Fuzzy MCDM for Improving the Performance of Agricultural Supply Chain

Fertilizer industry in Vietnam and globally have entered the saturation phase.With the growth rate slowing down,this poses challenges for the development impetus of the fertilizer industry in the next period.In fact,over the past few decades,Vietnam’s crop industry has abused excessive investment in chemical fertilizers,with organic fertilizers are rarely used or not at all,limiting crop productivity,increasing pests and diseases.To develop sustainable agriculture,Vietnam’s crop industry must limit the use of chemical fertilizers,increase the use of environmentally friendly organic and natural mineral fertilizers to produce clean agricultural products which is safe.Therefore,it is necessary to consider and choose the right supplier to ensure the goal of sustainable development.Spherical Fuzzy Analytic Hierarchy Process(SF-AHP),and the combinative distance-based assessment(CODAS)are new Multicriteria Decision Making(MCDM)method which can be used to solve supplier selection problem.This paper uses an effective solution based on a combined the concept of triple bottom line(TBL),SF-AHP and CODAS approach to help agriculture companies that need to select the best fertilizer supplier.This research can support supply chain managers to achieve supply chain systems that reduce not only sourcing costs,but also develop sustainable agriculture.

Optimization Agricultural Supply Chain:A Case Study of Fertilizer Supplier Selection

The 21st century is associated with the IndustrialRevolution 4.0 and the organic agriculture trend,making the utilization of high-quality fertilizers,abundant nutritional content,economical,and no affect to environment pollution.According to the new concept,clean agricultural production and organic agricultural products are not allowed to excessively use synthetic chemicals such as chemical fertilizers,and plant protection drugs,but priority is to use manure,organic fertilizers,and natural mineral fertilizers.Fertilizer must meet the balanced nutritional requirements of crops,maintain,and improve the fertility of the ground,protect the surrounding ecosystem,and leave harmful effects in agricultural products,products with high quality,safe for users and high economic efficiency for producers.To achieve the above goal,the selection of a fertilizer supplier is an important decision,supporting the supply chain’s sustainable development,fertilizer supplier selection is a multicriteria decision making model,the decision maker must assess all qualitative and quantitative factors.In this paper,the author proposed an integer decision making model including Fuzzy Analytic Hierarchy Process(FAHP)and Complex Proportional Assessment of Alternatives(COPRAS)for fertilizer supplier selection.The weightings of the criteria are calculated by using FAHP,COPRAS is then applied for ranking some potential fertilizer suppliers.The efficiency of the proposed models is proved by a case study conducted in a farm located in the south of Vietnam.This research is the first fertilizer supplier evaluation and se-lection model in Vietnam by interviewing experts and reviewing the literature.Re-search result is to provide a case study on evaluating supplier in agricultural supply chain utilizing the model proposed by the combination of FAHP and COPRAS models.

Agricultural Supply Chain Traceability System Based on Multi-Agent System

In order to overcome defects in existing ASCTS(Agricultural Supply Chain Traceability System,a new traceability system based on Multi-Agent System(MAS) is put forward.By qualitative method,I analyze problems of application of Agent technology in tracing quality of agricultural products.Physical model is built for this system and structure of traceability system is determined.Finally,algorithm is presented for major entities.From analysis of algorithm,it is proved that this system has some reference value in improving breadth and depth of product traceability.

Research on the High-Quality Development of Agricultural Supply Chain Financial Ecosystem Empowered by Science and Technology

A systematic perspective on agricultural supply chain finance can offer fresh insights into its development.The high-quality development of the agricultural supply chain finance ecosystem is crucial for the comprehensive revitalization of rural areas and the realization of agricultural power.Based on the current state of development of this ecosystem,this paper identifies several bottlenecks,such as insufficient policy and technical support in the macro-environment system,weak incentives for independent circulation within the industrial environment system,and inadequate motivation for stakeholders to participate in the micro-environment system.To address these issues,this paper proposes that the visualization,digitalization,and authenticity characteristics of the“blockchain+Internet of Things”technology architecture can effectively resolve these bottlenecks.Additionally,targeted strategies are suggested to promote the high-quality development of the agricultural supply chain finance ecosystem.

Application of Deep Learning to Production Forecasting in Intelligent Agricultural Product Supply Chain

Production prediction is an important factor influencing the realization of an intelligent agricultural supply chain.In an Internet of Things(IoT)environment,accurate yield prediction is one of the prerequisites for achieving an efficient response in an intelligent agricultural supply chain.As an example,this study applied a conventional prediction method and deep learning prediction model to predict the yield of a characteristic regional fruit(the Shatian pomelo)in a comparative study.The root means square error(RMSE)values of regression analysis,exponential smoothing,grey prediction,grey neural network,support vector regression(SVR),and long short-term memory(LSTM)neural network methods were 53.715,6.707,18.440,1.580,and 1.436,respectively.Among these,the mean square error(MSE)values of the grey neural network,SVR,and LSTM neural network methods were 2.4979,31.652,and 2.0618,respectively;and theirRvalues were 0.99905,0.94,and 0.94501,respectively.The results demonstrated that the RMSE of the deep learning model is generally lower than that of a traditional prediction model,and the prediction results are more accurate.The prediction performance of the grey neural network was shown to be superior to that of SVR,and LSTM neural network,based on the comparison of parameters.

A blockchain maturity model in agricultural supply chain

Blockchain technology is a disruptive technology that changes business and supply chain models.Using distributed software architecture and advanced computing,blockchain can change the way information is exchanged between actors in the chain.Blockchain technol-ogy provides a platform for solving the problem of tracking product information in supply chain management.Accordingly,the present study aims to provide a model for evaluating the maturity of blockchain technology in the agricultural supply chain.The present research is applied that has been done in three stages.In the first phase,the dimensions of the blockchain are ranked by agricultural experts using the SWARA method.The research experts are 13 faculty members of the department of agriculture active in the field of technology application.In the second phase,a model is designed to evaluate blockchain maturity using each dimension of blockchain technology and maturity dimensions.In the third phase,the proposed model is tested using data collected by a questionnaire in the supply chain of a company active in the agriculture sector.The research findings show that smart contracts,Internet of Things(IoT),and transaction records are of the highest impor-tance among the blockchain dimensions.Also,the supply chain under study is in a good condition in digital documents.Theoretically,the originality aspect of the research is that it determines the importance of blockchain dimensions in the field of agriculture and from an applied point of view,it introduces the maturity model of blockchain in supply chain management.

The Operation Mechanism of Agricultural Products Supply Chain and Profit Allocation Model in the Context of Asymmetric Information

The research performed analysis on causes of asymmetric information of agricultural product supply chain and made conclusion on operation mechanism and characteristics of supply chain based on asymmetric information. Finally, the research detailed profit sharing of agricultural product supply chain in the context of asymmetric information and proposed suggestions, providing references of pricing and profit sharing of supply chains of agricultural products.

Optimization Analysis of Agricultural Product Supply Chain From the Perspective of Internet

With the development of our agricultural modernization process accelerated, the agricultural products supply chain is also facing the demand of further optimization and improvement. And the development of the Intemet makes it become an important means to optimize the agricultural products supply chain. Firstly, it is based on the concept explanation of ＂Internet ＋＂. Secondly, according to the present situation which includes traditional models dominated, the main bodies on the chain are diversified, farmers＇ position is lower and the problems which include the chain is too long, logistics nodes are scattered, infi＇astructure lags behind, circulation of information is poor, and risk monitoring is difficult of the supply chain of agricultural products are facing in China, clarifying the role of the Internet in the agricultural products supply chain which includes making the agricultural information network more perfect, adjusting and optimizing the supply chain of agricultural products. Finally, authors put forward some measures to optimize the supply chain of agricultural products and make conclusions.

Fresh-Keeping Decision and Coordination of Fresh Agricultural Product Supply Chain Considering Carbon Cap-and-Trade under Different Dominance

In the context of low carbon,this paper discussed the impact of the carbon cap-and-trade policy on the fresh-keeping decision-making of two-echelon fresh agricultural product supply chains under different dominance,and designed cost-sharing contracts to coordinate the supply chain of fresh agricultural products dominated by suppliers and retailers respectively.The results showed that:dominance has no effect on the fresh-keeping decision and total revenue of fresh agricultural product supply chain,but it affects the internal income distribution,and dominance does not always bring more benefits;the implementation of carbon cap-and-trade reduces the fresh-keeping decision-making of fresh agricultural products supply chain and reduces the free-rider income of followers;the role of higher carbon trading price is twofold,which not only brings about the speculation of leading enterprises,but also promotes the application of low-carbon technologies;consumers’high preference for freshness,low-cost and high-efficiency low-carbon technology are all conducive to improving the fresh-keeping efforts and benefits of the supply chain;cost-sharing contracts can coordinate the supply chain of fresh agricultural products.

The Construction and Competitiveness of Operation Model of Agricultural Industrial Cluster

Through reviewing the viewpoints of former scholars, the connotation and features of supply chain of agricultural industrial cluster are introduced. The agricultural industrial cluster model constituted by core network and supporting network is constructed. Three operation models of this kind of supply chain is described: the model takes wholesale market of agricultural products as the core; the model take pillar industries of agricultural industrialization as core; model takes the chains of retail enterprises as core. The competitiveness of agricultural industrial cluster is researched. The research assumes that the competiveness of supply chain of agricultural industrial cluster is mainly represented to make the agricultural industrial cluster to acquire more capabilities in terms of innovation and knowledge sharing capability, resource allocation capability, agile market adaptability and distinct value creation capability.

Quality control of the agricultural products supply chain based on"Internet+"

This paper describes a quality-control supply-chain model using the"Internet+"paradigm.The model is based on principal-agent theory,which considers the reputational loss due to inferior products and external responsibility identification.After model analysis and simulation verification,the results show that the optimal quality-control level and market price of agricultural products can be achieved in the agricultural supply chain based on"Internet+"if and only if the information platform’s claim to the agricultural producer is less than the agricultural producer’s claim to the delivery service provider.Also,a rise in consumers’claims or the agricultural producer’s reputational loss due to inferior products will motivate the quality control of an agricultural procedure.Meanwhile,the market price of agricultural products will also increase with enhanced quality control procedures.The quality-control level of a delivery service provider is inversely proportional to the information platform or its own reputational loss.Thus,the key to promoting quality control along the supply chain is to strengthen the responsibility confirmation of an inferior product between the agricultural producer and the delivery service provider.

Enabling affordances of blockchain in agri-food supply chains:A value-driver framework using Q-methodology

The application of blockchain beyond cryptocurrencies has received increasing attention from industry and scholars alike.Given predicted looming food crises,some of the most impactful deployments of blockchains are likely to concern food supply chains.This study outlined how blockchain adoption can result in positive affordances in the food supply chain.Using Q-methodology,this study explored the current status of the agri-food supply chain and how blockchain technology could be useful in addressing existing challenges.This theorization leads to the proposition of the 3TIC value-driver framework for determining the enabling affordances of blockchain that would increase shared value for stakeholders.First,we propose a framework based on the most promising features of blockchain technology to overcome current challenges in the agri-food industry.Our value-driver framework is driven by the Q-study findings of respondents closely associated with the agri-food supply chain.This framework can provide supply chain stakeholders with a clear perception of blockchain affordances and serve as a guideline for utilizing appropriate features of technology that match organizations’capabilities,core competencies,goals,and limitations.Therefore,it could assist top-level decision-makers in systematically evaluating parts of the organization to focus on and improve the infrastructure for successful blockchain implementation along the agri-food supply chain.We conclude by noting certain significant challenges that must be carefully addressed to successfully adopt blockchain technology.