Chain Enterprises Research Articles

Research on the Risk Contagion Path and Prevention of Supply Chain Finance Based on DEMATEL-ISM Model

The financing risk of enterprises in the supply chain is easily transmitted in the supply chain system, leading to the overall supply chain in financial difficulties. Therefore, it is necessary to analyze the links and transmission paths of risk generation and control them in time. In this paper, 15 factors are extracted from three perspectives: supply chain environment, financing enterprise and core enterprise, and a risk assessment system for supply chain finance is established. Based on this, the coupling method of Decision-making Trial and Evaluation Laboratory-Interpretative Structural Modelling (DEMATEL-ISM) is used to investigate the influence relationship among the factors and the multi-level recursive structural analysis of supply chain risk transmission paths. The results show that the DEMATEL-ISM model can visualize the interactions among three levels of supply chain financial risks: supply chain environment, financing firms, and core firms, and identify five key influencing factors such as innovation capability of core firms in the process of financial risk generation and transmission. This paper investigates the factors affecting the generation of financial risks in the supply chain and the risk transmission paths, and provides guidance for effective control and prevention of supply chain financial risks.

Sustainability in Logistics Service Quality: Evidence from Agri-Food Supply Chain in Ukraine

The purpose of this paper is to explore which attributes of logistics service quality (LSQ) are associated with the superior LSQ in rural territories of the developing economy of Ukraine. The data were collected from 52 Ukrainian agrarian companies. Ukraine was chosen because of the high potential of its agricultural sector, which has been one of the world’s largest exporters of agricultural goods for years. This paper investigates LSQ from the perspective of agri-businesses and addresses sustainability. The primary data were obtained in a survey of clustered samples of agri-businesses in rural Ukraine. An exploratory factor analysis (EFA) was conducted with the Stata 16 software to test one hypothesis. This study builds on the expectancy–disconfirmation paradigm in service management research and the related service quality in order to compare the perceived and expected quality of social and environmental sustainability-related aspects of LSQ to test two hypotheses. The findings revealed that service quality in agricultural logistics is a five-dimensional construct. Its five dimensions are reliability, digital transformation, corporate image, environmental sustainability, and quality of customer focus. Furthermore, the study delivers evidence that the perceived and expected quality of the social sustainability-related aspects of LSQ are substantially different. As the study’s data collection process was interrupted by the Russian–Ukrainian war, the proposed model was only tested with 52 enterprises in an agri-food supply chain in rural Ukraine. Such a small sample is one of the study’s limitations. The research has great managerial implications as managers can use the explored attributes as a basis for customer satisfaction analyses or benchmarking in agricultural logistics. This is the first work exploring LSQ in rural Ukraine. The major contributions of this paper are the explored dimensions of LSQ with EFA. The study presents the first and most current data about LSQ from four united territorial communities in the rural center of Ukraine.

A Green Supply Chain Member Selection Method Considering Green Innovation Capability in a Hesitant Fuzzy Environment

The purpose of this paper is to propose an improved hesitation fuzzy multi-attribute decision-making method to realize green supply chain member selection under green innovation vision. The method uses hesitation fuzzy sets to express decision information of decision makers, takes green innovation capability as the evaluation perspective, and selects green innovation input, synergy of subjects in green supply chain, green innovation output capability, institutional innovation capability of enterprises in green supply chain, and green innovation sustainability as the indexes to evaluate the green innovation capability of enterprises. The multi-attribute decision method proposed in this paper takes into account the shortcomings of the original hesitant fuzzy multi-attribute decision method considering attribute weight optimization in the determination of attribute weights and scheme ranking, then proposes a three-point estimation method for scheme ranking and optimizes the attribute weights by quantifying the balance coefficients of the original decision method. Finally, an example is used to verify the rationality and effectiveness of the proposed method, and a comparison with the original method is made to highlight the advantages of this paper’s method. This paper provides a certain theoretical basis for the selection of members in green supply chains, which helps the selection of members in green supply chains and provides some insight for similar hesitant fuzzy multi-attribute decision-making problems in other fields. In future research, the method proposed in this paper can be considered to combine with probabilistic hesitant fuzzy sets and some other fuzzy sets for method extensions to solve multi-attribute decision-making problems.

Evolutionary Game and Simulation of Collaborative Green Innovation in Supply Chain under Digital Enablement

The deep integration of digital technologies has given rise to the development of new industries and models in various sectors, as well as new opportunities and challenges. Whether digital transformation can drive collaborative green innovation in the supply chain has also become an important topic of great interest, which has not yet been resolved. In this paper, we study the impact of digital enablement on collaborative green innovation in supply chain enterprises in order to assist in reasonable strategic decision making. An evolutionary game model is constructed for both upstream and downstream supply chain companies under digital enablement, following which the model is solved and systematically simulated. Our main findings are as follows: The influencing factors of collaborative green innovation in the supply chain can be divided into driving factors, blocking factors, and regulating factors. After digital enablement, the effect of the drivers of collaborative green innovation is more obvious, the side-effects of the deterrents are weakened, and the threshold of the positive effect of the moderators is expanded. Overall, digital enablement helps to promote collaborative green innovation in the supply chain, and companies should apply digital technology to enable collaborative green innovation.

Research on the Impact of Big Data Analysis Capability on Enterprise Supply Chain Resilience

Based on the current economic environment and from the perspective of dynamic capability, this paper divides big data analysis capability into big data perception capability, big data capture capability and big data transformation capability, and divides supply chain ambidexterity into supply chain agility and supply chain adaptability. A questionnaire survey was used to quantify the impact of big data analysis capability (BDAC) on supply chain elasticity (SC-RE). A total of 300 questionnaires were distributed to managers of supply chain nodes of enterprises, and 217 valid questionnaires were obtained. The regression results of questionnaire data showed that BDAC was positively correlated with SC-RE. Supply chain duality (SC-AM) is positively correlated with SC-RE. SC-AM plays a partial mediating role in the positive effect of BDAC on SC-RE. Based on the regression results of this paper and the research results of existing scholars, the corresponding conclusions are drawn, and some suggestions are put forward for enterprise managers. BDAC is an effective way to improve the performance level and competitive strength of supply chain enterprises. Enterprises should attach importance to the useful information contained in big data, take certain measures to enhance BDAC, improve the information processing capacity and speed of enterprises, reduce the probability of risk occurrence, so as to improve the supply chain resilience of enterprises and improve the level of supply chain risk management.

Analysis of Sub-Optimization Impact on Partner Selection in VMI

Different combinations of elements will lead to different system functions, so a supply chain composed of enterprises with different characteristics will lead to differences in the system performance. In this study, a vendor-managed inventory (VMI) model is built; the model takes into consideration the factors of demand amplification, order and inventory cost change. Then, the change in the revenue of the supply chain and its members—due to VMI—are represented, and the influence of the different production parameters on this change is analyzed. On the basis of proving the distinctive feature of the Kaldor–Hicks improvement possessed by VMI, the profit fluctuations of enterprises in a supply chain that is composed of members with different characteristics using VMI are calculated by a numerical experiment. The conclusions of this paper indicate why enterprises prefer to choose VMI partners, and the results confirm the sub-optimal characteristic of this tendency. In addition, the results also reveal the inherent contradiction of VMI between supply chain efficiency improvement and coordination among the supply chain’s members. If an enterprise chooses VMI partners solely to maximize its own interests, the possibility of Pareto improvement in the supply chain will be maximized. However, at this time, a more effective supply chain system cannot be organized.

Profit allocation on a four-echelon supply chain in perspective of cooperative games on augmenting systems

Profit allocation is an important research topic in supply chain enterprises, where the rationality of allocation determines the stability of their cooperative relationships. This paper focuses on the profit allocation of the supply chain dominated by upstream enterprises. To achieve this goal, a general four-echelon supply chain is constructed. By analyzing the drawbacks of the existing profit allocation methods, we propose three new Shapley values to deal with the different risk attitudes of players. Through theoretical discussions, we can see that the proposed new Shapley values endow upstream participants with profit priority. It shows that the new profit distribution mechanisms suit supply chains dominated by upstream enterprises. We also provide an application example to check the concrete distribution results of the proposed new Shapley values and to compare the experimental results of the proposed new Shapley values with the existing Shapley values to deal with Profit allocation on a four-echelon supply chain. As a result, the proposed new Shapley values outperform the previous Shapley values to deal with the profit allocation on a four-echelon supply chain from the perspective of cooperative games on augmenting systems.

Dynamic Optimal Decision Making of Innovative Products’ Remanufacturing Supply Chain

In order to realize the recyclability of innovative product resources, we explored the optimal dynamic path of each decision variable in the remanufacturing supply chain and analyzed the impact of each decision variable on supply chain performance. Based on the Bass innovation diffusion model, we established a remanufacturing supply chain model in which a single manufacturer leads and a single retailer follows, and the retailer is responsible for recycling. The optimal wholesale price, retail price, and recovery effort path were obtained through optimal control theory. We also discussed the influence of different innovation coefficients and imitation coefficients on the overall long-term profit of each member in the supply chain, and at the same time, found the optimal market share of the product. The research results show that the larger the market innovation coefficient and the imitation coefficient are, the larger the overall long-term profit of the manufacturer and the greater the market share of the product, while the overall long-term profit of the retailer and the entire supply chain will increase first and then decrease; when the innovation coefficient and imitation coefficient are above a certain level, retailers will not enter the market. In a market with a small innovation coefficient and a large imitation coefficient, the overall long-term profits of retailers and supply chains will be higher. This study provides a theoretical basis for the decision making of the remanufacturing supply chain of innovative products in a dynamic environment, and also provides guidance for the practice of nodal enterprises in the supply chain.

Perceptions, attitudes, and motivational factors for consumers and nonconsumers of traditional and craft beers

AbstractBeer is the most consumed alcoholic beverage in the world, and craft‐style beers have presented interesting marketing prospects in the segment. This study intends to establish a consumer profile and their relationship with craft beer compared with traditional versions, as well as understand nonconsumers in order to design more assertive market strategies. The data were obtained using an online questionnaire with 195 participants. Women were about 56.90% less likely to consume craft beer. Craft beer consumers show a preference for bitter, exotic beers, with a strong and full‐bodied flavor, and seek high quality and authenticity. On the other hand, traditional beer consumers seek well‐known and easy‐drinking beers, considering product availability and price. The high price and the stronger flavor are the main reasons for not consuming craft beer. Nonconsumers of beer report the taste as a barrier to consumption. The conceptual and affective associations to the beers are positive, except for the group of nonconsumers.Practical ApplicationsThe brewing segment, shows constant evolution, seeking innovation to better meet the variability existing among beer consumers. One of the outstanding niches is the craft segment, with a complex relationship between consumers and beer. The results of this study provide a view of beer consumption habits and consumer craft and traditional, and answers about nonconsumers. The results show how gender interferes with consumer attitudes and offers insights into opportunities to expand the segment. The consumer seeks positive experiences, whether sensory or not, however, the consumption may not be repeated if these experiences are negative, as in the case of nonconsumers. Given the results, industrial enterprises in the beer production chain can create more personalized strategies to reach target audiences that are not being contemplated. Other segments favored are tourist enterprises, especially those that envision gastronomic tourism, as beer is associated with the consumption of other products and social interaction.

Predicting Chain’s Manufacturing SME Credit Risk in Supply Chain Finance Based on Machine Learning Methods

Supply chain finance is an effective way to solve the financial problems of small and medium-sized manufacturing enterprises, and the assessment of credit risk is one of the key issues in supply chain financing. However, traditional credit risk assessment models cannot truly reflect the credit status of financing companies. In recent years, scholars working in this field have proposed using machine learning methods to predict the credit risk of supply chain enterprises, achieving good results. Nonetheless, there is no consensus on which approach is the most suitable for manufacturing companies. This study took small and medium-sized manufacturing enterprises as the research object, selected risk evaluation indicators according to the characteristics of the small and medium-sized manufacturing enterprises, and built a credit risk evaluation system. On this basis, we selected SMEs on China’s stock market from 2015 to 2020 as the sample data and evaluated corporate credit risk based on four commonly used machine learning algorithms. Then, combined with the evaluation results, a partial dependence plot method was used to visually analyze the important indicators. The results showed that a credit risk evaluation system for supply chain finance for manufacturing SMEs could be composed of the profile of the financing companies, the asset status of the financing companies, the profile of the core companies, and the operation of supply chains. The use of a random forest algorithm made it possible to more accurately assess the credit risk of manufacturing supply chain finance. Since the impacts of different indicators on the evaluation results were quite different, supply chain enterprises and financial service institutions should formulate corresponding strategies according to specific situations.

Pricing and coordination of remanufacturing supply chain considering remanufacturing capacity and preferences under government mechanisms

The management of recycling and remanufacturing supply chains, which can help enterprises achieve low pollution, low energy consumption and sustainable development, has become a new strategy of modern enterprises. The factors of supply chain and government mechanisms will have an impact on enterprise decisions for recycling, remanufacturing and social welfare. In order to promote the sustainable operation of the supply chain, considering the coordination role of government mechanisms and supply chain, a recycling and remanufacturing supply chain model composed of a manufacturer, retailer and recycler is constructed. This paper discusses the pricing decision of new/remanufactured products, supply chain performance level, such as remanufacturing effort, publicity service efforts and profit, and social welfare in five models of three situations: centralized situation, including non-government mechanisms and non-supply chain coordination; manufacturer-led situation, including non-government mechanisms and non-supply chain coordination, government mechanisms and non-supply chain coordination, government mechanisms and supply chain coordination; government-led situation, including government mechanisms and non-supply chain coordination. It is found that under manufacturer-led situations, the government subsidy and bonus-penalty mechanisms can encourage manufacturer and retailer to actively participate in the recycling and remanufacturing activities. The supply chain coordination contract can further enhance the role of the consumer market and promote the implementation of government mechanisms. Manufacturer adopts a cost-sharing contract to encourage recyclers to carry out recycling activities. Under certain conditions, the contract can effectively improve the benefits and social welfare. The research conclusions have important theoretical and practical application value for the coordination and cooperation among enterprises in the supply chain and the formulation of government mechanisms.

Game behavior to carbon reduction of enterprises in the industrial symbiosis chain under different reciprocal scenario

Game behavior to carbon reduction of enterprises in the industrial symbiosis chain under different reciprocal scenario

Course Exploration and Practice of Ideological and Political Education in Human Resource Management of Chain Enterprises

Course Exploration and Practice of Ideological and Political Education in Human Resource Management of Chain Enterprises

Research on Supply Chain Financial Risk Prevention Based on Machine Learning.

Artificial intelligence (AI) proves decisive in today's rapidly developing society and is a motive force for the evolution of financial technology. As a subdivision of artificial intelligence research, machine learning (ML) algorithm is extensively used in all aspects of the daily operation and development of the supply chain. Using data mining, deductive reasoning, and other characteristics of machine learning algorithms can effectively help decision-makers of enterprises to make more scientific and reasonable decisions by using the existing financial index data. At present, globalization uncertainties such as COVID-19 are intensifying, and supply chain enterprises are facing bankruptcy risk. In the operation process, practical tools are needed to identify and opportunely respond to the threat in the supply chain operation promptly, predict the probability of business failure of enterprises, and take scientific and feasible measures to prevent a financial crisis in good season. Artificial intelligence decision-making technology can help traditional supply chains to transform into intelligent supply chains, realize smart management, and promote supply chain transformation and upgrading. By applying machine learning algorithms, the supply chain can not only identify potential risks in time and adopt scientific and feasible measures to deal with the crisis but also strengthen the connection and cooperation between different enterprises with the advantage of advanced technology to provide overall operation efficiency. On account of this, the paper puts forward an artificial intelligence-based corporate financial-risk-prevention (FRP) model, which includes four stages: data preprocessing, feature selection, feature classification, and parameter adjustment. Firstly, relevant financial index data are collected, and the quality of the selected data is raised through preprocessing; secondly, the chaotic grasshopper optimization algorithm (CGOA) is used to simulate the behavior of grasshoppers in nature to build a mathematical model, and the selected data sets are selected and optimized for features. Then, the support vector machine (SVM) performs classification processing on the quantitative data with reduced features. Empirical risk is calculated using the hinge loss function, and a regular operation is added to optimize the risk structure. Finally, slime mould algorithm (SMA) can optimize the process to improve the efficiency of SVM, making the algorithm more accurate and effective. In this study, Python is used to simulate the function of the corporate business finance risk prevention model. The experimental results show that the CGOA-SVM-SMA algorithm proposed in this paper achieves good results. After calculation, it is found that the prediction and decision-making capabilities are good and better than other comparative models, which can effectively help supply chain enterprises to prevent financial risks.

Assessment of Data Security Implementation in the Supply Chain Enterprises in Latvia

Abstract The importance of data security in the supply chain has increased in the last few years. The study identifies recent trends and shortcomings in data security, assessing enterprises operating in Latvia’s transport and storage industry. The research aims to study and identify the current trends in data security in the Transport and Storage industry to develop recommendations for improving data security in the supply chain. The research focuses on studying data security in the supply chain in Latvia. The theoretical literature review was used to learn the main aspects of the supply chain concept and the data security measures applied. Statistical and content analysis shows the industry’s primary data security trends and issues. The results of the research concluded that in Latvia, enterprises providing supply chain operations are focusing on something other than mandatory education about the data security of their employees; thus, they need to apply sophisticated measures to protect data through all supply chain processes.

Determinants of Choice of Market Channel of Broiler Value Chain Main Actors in Southwest, Nigeria.

This study on Determinants of choice of market channel of broiler value chain main actors in Southwest, Nigeria was carried out in Lagos and Ogun States, Nigeria. Multistage sampling procedure was used to select two hundred and thirty respondents made up of broiler producers, broiler processors, live broiler marketers, and dressed broiler marketers. Primary data were used for the survey. Data were analysed with the use of descriptive statistics and multinomial regression analysis. Male farmers in their active age dominated the broiler enterprise across the value chain in the Southwest. Majority (53.3%) of the actors had tertiary education; about 70.9% of the respondents had and average experience of 6years in broiler value chain enterprise with an average household size of 3 persons. However, majority (64.8%) of the respondents did not belong to any association. Results revealed that level of education and transportation cost were significant as determinants of preference of local market over farm gate, however, only transportation cost had odd ratio greater than 1. The Age, years of marketing experience, price of broiler chickens and membership of association of the respondents were significant as determinants of preference of urban market over farm gate, however, the age of the respondents had odd ratio less than 1. The study recommends that, entrepreneurial trainings should be organized for young adults by various government agencies and NGOs and, actors be encouraged to form themselves into association to promote sales outside the farm gate.

Meta-Analysis of the Effect of the COVID-19 Epidemic on China’s Food Supply Chain

With the rapid improvement of China’s food industrialization and socioeconomic development level, many specialized food supply chain enterprises have been born in China in recent years, contributing to the development of the food industry and the enrichment of people’s material life. A meta-analysis was conducted to investigate the global impact of COVID-19 on China’s food supply chain. The objective was to explore whether changes in the food supply chain would affect consumer health, food safety, food prices, and food quality. According to statistics, the COVID-19 outbreak has caused an increase in food prices. This study shows that during the period when the outbreak first occurred imports from other countries were restricted. The COVID-19 epidemic has affected vast numbers of farms directly and indirectly and caused considerable losses in China’s market prices. The epidemic has affected the suspension of many industries and businesses, and residents are isolated from their homes. This paper will analyze the impact of COVID-19 on China’s food supply chain and propose corresponding solutions.

Retracted: Security Enhancement Algorithm of SM‐254 Cloud System and Automated Personnel Identification of the Management in the Supply Chain Enterprise

Retracted: Security Enhancement Algorithm of SM‐254 Cloud System and Automated Personnel Identification of the Management in the Supply Chain Enterprise

Applying information ecological theory to analyse the green supply chain management system in universities

AbstractIn order to create higher benefits for enterprises in the university supply chain and make them meet the requirements of sustainable development, this study uses information ecology theory to study the cognitive management and transformation path of the green supply chain. Firstly, the related concepts of university supply chain management and green supply chain management are expounded, and the differences are mainly discussed. Then, the evaluation of supply chain greenness is studied. The fuzzy hierarchical comprehensive evaluation method combining quantitative and qualitative is used to establish the evaluation model. Finally, the proposed evaluation model is tested. The test results show that Suzhou University's greenness fuzzy evaluation score is 58.2 points, which is a medium level. The resource factor scored 61 points, the energy factor scored 52.9 points, the environmental factors scored 59.8 points, the economic factor scored 62.7 points, and the social factor scored 55.5 points. The company has obvious advantages in terms of resources and economy, but the level is not very high. The higher the cost synergy between enterprises and customers, the greater the environmental cost synergy. Therefore, manufacturing enterprises should strengthen communication and cooperation with customers. The higher the cost synergy control of manufacturing and waste recycling enterprises, the greater the synergy effect of environmental cost control. Therefore, increasing cooperation with waste recycling enterprises is conducive to developing environmental cost control and coordinated benefits. The proposed scheme provides some ideas for applying information ecology theory in the university supply chain.

Marketing Strategy Analysis and SWOT Analysis of Haidilao Under the COVID-19 Epidemic

Since 2020, the COVID-19 pandemic has spread around the world and caused a huge impact on the economy. In the catering industry, the emerging online restaurants, which mainly focus on online sales, are growing rapidly thanks to China's epidemic management policy. In contrast, traditional restaurants, where offline dining is the main form of dining, have been hit hard by the coronavirus pandemic as people cannot go out. Based on the theory of consumer behavior, this paper analyzes the performance, financial status, advantages, and disadvantages of Haidilao, a traditional hotpot chain enterprise, during the epidemic period through case studies and literature research methods. This study found that the impact of COVID-19 on consumers and aggressive marketing strategies were the main reasons for the loss of Haidilao. Through this study, this paper proposes solutions to the financial crisis and product deficiencies of Haidilao and hopes to provide a reference for the traditional catering industry to develop appropriate marketing strategies during the COVID-19 pandemic.