. First, this research explores the analysis of risk factors and their interrelationships in the agricultural supply chain based on a decision tree algorithm with a transition structure. This algorithm enhances decision-makers’ understanding of risk factors and their interrelationships, and guide the implementation of effective risk mitigation measures and the formulation of contingency plans. Subsequently, the research constructs a corresponding data-driven multi-criteria decision-making method, assisting managers in balancing different risk management strategies in a volatile supply chain environment, considering costs, benefits, and feasibility to formulate the optimal strategy. The innovation of this research lies in the development of a novel risk analysis tool based on the transition decision tree algorithm. This is the first time that such advanced algorithms are applied to agricultural supply chain risk management, filling a gap in the current research. The outcomes of this study not only contribute to enhancing risk management practices within agricultural supply chains but also offer novel insights and methodological tools that are applicable in research and practices across related domains.

A novel Nash-based low-carbon implementation in agricultural supply chain management

The transition to low-carbon agriculture is seen as essential for accelerating the implementation of ecologically friendly and climate-smart agricultural supply chain management strategies. Success in these efforts depends on robust policy frameworks, effective stakeholder participation, and the availability of agricultural products to customers. This study introduces a conceptual and operational structure for the incorporation and management of an agricultural supply chain with a low-carbon scheme through the establishment of a collaborative market environment involving farmers, agricultural enterprises, and consumers. Within this framework, agricultural enterprises and farmers engage in a cooperative Nash game to determine the extent to which they are willing to employ low-carbon practices in response to collaborative market prices and government policies, including subsidies and carbon taxes. The Nash game yields a unique Nash equilibrium, suggesting the possibility of cooperative negotiations among the parties with the goal of improving their financial gains. The proposed model is applied in two Brazilian sugarcane supply chain case studies, integrating with traditional biorefinery mills to produce and market ethanol as a gasoline alternative. Our results suggest that (1) successfully allocating government subsidies and taxes motivates low-carbon adoption; (2) the government taxation policy stabilizes the low-carbon supply chain, improving stakeholder market pricing and consumer affordability; and (3) reduced cost gaps between low-carbon and non-low-carbon alternatives increase low-carbon adoption. As a result, this study provides fresh insights on the Nash collaboration of stakeholders in accordance with government policies to create a cleaner and more affordable agricultural supply chain market.

Online or offline: High temperature, sales channel adjustment, and agricultural profit

Extreme weather poses significant challenges to agricultural supply chain management, especially in developing countries. In this paper, we investigate to what degree can the adjustment of sales channels mitigate the economic consequences of supply chain risks of fresh agricultural products driven by extreme weather. Exploiting a field survey of fresh agricultural products from smallholder farmers in rural China, we empirically show that the high temperatures driven-supply risks can be mitigated by sales channel adjustment from offline to online and thus increase producers' agricultural profit. One percentage point increase in online channel sales driven by high temperature raises farmers' unit profit growth by 1.12 CNY. In the absence of sales channel adjustment, farmers’ agricultural economic losses due to high temperatures could be up to 26.65% higher. These findings are significant not only because high temperature events are predicted to increase significantly in the future, but also because they shed light on how smallholder farmers with limited adaptability to extreme weather can better adapt to adverse conditions by supply chain management - thus prospering rural e-commerce and development.

Promoting the transformation of agricultural supply chain management under the development of digital economy in the Internet era

Abstract Agricultural products, as the necessities of people’s daily consumption, are related to the national economy and people’s livelihood, and the development of information technology provides a new direction and ideas for the transformation of agricultural products supply chain management. The article proposes the risk assessment method for the agricultural products supply chain based on the Bayesian network inference algorithm and OWA algorithm, firstly constructs the Bayesian network model for risk assessment of agricultural products supply chain, elaborates on the belief updating algorithm and the belief-free updating algorithm in the Bayesian network, then combines with the OWA operator, proposes the method of risk diagnosis of agricultural products supply chain based on the Bayes-OWA hybrid operator, and with this The algorithm is the core of the proposed agricultural supply chain management strategy. Through empirical tests, it can be obtained that the average supply time of enterprise 4 in agricultural products is 22.3 days, and the reliability of supply is 92.3%, which is highly efficient. In the agricultural products supply program, the average value of quality qualification rate has been improved by 2.67%, the average number of days for supplier delivery has been shortened by 13 days, and the supplier’s ability to respond quickly to demand has been improved by 3.61%. Therefore, actively constructing the informationization construction of the agricultural supply chain, building a logistics information platform, improving rural communication facilities, and providing timely market information to farmers can better ensure the efficient operation of the agricultural supply chain.

Secure and Efficient Crop Tracking in Agriculture using Block chain

Crop tracking and traceability are crucial aspects of the modern agriculture supply chain, ensuring the safety and authenticity of products for consumers while improving efficiency and reducing waste. This paper presents a secure and efficient solution for crop tracking in agriculture by leveraging blockchain technology. The proposed system employs distributed ledger technology to record and verify the journey of crops from the field to the consumer, enhancing transparency and accountability. We explore the integration of smart contracts to automate key supply chain processes, such as quality assessment and payment settlement. Our solution not only strengthens the security of crop data but also streamlines the supply chain, reducing administrative overhead. We demonstrate the feasibility of our approach through a practical implementation, highlighting the benefits of blockchain in agriculture supply chain management.

The Role of Technology in Transforming Agricultural Supply Chain Management: Systematic Literature Review

The Role of Technology in Transforming Agricultural Supply Chain Management: Systematic Literature Review

Digital Economy Enables Community Group-buying Fresh Agricultural Products Supply Chain Management Optimization

In the context of China's digital economy promoting social development, this paper based on the characteristics of fresh agricultural products perishable, difficult to preserve and easy to wear, with the help of digital economy enabling model, explores the practical problems of community group purchase of fresh agricultural products, and analyzes its supply chain management. The analysis results show that the optimization of supply chain management depends on the digital economy, which can effectively do a good job in factor allocation, model innovation and information transmission, and achieve win-win benefits of multiple entities by improving product quality control, forming core competitiveness, balancing supply and demand and controlling costs, and meeting the diversity requirements of consumers. This study can explain the potential problems of the current agricultural product supply chain to a certain extent, and also provide a reference for the digital economy enabling community group-buying fresh agricultural product supply chain management optimization.

A Survey on Blockchain Based Solution for Agriculture Supply Chain Management

Abstract: Agriculture, a practice that spans thousands of years, has always been at the heart of human civilization. Throughout history, agriculture has continuously adapted to meet the needs of growing populations and ensure food quality, traceability, and efficiency. Recent advancements in blockchain technology have brought about significant positive changes in the agricultural sector. Blockchain has found a valuable role in agriculture, enhancing transparency, traceability, and trust throughout the supply chain. This paper provides an in-depth survey of how blockchain has impacted various aspects of agriculture, discusses the challenges it faces, and considers the promising future it holds for the industry. As blockchain adoption in agriculture continues to evolve, it promises to revolutionize the way we produce and distribute food, ensuring a more efficient, secure, and sustainable supply chain.

AgriBlock: A Blockchain based Framework for Agricultural Supply Chain Management

To facilitate complex interactions between regional players and the agricultural environment, modern agriculture supply chains have arisen. Supply chain processes that include several parties, such as production, processing, and delivery, interacting with one another. Lack of transparency in the agricultural supply chain is a major contributor to the incidence of fraud in this industry. A lack of openness on the part of organisations leads to worries about potential financial losses, diminishing customer trust, and dwindling brand value. Several fundamental changes to the existing supply chain architecture are required to foster the development of an effective and reliable trade environment. It is widely recognised that blockchain technology has the potential to increase visibility across agricultural and food supply chains. Businesses are using blockchain and IoT to implement more egalitarian, sustainable, and consumer-friendly methods of food production. Based on what we learned, blockchain technology may be useful in the push for a more transparent and responsible food supply chain. The primary goal of this study is to create a decentralised application framework called AgriBlock that can be used for managing the supply chains of agricultural products using blockchain technology. The developed work AgriBlock will aid in making the supply chain process more open and clear to every participant involved.

Factors influencing application of blockchain technology in agricultural supply chain management: Systematic literature review and social network analysis

Factors influencing application of blockchain technology in agricultural supply chain management: Systematic literature review and social network analysis

Hunger games search optimization with deep learning model for sustainable supply chain management

The supply chain network is one of the most important areas of focus in the majority of business circumstances. Blockchain technology is a feasible choice for secure information sharing in a supply chain network. Despite the fact that maintaining security at all levels of the blockchain is difficult, cryptographic methods are commonly used in existing works. Effective supply chain management (SCM) offers various benefits to organizations, such as enhanced customer satisfaction, increased operational efficiency, competitive advantage, and cost reduction. Potential SCM for agricultural and food supply chains needs distributors, coordination and collaboration among farmers, retailers, and stakeholders. The use of technology like Block Chain (BC), sensors, and data analytics, can boost traceability and visibility, decrease waste, and ensure safety and quality throughout the supply chain. Therefore, this study develops a Hunger Games Search Optimization with Deep Learning Model for Sustainable agricultural and food Supply Chain Management (HGSODL-ASCM) technique. The fundamental goal of the HGSODL-ASCM technique is to improve decision-making processes for agricultural and food commodity production and storage in order to optimise revenue. In the provided HGSODL-ASCM technique, a bidirectional long short-term memory (Bi-LSTM) model is built to determine the amount of productivity and storage required to maximise profit. In order to boost the performance of the Bi-LSTM classification process, the HGSO algorithm has been utilized in this work. The presented HGSODL-ASCM technique can independently achieve the SCM policies via interaction with complicated and adaptive environments. A brief set of simulations were performed to ensure the improved performance of the HGSODL-ASCM technique. The simulation results demonstrated how superior the HGSODL-ASCM method is to other methods already in use.