Digitization in Agriculture: Leveraging the Digital Economy for Enhanced Supply Chain Efficiency and Sustainability

This paper reviews the institutional reforms in agricultural commodity markets in India and examines their implications for spatial efficiency in supply chains of the markets. In order to remove inefficiencies in the traditional supply chain, the Agricultural Produce Marketing Committee (APMC) Act was revised, and a Model APMC Act 2003 was introduced with the provisions for establishing private markets/yards, direct purchase centres, farmers markets for direct sale, contract farming and promotion of public–private partnership in the management and development of agricultural markets. Initiative has been taken to set up a National Agricultural Market as an all-India electronic trading portal to develop a ‘common national market’ for agricultural commodities. The institutional reforms in agricultural marketing system since the early 1990s appear to have contributed towards improving the spatial efficiency in rice and wheat markets. The finding of an increase in the extent of spatial integration of markets after the reforms and the tendency of the prices to move towards a common stochastic trend lend support to the idea of setting up a ‘common national market’ for agricultural commodities. Further reforms in the marketing system with better infrastructure facilities would strengthen market integration and improve efficiency in the supply chains. JEL classification: O13, Q13, Q18.

This study aims to evaluate the efficiency of agricultural supply chain using data envelopment analysis (DEA) model. This is because the supply chain of agricultural products is not regular and contains various members, which has been a limitation for analysis, but to overcome this, this study aims to systematically analyze it using the data envelopment analysis (DEA) model. The purpose of this study is to identify factors that hinder the development of the agricultural supply chain and propose strategies to improve the efficiency of the system. This study aims to verify the effectiveness of the analysis of China's agricultural supply chain, identify the main areas of inefficiency, and derive practical measures to optimize the supply chain system. This study provides implications for global agricultural supply chain cooperation between the Korean agricultural market and the Chinese agricultural market, which still has inefficiency factors, and for Korean companies to enter the Chinese agricultural supply chain market.

Abstract: The sustainability of agricultural supply chains is increasingly influenced by digital advancements, particularly in developing countries like Nigeria, where agriculture plays a vital role in livelihoods and food security. This research examines the perspectives of various stakeholders on the impact of digital technologies on enhancing the sustainability of agricultural supply chains in Nigeria. A qualitative methodology was employed to gather data through interviews and focus group discussions that included farmers, agritech business owners, policymakers, and financial institutions. Thematic analysis highlighted three main results: (i) digital platforms improve market access, financial inclusion, and the efficiency of supply chains, (ii) collaboration among stakeholders is essential for scaling and integrating digital solutions, and (iii) sustainability benefits are noticeable through reduced post-harvest losses, increased productivity, and stronger climate resilience, although challenges related to inclusivity continue to exist. The study concludes that, although digital innovation has significant transformative potential, obstacles such as infrastructural deficits, the digital divide, and policy gaps are critical challenges. It suggests expanding digital infrastructure, enhancing partnerships among stakeholders, and developing inclusive digital literacy initiatives to promote equitable and sustainable agricultural growth.

Given the state of technical advancement in modern society, blockchain technology has obvious potential in improving the transparency and efficiency of agricultural product supply chains. However, its high cost greatly influence enterprise strategy choices and adoption. Additionally, the agricultural supply chain faces several challenges, including asymmetric information, difficulties in traceability, complicated circulation links and high cost. This study explores how the deployment cost of blockchain affects the strategic choice of enterprises and to build a basic theoretical analysis framework. Also, the study analyzes the dynamic impact of blockchain technology cost on the strategic choices of agricultural supply chain by studying the case of Carrefour agricultural supply chain. The research concludes that the cost structure of blockchain technology directly drives enterprises to adopt the gradual strategy of "pilot expansion ecology". With the promotion of strategy, enterprises further mitigate the technology cost through large-scale application and ecological synergy, forming a positive cycle of "technology investment strategy upgrade cost optimization larger-scale investment".

PurposeThis article sheds light on the missing links concerning the study of using integrated enabling technologies toward sustainable and circular agriculture supply chains by examining the available literature and proposing future research possibilities.Design/methodology/approachThe relevant literature was researched through online databases such as Scopus, Web of Science, Academic Search Premier, Emerald, IEEE Xplore, Science Direct, World Scientific Net and Springer-Link Journals, covering a period from 1999 to 2020. A systematic literature review based on 75 papers analyzed the integration of the concepts of enabling technologies, sustainability, circular economy and supply chain performance in agriculture supply chains.FindingsIt was identified that enabling technologies and agriculture supply chains alone have been explored further than integrated enabling technologies, sustainability, circular economy, supply chain performance and agriculture supply chains. Enabling technologies and agriculture supply chains' main findings are: enabling technologies have been studied to improve food safety, food quality and traceability in agriculture supply chains. The main results regarding integrated enabling technologies, sustainability, circular economy, supply chain performance and agriculture supply chains are: Internet of Things and information communication technology play an important role in addressing food security, traceability and food quality, which help achieve sustainable development goals.Originality/valueThis review study provides 13 research questions to underpin future trends regarding integrated technologies' application in agriculture supply chains for circular and sustainable growth.

The Agriculture Trading Platform (ATP) represents a significant innovation in the realm of agricultural trade in Malaysia. This web-based platform is designed to address the prevalent inefficiencies and lack of transparency in the current agricultural trading environment. By centralizing real-time data on agricultural production, consumption, and pricing, ATP provides a comprehensive dashboard that facilitates data-driven decision-making for all stakeholders in the agricultural supply chain. The platform employs advanced deep learning algorithms, including Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNN), to forecast market trends and consumption patterns. These predictive capabilities enable producers to optimize their market strategies, negotiate better prices, and access broader markets, thereby enhancing the overall efficiency and transparency of agricultural trading in Malaysia. The ATP’s user-friendly interface and robust analytical tools have the potential to revolutionize the agricultural sector by empowering farmers, reducing reliance on intermediaries, and fostering a more equitable trading environment.

With the rapid development of Internet of things technology, the supply chain of agricultural products is increasing maturity in the Internet of things environment. Agricultural products supply chain in our country is in a key period from traditional mode to a modern one. This article finds out the combination point between agricultural products supply chain each link with the Internet of things, and analyzes information processing system of the agricultural supply chain under the Internet of things technology based on Internet of things technology and the characteristics of the agricultural products supply chain management, having guidance value to implementing agricultural information sharing in the IOT environment in the future.

Blockchain technology is a distributed database, which realizes the safe trans-mission and sharing of data in a decentralized system through technical means such as consensus mechanism, encryption algorithm and smart contract. Its application in the field of agriculture can effectively solve many problems in the supply chain of agricultural products. Therefore, the application of block-chain technology to agricultural supply chain management can provide security and information sharing for agricultural supply chain management, thus im-proving the operational efficiency of agricultural supply chain. This paper fo-cuses on the problems existing in agricultural supply chain and the application of blockchain technology in agricultural supply chain.

The agricultural supply chain is a complex network prone to inefficiencies, leading to significant food waste and economic losses. Artificial Intelligence (AI) offers a transformative solution to optimize agricultural supply chains, reducing waste and improving efficiency. This paper explores AI applications in agricultural supply chains, focusing on predictive analytics, route optimization, supply chain visibility, and quality control. AI-powered predictive models forecast demand, detect anomalies, and optimize production planning, reducing food waste by up to 50%. AI-driven route optimization reduces fuel consumption, emissions, and transit times. Real-time tracking and monitoring systems provide visibility, enabling quick response to issues. AI-powered quality control detects defects, monitors quality, and predicts spoilage, ensuring safer food products. Case studies demonstrate AI's potential in optimizing inventory management, irrigation, and supply chain logistics. The paper discusses challenges, future directions, and regulatory frameworks necessary for AI adoption in agriculture, highlighting AI's critical role in ensuring sustainable and efficient agricultural supply chains.

Building a sustainable and efficient green agricultural product supply chain (GASC) is crucial for ensuring global food security and promoting environmental sustainability. However, at the regional level, the spatial differentiation patterns of its efficiency and underlying driving mechanisms—particularly the synergistic relationship between technical efficiency and scale efficiency—remain to be elucidated. This study focuses on Hebei Province, a key agricultural region in China. By constructing a multidimensional evaluation index system and employing a two-stage approach combining Principal Component Analysis (PCA) with Data Envelopment Analysis (DEA), we measure and analyze the operational efficiency and regional disparities of green agricultural product supply chains across 11 prefecture-level cities. Findings revealed that the overall efficiency of Hebei’s green agricultural product supply chains required improvement and exhibited a distinct spatial pattern characterized by “high-efficiency dominance with localized lags.” The core bottleneck lies in the failure of most regions to achieve effective synergy between technology and scale, resulting in widespread resource misallocation—either “technology without scale” or “scale without technology”—and causing some areas to experience diminishing returns to scale. Furthermore, excessive reliance on single factor advantages in many cities reveals structural vulnerabilities within their supply chain systems. This study’s primary contribution lies in deepening the understanding that efficiency cannot be driven by technology or scale alone. It theoretically emphasizes that the synergistic coupling of “technology-scale” is key to enhancing the efficiency of regional green agricultural product supply chains. These findings provide empirical evidence and policy insights for building a more resilient and balanced regional green agricultural system.

The use of digital technology has been shown to be effective in managing chronic conditions. Telemedicine and mobile application are two common applications of digital technology in managing diabetic foot ulcers (DFU). The facilitators and barriers of using it for DFU management are yet to be explored. This is a qualitative systematic review. Five bibliography databases and grey literature sources were searched (2000‐2019). Two reviewers independently screened the citations, extracted the data, assessed the quality of the included studies, and performed thematic synthesis. Three studies on patients and five studies on healthcare practitioners (HCPs) were included. Two studies focused on the use of mobile applications and six on telemedicine. In studies on patients, four analytical themes were generated: the relationships with HCPs; the attitude towards the usage of digital technology; the role of wound image taking; and impact of digital technology on DFU care, encompassing 15 facilitators (eg, enabling community support, improving wound care knowledge) and 12 barriers (eg, lack of technological savviness, difficulty reading on smartphones). Three analytical themes were generated from studies on HCPs: the impact of digital technology on HCPs; the role of digital technology in DFU care; and organisation of DFU care delivery, encompassing 17 facilitators (eg, adequate wound care training, digital technology enables holistic care) and 16 barriers (eg, lack of multidisciplinary approach in caring for DFU, lack of direct contact in care provision). Patients and HCPs reported various barriers and facilitators relating to different aspects of using digital technology in DFU management. Our findings can help inform future research as well as the adoption of digital technology in DFU management.

Purpose This paper presents a comprehensive overview of existing academic research on the application of Generative AI (Gen-AI) and ChatGPT within agricultural supply chains, highlighting current trends, leading publishers, thematic areas and proposing a future research agenda. Design/methodology/approach A bibliometric analysis was conducted using VOSviewer software on a sample of 79 articles retrieved from the Web of Science (WoS) and Scopus databases to identify emerging research topics. Findings The number of publications in this area has increased, and since 2023, academic interest in the application of Gen-AI and ChatGPT to agricultural supply chains has shown a consistent upward trend. Key areas of focus include enhancing prediction accuracy, coordination, automation, employee performance, optimizing supply chain management and improving overall business outcomes. However, concerns also exist, like hallucination, data privacy, security risks, lack of accuracy, copyright issues and ethical implications. Consequently, the risk of ungoverned Gen-AI outputs without human oversight potentially disrupting operations underscores the need for robust governance frameworks to ensure its reliable integration in agricultural contexts. Practical implications Gen-AI and ChatGPT provide several advantages for agricultural supply chains. They enhance forecasting capabilities and coordination among partners, automate stakeholder interactions to increase efficiency, reduce manual tasks to improve employee performance and support data-driven decision-making through advanced analytics, ultimately strengthening supply chain management. Originality/value This study offers a structured and in-depth examination of the Gen-AI and ChatGPT phenomenon in agricultural supply chains. Moreover, it contributes to the literature by identifying existing research gaps and suggesting potential directions for future investigation.

With the continuous improvement of agricultural mechanization level, the role of supply chain management in agricultural production is becoming increasingly significant. The article aims to explore the application of big data technology in agricultural mechanization supply chain and the challenges it faces. Through remote sensing technology, Internet of Things technology, data mining, and machine learning methods, remote monitoring and intelligent management of agricultural machinery and equipment can be achieved, as well as information management of agricultural product production and circulation links, further optimizing resource allocation and enhancing the quality and market competitiveness of agricultural products. Research has found that big data technology can significantly improve the overall efficiency and response speed of agricultural mechanization supply chains, supporting agricultural producers to make more scientific and reasonable decisions. However, challenges such as data security, data quality, and data privacy also arise. To address these challenges, the article proposes implementing multi-layer encryption and access control, adopting advanced data cleaning techniques and verification mechanisms, and implementing strict data classification and anonymization processing strategies.

The study explores the transformative role of blockchain technology in enhancing transparency and traceability within the agricultural food supply chain. By leveraging blockchain's inherent characteristics of decentralization, immutability, and security, stakeholders can significantly improve information sharing and visibility from farm to consumer. The study delves into how blockchain addresses longstanding transparency and traceability issues that have plagued the agricultural sector. Real-world examples illustrate blockchain's successful application in agriculture, showcasing its capacity to boost transparency, operational efficiency, and trust among supply chain participants. These case studies demonstrate how blockchain creates tamper-proof records, enhances end-to-end visibility, and provides reliable, real time data. The technology's potential to combat fraud, promote sustainability, and ensure product authenticity is also explored. Furthermore, the research investigates blockchain's impact on food safety, particularly when integrated with Internet of Things (IoT) devices and smart contracts. These synergies enable automated, secure data collection and the execution of predefined agreements, further streamlining supply chain processes. Successful implementations across various areas of supply chain management, including logistics, inventory tracking, and quality control, are highlighted to demonstrate the practical benefits of blockchain adoption. By providing an in-depth analysis of blockchain's potential, this study underscores its pivotal role in building consumer trust regarding food safety, quality, and origin. The research concludes by discussing the challenges and opportunities for widespread blockchain adoption in agriculture, offering insights into its future trajectory and potential to revolutionize the global food supply chain.

The Internet of Things (IoT) has shown rapid growth in recent years. However, it presents challenges related to the lack of standardization of communication produced by different types of devices. Another problem area is the security and privacy of data generated by IoT devices. Thus, with the focus on grouping, analyzing, and classifying existing data security and privacy methods in IoT, based on data anonymization, we have conducted a Systematic Literature Review (SLR). We have therefore reviewed the history of works developing solutions for security and privacy in the IoT, particularly data anonymization and the leading technologies used by researchers in their work. We also discussed the challenges and future directions for research. The objective of the work is to give order to the main approaches that promise to provide or facilitate data privacy using anonymization in the IoT area. The study’s results can help us understand the best anonymization techniques to provide data security and privacy in IoT environments. In addition, the findings can also help us understand the limitations of existing approaches and identify areas for improvement. The results found in most of the studies analyzed indicate a lack of consensus in the following areas: (i) with regard to a solution with a standardized methodology to be applied in all scenarios that encompass IoT; (ii) the use of different techniques to anonymize the data; and (iii), the resolution of privacy issues. On the other hand, results made available by the k-anonymity technique proved efficient in combination with other techniques. In this context, data privacy presents one of the main challenges for broadening secure domains in applying privacy with anonymity.