Leveraging deep learning for agricultural market forecasting and supply chain optimization in Malaysia

PurposeThis paper aims to address the conceptual and practical challenges in integrating triple bottom line (TBL) sustainability in the agriculture supply chain (ASC). It identifies the key enablers for each of the three dimensions of TBL sustainability, analyses their causal relationships as well as cross-dimensional interactions under each TBL dimension. Further, it develops a decision support framework (DSF) for the assessment of TBL sustainability practices and policies in ASC and validates it through a case study.Design/methodology/approachAn interpretive structure modelling (ISM) methodology is deployed to establish the interrelationships among all TBL enablers and to identify the enablers with high driving power on sustainable ASC. Brainstorming by a group of experts was used to identify the relevant enables. Finally, a DSF was developed as a resultant of ISM.FindingsThe paper provides a set of enablers with high driving power that can significantly influence the sustainability practices and policies in ASC. The social enablers directly help to enhance the effect of economic enablers and collectively these enhance the effect of environmental enablers. If agriculture firms and supply chains design innovative policies and develop practices based on these enablers, they can achieve sustainable ASC. Consequently, the living standards of the people directly or indirectly associated with the agriculture firm or supply chain can be improved without compromising on economic performance.Research limitations/implicationsThe paper consolidates the fragmented knowledge of sustainable supply chain management in the agriculture sector and suggests a DSF to policymakers, managers and practitioners for assessing TBL sustainability practices and policies. The DSF has wide applicability in other sectors of production and operations management as these sectors also face the challenge of achieving TBL sustainability across their supply chain.Practical implicationsThe DSF, developed in the paper, is a useful tool for practitioners to frame and analyse sustainability initiatives and policies for ASC. A firm or supply chain may achieve TBL sustainability if it succeeds in uplifting the social status of its stakeholders.Social implicationsIt is a first step towards addressing the practical challenge of integrating sustainability in the agriculture sector of emerging economies and provides a path to improve the livelihood of people in the agriculture sector. Stakeholder engagement with a focus on collaboration and awareness may lead to the desired social and environmental consequences. Potential adverse social effects also need to be considered.Originality/valueThis paper focusses on the so far rather neglected but essential aspect of integrating TBL sustainability in the agriculture sector of emerging economies. The hierarchal representation and classification of the TBL sustainability enablers of sustainability is a unique effort in the field of ASC. Development of DSF is one of the first attempts to create a mapping between various enablers of TBL sustainability. The novelty of the study lies in the sector-specific, holistic evaluation of TBL sustainability policy measures that may lead to improvements in practice.

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.

Agriculture and allied activities hold a key to sustaining all human activities and ensuring a food-secured future. However, significant issues such as the ever-growing population and cut-throat competition for resources pose a continuous threat to the agricultural supply chains, thereby compromising sustainable agricultural development. To overcome the ever-escalating complex challenges in agricultural supply chains and production systems, advancements in precision agriculture, smart farming, and effective supply chain collaboration are critical for addressing agricultural sustainability challenges. This research study examines the direct effects of industry 4.0 technology capabilities (I4TC) and supply chain integration (SCI) on sustainable agricultural supply chain performance (SASCP). The study investigates the direct and indirect impact of I4TC on SASCP with SCI as the mediating variable; moreover, it seeks to validate the direct influence of I4TC on SCI and SASCP. Based on the data collected from 262 food processing organizations in India, the findings highlight noteworthy impacts of I4TC on SASCP and verify the presence of SCI as a partially mediating variable. Furthermore, the findings extend the body of knowledge on I4TC by recognizing I4TC as an enabler of SCI, thereby leading to enhanced SASCP. From the practitioner's perspective, the current study can help food-processing organizations better understand the importance of SCI in ASCs and provide valuable insights for managing ASCs to achieve SASCP.

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".

With the increasing prominence of food safety problems, consumers are paying more and more attention to the quality and safety of agricultural products. Information traceability of agricultural products supply chain is an important way to ensure the quality and safety of agricultural products. Blockchain technology provides a new solution for information traceability of agricultural products supply chain with its characteristics of decentralization, immutable and transparency. This paper reviews the basic principles of blockchain technology and its application in agricultural supply chain information traceability. By combing relevant literature, it is found that blockchain technology is widely used in the production, processing, logistics and other aspects of agricultural products, effectively improving the transparency and traceability of the supply chain. Finally, it is concluded that the information traceability of agricultural product supply chain under the blockchain improves the traceability, visibility and information security of the supply chain, and also promotes the cooperation and coordination among various entities in the supply chain. With the continuous development and improvement of blockchain technology, its application in agricultural product supply chain information traceability will be more extensive and in-depth, providing more solid technical support for the quality and safety of agricultural products.

Environmental factors in time and space play a critical role in advancing the sustainable development of the fresh agricultural product supply chain. This paper, availing the panel data of 31 Chinese provinces from 2008 to 2019, constructs a system of indicators assessing the development of the fresh agricultural product supply chain, and obtains the comprehensive development level in the Entropy Weight Method (EWM). Furthermore, it establishes a comparison between optimal solutions generated by the Instrumental Variables Method (IVM) and the Generalized Method of Moments (GMM) over the endogeneity issue of variables, creates the comparison between the weighted regression methods of Geographically Weighted Regression (GWR) and Multi-scale Geographic Weighted Regression (MGWR), and obtains the relationship among the 14 environmental factors in their spatio-temporal impacts on the development of the fresh agricultural product supply chain. The results indicate that: (1) the environmental influencing factors in this paper have significant endogenous problems and various environmental factors impact on the fresh agricultural product supply chain in different trends and to different degrees. (2) With different bandwidths, the environmental factors could impact the fresh agricultural product supply chain to greatly varied degrees, demonstrating a strong attribute of regional correlation.

Building an “autonomous and controllable, safe and stable” agricultural product supply chain is an important part of coordinating national food development and security stability. Based on the TOE framework, this paper constructs an integrated theoretical model for enhancing the resilience of agricultural product supply chains. Using fsQCA, a configurational analysis of 30 provincial cases in China is conducted. The study finds:1.According to the different combinations of core conditions and peripheral conditions, four paths driving high-level agricultural product supply chain resilience are identified: coordinated development type, internal drive type, intermediary role type, and institutional openness type;2. Based on the TOE framework, technological empowerment-New Quality Productivity、organizational coordination-high-quality development of the logistics industry and various environmental variables cannot constitute necessary conditions for explaining high agricultural product supply chain resilience;3. In the equivalent configurations for enhancing the resilience of agricultural product supply chains, there are differences in the interaction of differentiated conditional variables and the functional performance of the same variable in different configuration settings;4. There is an asymmetry of causal relationships between the conditional configurations of high agricultural product supply chain resilience and non-high agricultural product supply chain resilience;5. New Quality Productivity and low urbanization rates play a particularly prominent role in improving the resilience of agricultural product supply chains, and the high-quality development of the logistics industry, as a peripheral condition, also plays a key role.

Agricultural food supply chain is a complex system starting from the production of food on a farm to the table of the consumer involving multiple stakeholders and a variety of processes. In recent years, the food supply chain has grown rapidly across nations, with customers demanding fresh, exotic foods all year round. The global shutdown due to the COVID pandemic has further complicated the food supply chain which has become prone to various contaminations and adulterations. Adulterated food is highly toxic to human health leading to several health issues, nutritional deficiencies, kidney disorders, and failure of vital organs. The existing systems used in the food supply chain do not provide enough transparency, traceability, food safety, or consumer trust. With today’s Big Data integrated supply chains, such technologies are highly ineffective. In order to ensure food safety and consumer satisfaction, this chapter proposes using blockchain as an efficient technology to provide transparency, traceability, and trust in food supply chains. The chapter discusses the significance of smart agriculture and how blockchain might help agricultural supply chains that have Big Data incorporated overcome their difficulties. A thorough description of exclusive applications of blockchain in Big Data integrated food supply chains is provided. The chapter also describes how blockchain is integrated into each stage of the food supply chain management process and explores the challenges in implementing blockchain in Big Data integrated food supply chain systems.

One year into the largest economic and health event of the past 70 years, this paper considers how agricultural supply chains and agricultural transportation have been impacted by the COVID‐19 pandemic. Written as an update to Gray (2020), we are able to show that agricultural transportation systems have proven to be extremely robust and were able to innovate in real‐time to address challenges in the agricultural and food supply chains. We are also able confirm that most of the transportation components are well‐equipped to deal with the remainder of the pandemic and the recovery phase. Notably, innovation created new services, cost‐saving technologies, safety innovations, new institutions, networks, and channels of communication that operated effectively to address the pandemic. These changes are likely to remain in place post pandemic.

Against the backdrop of domestic and international dual circulation and rural revitalization, artificial intelligence (AI) serves as the core impetus driving the digital transformation of the agricultural product supply chain. Existing research mostly focuses on the application ofAI in a single link of the agricultural supply chain, lacking studies from the perspective of e-commerce platforms on how to solve the problem of dispersed supply chain entities and achieve full-chain collaboration. This paper takes the Pinduoduo's Agricultural Land Cloud Group Buying Project as the research object and uses the case study method to analyze the empowerment practice of AI in the entire process of agricultural supply chain production, circulation, and sales, and explores the impact of macro and micro factors on the empowerment effect of AI. The research finds that the project has achieved the compression of supply chain links, reduction of losses, and increase in sales through AI, but it faces bottlenecks such as the low digital literacy of elderly farmers and the tilt of platform R&D resources towards the sales end. Based on this, this paper designs optimization paths from three dimensions: e-commerce platforms, government departments, and research institutions, providing theoretical and practical references for e-commerce platforms to empower the digital transformation of the agricultural supply chain.

PurposeWith the rapid growth of the economy, people have increasingly higher living standards, and although people simply pursued material wealth in the past, they now pay more attention to material quality and safety and environmental protection. This paper discusses the lack of motivation for investing in fresh-keeping technology for agricultural products by individual members of an agricultural supply chain composed of a supplier and a retailer by means of mathematical models and data simulations and discuss the optimal price-invest strategies under different sales models.Design/methodology/approachFirst, based on the model of no investment by both sides (NN), this paper considers three models: supplier only (MN), retailer only (NR) and cooperative investment (MR). Then, the authors analyze the influence of consumer price sensitivity and freshness sensitivity on the investment motivation of agricultural products under four models. Subsequently, the paper makes a sensitivity analysis of the optimal strategies under several models, and makes a game analysis of the suppliers and retailers of agricultural products. Finally, we conduct an empirical analysis through specific values.FindingsThe results show that (a) when the two sides cooperate, the amount of investment is largest, the freshness of the agricultural products is highest, and the sales volume is greatest; however, when both sides do not invest, the freshness of agricultural products and sales volume are lowest. (b) The price and freshness sensitivity of the consumer have an impact on investment decisions. Greater freshness sensitivity corresponds to a higher investment, higher agricultural product price, greater sales volume, and greater supply chain member income and overall income; however, greater price sensitivity corresponds to a lower investment, lower agricultural product price, lower sales volume, fewer supply chain members and lower overall income. (c) The investment game between the supplier and retailer is not only related to the sensitivity to price and freshness but also to the coordination coefficients of interest. At the same time, the market position of agricultural products should be considered when making decisions. The market share of agricultural products will affect the final game equilibrium and then affect the final benefit of the supply chain and individual members.Practical implicationsThese results provide managerial insights for enterprises preparing to invest in agricultural products preservation technology.Originality/valueAt present, the main problem is that member enterprises of agricultural supply chains operate based on their own benefits and are resistant to investing alone to improve the freshness of agricultural products. Instead, they would prefer that other members invest so that they may reap the benefits at no cost. Therefore, the enterprises in each node of the agricultural product supply chain are not motivated enough to invest, and competition and game states are observed among them, and such behavior is definitely not conducive to improving the freshness of agricultural products. However, the current research on agricultural products is more about price, quality and greenness, etc., and there are few studies on agricultural investment. Through the establishment of the model, this paper is expected to provide theoretical suggestions for the supply chain enterprises that plan to invest in agricultural products preservation technology.

Online leakage current classification using convolutional neural network long short-term memory for high voltage insulators on web-based service

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.

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.

In recent years, The vulnerability of agricultural products chain is been exposed because of the endlessly insecure events appeared in every areas and every degrees from the natural disasters on the each node operation of agricultural products supply chain in recently years. As an very important place of HUNAN Province because of its abundant agricultural products, the Eastern Area's security in agricultural products supply chain was related to the safety and stability of economic development in the entire region. In order to make the more objective, scientific, practical of risk management in the empirical analysis, This item is based on the AHP-FCS method to deal with the qualitative to quantitative analysis about risk management of agricultural product supply chain, to identify and evaluate the probability and severity of all the risk possibility.