Link In Supply Chain Research Articles

Linking Supply Chain Disruption Orientation to Supply Chain Resilience and Market Performance with the Stimulus–Organism–Response Model

Since 2020, supply chain disruptions have emerged as an ever-present challenge. This research provides a glimpse into the organizational structures that develop supply chain resilience and market performance amid continuous supply chain disruptions. Utilizing psychosomatic variables and empirical modeling, a model was constructed through a review of extant literature and tested with PLS-SEM analysis. Uniquely, this research model is framed with the stimulus–organism–response model; thus, placing a firm within the context of a tumultuous environment where stimuli elicit responses from an organization that behaves as an organism. Results demonstrate that organizational culture plays a critical role in developing supply chain resilience amid supply chain dynamism. Market performance was also developed but only through supply chain resilience; supply chain disruption orientation alone did not improve market performance. Mediation effects highlight the importance of supply chain disruption orientation, a strategic orientation that cements an organization’s ability to develop supply chain resilience.

Multi-Chain Collaboration-Based Information Management and Control for the Rice Supply Chain

The issue of food quality and safety is a major concern. Rice is considered one of the three staple foods. Rice quality and safety problems have occurred frequently, which seriously affect human health. The rice supply chain is characterized by complex links, discrete data, and numerous types of hazardous substances. Strengthening the information management and control capabilities of the rice supply chain is an important means to ensure the quality and safety of rice. Based on multi-chain collaboration, we have conducted research on information management and control of the rice supply chain. First, a multi-chain collaborative model of “blockchain + sub-chain” is designed. Based on this model, the following four mechanisms are designed: a trusted chain mechanism, a multi-level sub-chain encryption mechanism, a trusted supervision mechanism, and a hierarchical consensus mechanism. These mechanisms jointly serve the multi-chain collaborative management and control of the rice supply chain information. Secondly, smart contracts and operating procedures are designed, and a comparative analysis of them is executed. Finally, the design and implementation of the prototype system is carried out, and an example is verified and analyzed in a grain enterprise. Results show that this model serves the information supervision of the rice supply chain by studying the multi-chain collaboration. The study solves the real-time data interaction problem between each link of the rice supply chain. The credible management of information and control of the rice supply chain is accomplished. This study applies new information technology to the coordination and resource sharing of the food supply chain and provides ideas for the digital transformation of the food industry.

Weak links in finance and supply chains are easily weaponized.

Russian sanctions highlight how network analysis is urgently needed to find and protect vulnerable parts of the global economy. Russian sanctions highlight how network analysis is urgently needed to find and protect vulnerable parts of the global economy.

Research on the Cross-Chain Model of Rice Supply Chain Supervision Based on Parallel Blockchain and Smart Contracts.

Rice is one of the three major staple foods in the world, and the quality and safety of rice are related to the development of human beings. The new crown epidemic, pesticide residues, insect pests, and heavy metal pollution have a certain security impact on the food supply chain. The rice supply chain is characterized by a long life cycle; complex roles in the main links; many types of hazards; and multidimensional, multisource, and heterogeneous information. To strengthen the rice supply chain’s supervision ability under the epidemic situation, a supervision cross-chain model suitable for the complicated data of the rice supply chain based on parallel blockchain theory and smart contract technology was built. Firstly, the data collected in the rice supply chain and different types of data stored in different parallel blockchains were analyzed. Secondly, based on data analysis, a collection/supervision cross-chain mechanism based on “hash lock + smart contract + relay chain”, a concurrency mechanism based on the K-means algorithm and a Bloom filter, and a consensus mechanism suitable for multichain consensus named the Supervision Practical Byzantine Fault Tolerance (SPBFT) were proposed. Furthermore, a cross-chain model of rice supply chain supervision was constructed. Finally, theoretical verification and simulation experiments were used to analyze the operation process, safety, cross-chain efficiency, and scalability of the model. The results showed that the application of parallel blockchains and smart contracts to supervision of rice supply chain information improved the convenience and security of information interaction between various links in the rice supply chain, the storage cost of supply chain data and the high latency of interaction was reduced, and the refined management of the rice supply chain data and personnel was realized. This research applied new information technology to the coordination and resource sharing of the food supply chain, and provides ideas for the digital transformation of the food industry.

Quality of Fresh Camel Meat (Camelus dromedarius) Sold at Retail Houses in Bechar City (Southwest of Algeria): Physicochemical and Hygienic Approaches

Background: Meat is the first source of animal protein, its richness in essential amino acids classifies it among the noble proteins. However, due to its nutritional qualities, meat constitutes a favorable ground for microbial development and can serve as a source of foodborne pathogens for consumers. Hence this study aimed to evaluate the hygienic quality of fresh camel meat marketed in Bechar city (Southwest of Algeria). Methods: At the butcher’s shops in the Bechar El Djadid’s market, the taken samples underwent analyzes of a few physicochemical and microbiological parameters. The suspected pathogenic isolates were confirmed using biochemical tests. Result: The physicochemical parameters results showed that the samples had slightly acidic pH values ranging from 5.25 to 5.86, the temperature from 6 to 7.5°C and the total solid content (TSC) ranging from 21 to 36.6% with a moisture rate ranging from 63.4 to 75.6. However, the obtained microbiological results showed a load of Escherichia coli of 3.3 and 4.83 Log10 CFU/g for the samples S1 and S2, respectively, exceeding the threshold set by national standards. The analyzed samples had a load of S. aureus (CoPS) ranging from 3.78 to 5 Log10 CFU/g, with the presence of Salmonella choleraesuis ssp arizonae for the sample (S1), while both Listeria monocytogenes and Pseudomonas spp species were absent in all the analyzed samples. The lactic acid bacteria (LAB) load ranged from 2.36 to 2.74 Log10 CFU/g. In conclusion, four out of five analyzed samples had an unsatisfactory quality. This is the result of a lack of hygiene in one of the links in the raw material supply chain, from the slaughterhouse to the retailer, whose stakeholders must ensure cleanliness and compliance with good hygiene practices (GHP) to protect consumers against microbial risks.

LINKING SUPPLY CHAIN MANAGEMENT PRACTICES TO CUSTOMER RELATIONSHIP MANAGEMENT OBJECTIVES: A PROPOSED FRAMEWORK

This research proposes a framework linking supply chain management (SCM) practices to customer relationship management (CRM) objectives through better organizational performance. First, critical review was conducted to identify the relationship between SCM practices and organizational performance. Then, a systematic review of published research work on CRM objectives for last two decades was conducted with the purpose of identifying key variables for CRM objectives and their impact on SCM practices through managing organizational performance. The review revealed a set of main variables for CRM objectives (customer satisfaction and customer loyalty). Upon which, a theoretical framework has been developed linking SCM practices to CRM objectives through enhancing organizational performance. This work brings together the concepts of SCM practices and organizational performance. It also provides a comprehensive review on CRM objectives over a time span (2000–2019) in order to develop the framework between SCM practices and CRM objectives through better organizational performance. The proposed framework can help practitioners to understand SCM practices that can lead to better CRM and hence better organizational performance.

Credit Rating Prediction Through Supply Chains: A Machine Learning Approach

As supply chain channels physical, financial, and information flows as well as associated risks, a firm's supply chain information should be helpful in understanding and predicting its credit risks. Credit ratings, as an approximate but important measure of corporate credit risks, have been widely used by investors, creditors, and supply chain partners in their decision‐making. This study studies the role of supply chain information in predicting companies’ credit ratings. Using firm‐level supplier–customer linkages and corporate credit rating data, we develop a machine learning framework with gradient boosted decision trees to examine whether and what supply chain features can significantly improve the prediction accuracy of credit ratings, and what types of supply chain links have higher information content that positively affects the predictability of the supply chain features. We construct a firm's supply chain variables from its supplier and customer portfolios. We show that incorporating supply chain features can improve prediction accuracy over the benchmark credit rating model using only the focal firm's features. Moreover, the informativeness of supply chain links in focal credit risk prediction depends on the focal firm's industry sector, the relationship strength of such links, and the switching costs. Finally, we develop a focal credit rating prediction model with a high accuracy level using supply chain factors solely, which can potentially be applied to predict credit risks of small‐ and medium‐sized enterprises (SMEs) and private firms with no public financial information, as long as their supply chain information is available.

As strong as the weakest link. Transport and supply chain security

ABSTRACT The supply chains form a complicated interlinked system where any disruption, at any possible level, can affect the network itself but also its surrounding, including the society. This feature is confirmed by a well-known and often repeated statement that the chain is only as strong as its weakest link. This manuscript provides a comprehensive research-based rationale for this statement to shed new light on how the phenomenon could be identified and what are theoretical grounds for its management. The scoping review allowed for exploring the existing literature on the weakest links in supply chains to clarify this complex concept and explain its heterogeneous nature. To structure our research, we have adopted two theoretical perspectives, present in existing studies, that is network interdependency and weakest link public good. The study contributes to the existing body of knowledge by summarising literature in the field, identifying gaps, and setting the agenda for future research. It concentrates on two areas derived from literature, that is the ways of identification of weakest links and the determination and provision of the optimal level of security. The analysis reveals that there is no consensus even regarding the weakest link definition. The majority of studies are theoretical and general with little research devoted to the practical implications. While equilibriums for optimal resource allocation are well recognised specific measures oriented at the elimination of the weakest link are lacking. As a result, we identify gaps in the existing body of knowledge regarding threat-weakest link occurrence, countermeasures, and policy options offered.

Blockchain-Based Information Supervision Model for Rice Supply Chains.

Rice is a major food crop around the world, and its various quality and safety problems are closely related to human health. As an important area of food safety research, the rice supply chain has attracted increasing attention. Based on blockchain technology, this study investigated problems of data privacy and circulation efficiency caused by complex rice supply networks, long circulation cycles, and various risk factors in each link. First, we deconstructed the quality and safety of each link of the rice supply chain at the information level and established a key information classification table for each link. On that basis, we built a rice supply chain information supervision model based on blockchain. Various encryption algorithms are used to secure the sensitive data of enterprises in the supply chain to meet regulators' needs for efficient supervision. Moreover, we propose a practical Byzantine fault-tolerant consensus algorithm that scores the credit of enterprise nodes, optimizes the selection strategy of master nodes, and ensures high efficiency and low cost. Then, we built a prototype system based on the open-source framework of hyperledger fabric, analyzed the model's viability, and implemented the system using cases. The results indicated that the proposed system can optimize the information supervision process of rice supply chain regulators and provide a feasible solution for the quality and safety supervision of grain and oil.

Cross-Border E-Commerce Logistics Transportation Alternative Selection: A Multiattribute Decision-Making Approach

Cross-border e-commerce logistics and transportation system is important link in the cross-border e-commerce supply chain. How to choose a fast, safe, reliable, and low-cost logistics transportation mode is an urgent problem to be solved in cross-border e-commerce logistics. In view of this, this paper first analyzes the system characteristics of cross-border e-commerce logistics transportation systems and analyzes the factors affecting the choice of transportation mode from the perspective of reliability. Then, based on the ELECTRE method system, a multiattribute decision-making method for cross-border e-commerce logistics transportation mode selection is proposed. Finally, through a data example, it is verified that the model constructed in this paper and the proposed multiattribute decision-making method can effectively help cross-border e-commerce choose logistics transportation mode according to goods.

Research on the improvement path of international competitiveness of China's agricultural product supply chain from the perspective of machine learning

AbstractIn order to explore the international competitiveness of China's agricultural product supply chain, this paper combines machine learning algorithms to optimize the data processing process of agricultural product supply chain, and proposes a data processing method for agricultural product supply chain based on the intra‐column rules and inter‐column rules. According to the problems of my country's agricultural product supply chain, this paper establishes a new agricultural product supply chain management model based on the various modules of the supply chain link, and constructs a corresponding intelligent analysis model. Moreover, this paper combines machine learning algorithms to study the improvement path of the international competitiveness of China's agricultural product supply chain, and builds an intelligent model to improve the international competitiveness of China's agricultural products. Finally, after constructing the model, this paper obtains the path to improve the international competitiveness of China's agricultural products through the simulation operation model, which also verifies the effectiveness of the intelligent algorithm of this paper from the side.

Effectiveness of food traceability system in the supply chain of local beef and beef sausages in Malawi: A food safety perspective

A study was conducted to determine status of traceability system implementation in the supply chain of local beef and beef sausages in Malawi, and tried to identify key factors affecting the implementation, in an attempt to find solutions to traceability issues, to ensure safety of these food products for consumers. Eighty-two (82) samples of cut beef (40) and beef sausages (42) were identified from retail outlets and followed retrospectively to determine if information trail generated along the supply chain link to identity of corresponding meat carcasses and live animals from feedlots. Fifty-eight (58) personnel for business operators involved in this supply chain and four (4) regulatory enforcement officers were interviewed to review level of knowledge on Food Traceability (FT) and Food Safety (FS) that is vital in food traceability implementation. Results of the study indicated that; it was not possible to trace attributes of local beef and beef sausages from retail outlets to cattle feedlots, personnel involved in this supply chain did not have adequate knowledge on FT and FS and that regulatory enforcement officers had adequate knowledge on FT and FS but contents of legislation could not allow them to effectively address issues of food traceability. It was, therefore, concluded that the supply chain of local beef and beef sausages in Malawi is not traceable which is a FS concern and a threat to public health and need to be swiftly addressed.

Factors affecting Lychee supply chain linkage and business performance

The objective of this study is to investigate the relationship between supply chain linkage and business performance in the lychee supply chain in Vietnam. The study collected 395 matched samples after sample screening. Partial least squares (PLS) algorithm is used to process the data. Research results show a link between supply chain linkage and business performance. Furthermore, research shows that risk supply chain, quality management, and business strategy also impact supply chain linkages and business performance.

Comparative analysis of sustainability factors in supply chain links. Evidence of empirical research

Sustainability factors play a very important role in shaping supply chain strategies. Their implementation and compliance is also important from the customers' perspective. This study attempts to present and analyze the actions taken in the field of implementing sustainable development factors and elements in supply chains, taking into account the perspectives of the various links. The results of the comparative analysis show the differences that occur in the implementation and application of sustainable development elements in various links of the chains. On the basis of selected questions from the survey questionnaire, the authors created a ranking in which they compared the indicated chain links in terms of the use of sustainable development elements, reflected by the indicated indicators. The results clearly show the differences, which means that the same indicators for different links have a different meaning and play a different role. This means that it is necessary to analyze and observe the individual links very carefully so that the understanding of sustainability is clear, and the more elements are implemented, the faster and easier it will be to have a holistic approach to implementing a sustainable supply chain strategy.

АМЕРИКАНО-КИТАЙСКИЕ ПРОТИВОРЕЧИЯ ВОКРУГ ТАЙВАНЬСКОГО ПРОЛИВА (Часть 1. Суть терминологического спора)

For decades, the Taiwan Strait has been one of the main "hot spots" in the Asia-Pacific region. As an object of confrontation between China and Taiwan, the U.S. and China, the area is strategically important to the entire global economy and international shipping. The strait connects the South China Sea with the East China Sea, through which up to 80% of world trade passes, and it is also a crucial link in the global supply chain. Even a short-term blockade of the Taiwan Strait could have serious consequences for the global economy. A new aggravation in the region occurred on July 13, 2022, when Wang Wenbin, spokesman for China's Foreign Ministry, declared that the Taiwan Strait is not "international waters." This article examines in detail the political and legal aspects of China's and the United States' perception of the legal status of the Taiwan Strait, revealing the understanding of "international waters" under international maritime law. It substantiates the main reasons for Beijing's actions regarding the Taiwan Strait, and also forecasts the possible resolution of this legal dispute in light of the fundamental change in China's policy regarding the islands and waters of the South China Sea, which followed the verdict of the Permanent Court of Arbitration in The Hague in 2016.

A Dynamic Source Tracing Method for Food Supply Chain Quality and Safety Based on Big Data

The data of food quality tracing information have a few features, such as wide coverage range, many circulation links, complex data sources, low authenticity, and difficult information sharing. The continuous development of big data technology provides infinite possibilities for the construction of food quality source tracing systems. Currently, there are many studies on the application of food quality source tracing systems; however, most of them are in the field of food quality databases, and few have concerned about its application in the field of big data. Therefore, to fill in this research gap, this paper aimed to study a dynamic source tracing method for food supply chain quality and safety based on big data. At first, this paper summarized the variables of food supply chain quality and safety, constructed a Petri net model and a Bayesian network model for food quality prediction and source tracing, and realized the prediction of food quality features. Then, this paper applied two data analysis and processing methods—the density‐based clustering algorithm and the cosine similarity algorithm—to preliminarily process the collected quality tracing information of each link in the food supply chain and analyzed the influencing factors of food quality. Finally, experimental results proved the effectiveness of the constructed model. Relying on the real‐timeliness and authenticity of big data, this paper guarantees the credibility of the traceable information in the tracking process and improves the accuracy through real‐time stream processing of the updated data, providing unlimited possibilities for the comprehensive tracking of food sources.

Research on the whole chain traceability system of dairy products based on consortium blockchain

Dairy products are one of the indispensable foods in people's life. However, reports about the quality and safety of dairy products often appear. In this paper, a dairy product quality and safety traceability system based on consortium blockchain is proposed by using block chain technology. In addition, the traceability link in the dairy supply chain is defined, and the basic framework and traceability bar code of the traceability system are designed. The system guarantees the integrity and security of the traceability information from the technical level, and provides the dairy traceability service for the government, enterprises and consumers.

MODELLING THE LINK BETWEEN SUPPLY CHAIN ANALYTICS, SUPPLY CHAIN INNOVATION AND COMPETITIVE ADVANTAGE: A STRUCTURAL EQUATION MODELLING APPROACH

Little are known about the nature of the interaction between supply chain analytics, supply chain innovation and competitive advantage. The purpose of this paper is to propose and validate a theoretical model to investigate whether supply chain analytics positively affects supply chain innovation and competitive advantage, and to examine how supply chain innovation may improve competitive advantage. A theoretical model was developed from extant studies and assessed through the development of a questionnaire survey conducted with South African manufacturers and logistics intermediaries involved in global supply chain operations. The data was analysed using confirmatory factor analysis and structural equation modelling (PLS-SEM) to validate the suggested model. It was found that supply chain analytics have a discernible positive influence on supply chain innovation and competitive advantage. Furthermore, supply chain innovation was found to have a significant impact on enhancing competitive advantage. Therefore, this work provides evidence for the importance of supply chain analytics and supply chain innovation in supporting competitive advantage, in doing so, supply chain innovation mediates the link supply chain analytics and competitive advantage. This study contributes to providing an empirical understanding of the strategic retention of supply chain analytics and supply chain innovation in the supply chain management discipline. Furthermore, it confirms and expands existing theories about innovation and competitive advantage. The findings provide firm grounds for managerial decisions on investment in innovation. This research is the first of its kind to empirically validate the relationships between supply chain analytics, supply chain innovation and competitive advantage in South Africa.\nKeywords: competitive advantage; supply chain innovation; supply chain analytics; structural equation modelling.

Modeling Perishability in MIT Beer Game Business Simulator

COVID-19 pandemic showed that customers tend to create an excessive inventory, and these demand shocks caused by disruptions or disruption anticipation destabilize the supply chains. The consequences of such demand shocks are hard to predict and model. We present a modified version of the MIT Beer Game which includes product perishability constraints. The model is implemented in Python 3 and uses a client-server architecture and the internet or a local server for players’ interaction. The increased complexity of the game dynamics affects the players’ behavior. The work is aimed at identifying the specifics of supply chain actors’ decisions under constraints of the limited shelf life of a product. The main hypothesis is as follows: when the number of uncertainty factors in the supply chain operation increases, the ability of the supply chain links (players) to implement an effective algorithm for an order and shipment planning decreases. Additional operational measures can help to allocate risks in a more equal way within the supply chain.

ОЦІНКА ВПЛИВУ НЕВИЗНАЧЕНОСТІ НА ВИНИКНЕННЯ РИЗИКІВ В ЛАНЦЮГАХ ПОСТАЧАННЯ

Russian aggression has destroyed much of Ukraine's infrastructure. The mechanism of functioning of supply chains has become unbalanced. Rapid response to challenges and identification of measures to prevent them is identified as a component of the Ukrainian economy in the struggle for victory. Uncertainty is understood as a situation when the probability of a certain event is not fully known. The import of missing data is considered to be a main approach to deal with the issue. The existence of uncertainty means the impossibility of clearly defining the future outcome and the need to respond to a threat that is likely to be an economic risk. The application of Monte Carlo methods in economics is not always acceptable to measure uncertainty. Classical probability theory has certain limitations for practical application to treat uncertainty. The Bayesian theory is applied as a preferable toolkit to address the issue. In practical terms, the main difficulty is to reduce the initial uncertainty given the results of statistical observations. The main approach to solving problems of uncertainty – imputation – enables to substitute the missing data with values determined by a certain algorithm. The main types of imputation are examined in the article. The goal of the research is to set forth an approach dealing with the impact of uncertainties on the economic risk of a supply chain link. The research was performed on the basis of a manufacturing enterprise. The task was to forecast orders for the supply of special metal shapes to fix the roads destroyed during the war. Due to the need to to make decisions when potential consumers of its products have not yet decided on their orders for the supply of its products, the company faces uncertainty challenges. To solve this problem, the Expectation-Maximization algorithm was applied to treat to predict initially missed data. By obtaining full data due to the EM-algorithm under the uncertainty, an equation was obtained to predict the relationship between the technological parameters of roads and the future demand for the company`s products. The equation obtained enables to determine the forecast output of special profiles required to meet the need in rolled shapes. The statistical evaluation of research results testifies to their reliability.