Enterprise Supply Chain Research Articles

Research on the Risk Identification and Evaluation of Enterprise Supply Chain under Major Public Emergencies

Under the background of globalization, the complex economic and social environment leads to the constant change of the supply chain system and the huge risk of management. Especially in recent years, the frequent occurrence of natural disasters, major public events, production accidents, product quality and safety accidents and other emergencies around the world has broken the smooth state of the supply chain, and even caused the rupture of the supply chain, causing great harm to the normal operation of the supply chain system. The risk of the supply chain stems from the uncertainty of the internal and external relations of the supply chain system and among the members of the supply chain. However, the occurrence of emergencies increasingly leads to the prominence of this uncertainty. The supply chain risk caused by emergencies is increasing, and it is increasingly difficult for the supply chain to recover from the failure caused by emergencies. Therefore, it is urgent to study the supply chain risk management under emergencies.

Improving the greenness of enterprise supply chains by designing government subsidy mechanisms: based on prospect theory and evolutionary games.

Fostering sustainable development through green supply chains is of paramount significance. Government subsidies emerge as a successful strategy for motivating businesses to actively participate in such eco-friendly practices. This study employs prospect theory and an evolutionary game model to analyze the transition toward carbon peaking and neutrality while promoting the expansion of highly sustainable businesses. By exploring the decision-making processes of businesses and governments regarding sustainability, we develop an evolutionary game-based decision model to assess the impact of government subsidies on businesses engaged in green supply chains. Through numerical simulation obtained via MATLAB, we examine various factors influencing the evolution of the game system between green supply chain businesses and the government. Additionally, we investigate how government incentives impact the decision-making behavior of green supply chain businesses. Our findings indicate that governmental fines can effectively encourage the adoption of green supply chains. Furthermore, moderate government subsidies incentivize enterprises to opt for sustainable supply chains, benefiting both the government and businesses. However, providing hefty government subsidies not only fails to encourage the adoption of green supply chains but also incurs costs for the government, without yielding any positive change in the businesses' approach. By incorporating evolutionary game theory and prospect theory, this study contributes to the body of knowledge on government-supported green supply chains, offering incentive programs tailored to the real-world conditions faced by businesses while demonstrating practical application values.

A novel integrated approach based on best–worst and VIKOR methods for green supplier selection under multi-granularity extended probabilistic linguistic environment

With consideration for the extensive resources consumption and environmental degradation being on the rise today, implementing green development strategy to pursue both socioeconomic growth and the coordinated of environment sustainability, has become an increasingly important issue in modern enterprise supply chain operations management. Hence, the appropriate green supplier selection (GSS), viewed as a core issue in green supply chain management (GSCM), requires continuous research in this field to obtain a complete perception on GSS practices. It can be regarded as a multi-attribute group decision-making (MAGDM) problem that involves many conflict and unmeasurable evaluation criteria. In view of the superiority of multi-granularity extended probabilistic linguistic term sets (MGEPLTSs) in modeling such issues on potential ambiguity, complexity and uncertainty in actual GSS practices, we propose a novel integrated MAGDM methodology for GSS problems, by integrating the BWM (best–worst method) with the VIKOR (VIšekriterijumsko KOmpromisno Rangiranje) technique under the MGEPLTSs environment. First, by introducing the multi-granularity and probabilistic linguistic term sets, the MGEPLTSs are proposed to represent and quantify the decision information of GSCM practitioners. Then, the BWM is introduced to the MGEPLTSs environment to compute the weights of decision-making panels and evaluation attributes in GSS problems, by building the fuzzy mathematical programming model, respectively. Finally, we extend a multi-granularity extended probabilistic linguistic VIKOR method to calculate the compromise measure of alternatives considering the group utility maximization and the individual regret minimization, thereby achieving the full ranking of alternatives. A GSS case is conducted to illustrate the feasibility of the proposed approach, and the sensitivity analysis and comparative analysis with other similar approaches are presented to demonstrate its effectiveness and advantages.

Carbon reduction decision-making in supply chain under the pledge financing of carbon emission rights

Supply chain enterprises can solve the cost problem caused by emission reduction through the pledge financing of carbon emission rights. This paper aims to optimize the pricing and ordering strategy and carbon reduction decision of the supply chain based on the pledge financing of carbon emission rights, establishes the expected revenue model of the manufacturer and the retailer, and analyzes the mechanism of the carbon reduction decision of the supply chain on its pricing and ordering strategy, expected revenue and revenue distribution strategy. The results illustrate that the optimal order quantity and the optimal wholesale price maximize the expected revenue of the retailer and the manufacturer, regardless of whether the pledge financing of carbon emission rights is introduced. With the adoption of the pledge financing of carbon emission rights, there is an optimal amount of carbon emission reduction per unit of the product to maximize the optimal order quantity. When both order quantity and wholesale price are optimal, the present value of expected revenue for the retailer and the manufacturer increases with the amount of carbon reduction per unit of product. The upper and lower limits of the retailer's share of sales revenue rise and fall as the amount of carbon reduction per unit of product increases, respectively.

Retracted: Enterprise Supply Chain Risk Assessment Based on the Support Vector Machine Algorithm and Fuzzy Model

Retracted: Enterprise Supply Chain Risk Assessment Based on the Support Vector Machine Algorithm and Fuzzy Model

Enterprise Collaboration Optimization in China Based on Supply Chain Resilience Enhancement

With the promotion of the new round of industrial revolution, the development environment of enterprises has undergone tremendous changes. Collaboration among enterprises has become crucial for enhancing core competitiveness, with the concept of the supply chain playing a key role. However, the complex and vulnerable nature of the supply chain operation environment poses various risks, hampering effective cooperative relationships between enterprises. This article proposed integrating the partial least-squares-artificial neural network (PLS-ANN) method to address this issue and optimize collaborative enterprise practices. The study examined enterprise collaboration optimization. This article uses used artificial neural network (ANN) to classify various complex data, implement an intelligent algorithm model for synchronous processing, and combine partial least squares (PLS) to classify and process the data information generated by collaborative networks to find the best match, minimizing the negative impact of multiple correlations of variables on enterprise collaboration. An empirical analysis was conducted in 2022, focusing on a manufacturing enterprise's supply chain and external cooperation management. The analysis examined two aspects: the supply chain's risk resistance level and the effectiveness of enterprise cooperation. Results showed that after implementing the PLS-ANN model, the average trust index between the enterprise and eight cooperative partners increased to approximately 0.652, compared to the initial average trust index of only 0.528. Detailed data analysis indicated that the PLS-ANN method effectively improved the supply chain's risk resistance capability while optimizing the cooperative relationships among all participating enterprises.

A hybrid forecasting model with logistic regression and neural networks for improving key performance indicators in supply chains

This study investigates the potential of predictive analytics in improving Key Performance Indicators (KPIs) forecasting by leveraging Lean implementation data in supply chain enterprises. A novel methodology is proposed, incorporating two key enhancements: using Lean maturity assessments as a new data source and developing a hybrid forecasting model combining Logistic regression and Neural Network techniques. The proposed methodology is evaluated through a comprehensive empirical study involving 30 teams in a large supply chain company, revealing notable improvements in forecasting accuracy. Compared to a baseline scenario without process improvement data, the new methodology achieves an enhanced accuracy score by 17% and an improved F1 score by 13 %. These findings highlight the benefits of integrating Lean maturity assessments and adopting a hybrid forecasting model, contributing to the advancement of supply chain analytics. By incorporating lean maturity assessments, the forecasting process is enhanced, providing a deeper comprehension of the underlying Lean framework and the impact of its elements on supply chain performance. Additionally, adopting a hybrid model aligns with current best practices in forecasting, allowing for the utilisation of various techniques to optimise KPI prediction accuracy while leveraging their respective strengths.

Multicriteria Decision-Making Framework for Supplier Selection: A Customer Community-Driven Approach

Supplier selection is the core of enterprise supply chain management. It involves a systematic evaluation of potential supply partners. Customer expectations for products and services are rarely considered when selecting suppliers. Considering customer factors in supplier selection faces many problems, including customer segmentation, importance ranking for customer requirements, and answering how customer requirements guide the supplier selection. For the above, a multicriteria supplier selection framework driven by customer communities is proposed. It includes three stages. In the first stage, a customer segmentation method is used to discover customer communities. In the second stage, the weighted interval rough number method quantitatively analyzes the customer requirements in each community, and then expert knowledge is integrated to determine the importance of supplier selection indicators. In the third stage, a genetic algorithm based on a stochastic tournament model is used to search for the optimal suppliers. A practical case study of a household refrigerator was conducted to illustrate the performance of our framework. A simulation experiment was designed to verify that our framework could update the supplier selection scheme according to changes in customer requirements in a dynamic scenario.

Supply chain coordination mechanisms of coal power enterprises under renewable energy quota system: A perspective of game analysis

The renewable energy quota system has become an important policy tool for countries around the world to solve the differences in renewable energy resource endowments between regions and promote the transformation of energy structure. How to coordinate the supply chain of power generation enterprises from the micro level of enterprises has become a key issue to ensure the implementation of renewable energy quota system. By constructing a game analysis model, this research studied the coordination game problem between the supply chain of coal power enterprises and renewable energy enterprises, and compared and analyzed the differences in decision-making between centralized and decentralized situations. The results illustrate that in the case of centralized decision-making, although renewable energy enterprises and coal power enterprises can guarantee profits and carbon emission reduction effects. However, in the real situation of independent rational economic man, it is difficult to ensure the real realization of centralized decision-making. Further, the research proposed that in the case of decentralized decision-making, the negotiation mechanisms of revenue sharing, cost allocation, and revenue sharing + cost allocation were used to solve the supply chain coordination problem of renewable energy enterprises and coal power enterprises. The equilibrium solution of the game model under different negotiation mechanisms is obtained. Finally, the results of theoretical analysis were verified by practical examples and the corresponding sensitivity analysis is carried out. The conclusion has decision-making reference value for solving the coordination problem between coal power enterprises and renewable energy enterprises, improving the overall income of supply chain and carbon emission reduction, and effectively promoting the implementation of renewable energy quota system.

Application of Financial Big Data Analysis Method Based on Collaborative Filtering Algorithm in Supply Chain Enterprises

At present, the financial situation of China’s supply chain finance is still relatively unstable, and there are still some problems between supply chain enterprises and banks such as asymmetric information, insufficient model innovation and high operational risks. Based on this, this paper proposes and constructs a risk control model of financial big data analysis based on collaborative filtering algorithm. The purpose of this study is to realize the resource integration of supply chain enterprises and optimize the logistics chain, financial chain and information chain through the analysis of financial big data based on collaborative filtering algorithm, provide quality services for supply chain enterprises and good support for solving the financing problems of small and medium-sized enterprises. In order to verify the feasibility of the model, an experimental analysis is carried out. The experimental results show that this model has good scalability and operability, and the algorithm itself also has good scalability. The results of empirical analysis further verify that the design method in this paper has a good recommendation effect in terms of matching degree and user satisfaction. Compared with other risk control models, it is more practical and feasible. This research has certain practical significance for the financial management of supply chain enterprises.

Sustainability-based enterprise supply chain optimization and response under circular economy approach: agile, adaptive and coordinated

PurposeFrom a supply chain perspective, logistics firms collaborate with other supply chain members to extend their business scope. Investment in circular economy projects in the supply chain can not only broaden the scope of business but also increase the value of the entire supply chain. Third-party logistics companies are gradually participating in the construction and operation of many circular economy projects. How to coordinate multiple circular economy supply chain projects is at the core of its operation.Design/methodology/approachThis paper first analyzes some typical supply chain projects in China and summarizes the main features of these projects. Secondly, considering the benefits of the project and the stakes of each project, a multi-stage stochastic programming model is established. Finally, Cplex, nested decomposition, LocalSolver and other methods are adopted to simulate and analyze the model.FindingsThe final experimental results find that the importance of coordinating multiple circular economy supply chain projects to increase the value of the entire supply chain. The multi-stage stochastic programming model presented in this research can provide a useful tool for logistics enterprises and third-party logistics companies to optimize their investment decisions and maximize their profits in the context of a circular economy.Research limitations/implicationsThere are still some limitations to this study; for example, it is limited to the analysis of circular economy supply chain projects in China. The study focused on third-party logistics companies, and other enterprises in the circular economy supply chain were not considered. The research also assumed that the benefits of each circular economy project and the stakes of each project were known, which may not always be the case in real-world scenarios.Originality/valueThis manuscript found that investing in other circular economy projects in the supply chain can broaden the scope of business and increase the value of the entire supply chain. Third-party logistics companies are gradually participating in the construction and operation of many circular economy projects, such as recycling and repurposing initiatives. It highlights the importance of coordinating multiple circular economy supply chain projects to increase the value of the entire supply chain. The multi-stage stochastic programming model presented in this research can provide a useful tool for logistics enterprises and third-party logistics companies to optimize their investment decisions and maximize their profits in the context of a circular economy.

Enterprise Supply Chain from the Perspective of SocioeconomicsTaking Taobao and Amazon as Examples

With the rapid development of the Internet in the world, the Internet has connected the world as a whole, and online shopping has brought many conveniences to people. People can buy items from all over the world on their mobile phones or computers. Especially in the sudden epidemic period, people stay at home, so online shopping has gradually become the choice of more and more people. This paper mainly studies the corporate supply chains of Taobao and Amazon and their supply policy changes and impacts before and after the epidemic. This paper uses literature analysis method and others to analyze and study this topic. Research data are mainly obtained from professional articles or literature. The results of the study found that both companies found suitable measures for their own supply chain development during the epidemic, and adopted them in a timely manner, and finally achieved unexpectedly good results both at the economic level and social employment level.

Impact of COVID-19 on the Supply Chain of Small and Medium Enterprises: Case Studies on Food, Manufacturing and Hospitality Industries

The constant flux in the supply chain has intruded on the demand and supply equilibrium throughout the globe. Firms that elongated the operation period have to pursue changes in suppliers to respond to the tumultuous trading environment due to the COVID-19 pandemic. This paper aims to develop a framework for supply chain disruption for different small and medium enterprises (SMEs) in the Food, Manufacturing, and Hospitality industries. SMEs are susceptible to fluctuant economic change since the change puts an enormous threat to the sustainability of SMEs. Therefore, strategic foresight is crucial for SMEs to be competitive in the market. In this paper, rationalization and digital transformation are chosen as potential measures to conquer the unsettled economic environment. Reformation and innovation in SMEs could provide opportunities to maintain the firms long-term healthy operation. This study can help SMEs comprehend the importance of modern strategies and survive during the outbreak of COVID-19.

Research on Enterprise Supply Chain Management --- Taking Apple as an Example

The term supply chain management first appeared in the logistics literature in the mid-1980s. The goal of so-called supply chain management is to plan, implement and control in order to reduce production costs and improve production efficiency. This paper aims to analyze enterprise supply chain management. The supply chain involves most of the products in our lives. The paper starts by presenting an overview of supply chain and the importance of it. This paper chooses Apple as an example to analyze supply chain management. Apple is the world's leading high-tech company, which can offer me some experience. The supply chain was not pioneered by Apple, but they do a good job. In the supply chain, part of the enterprise's business is external, which reduces costs and improves production efficiency. Apple is consumer-oriented. Some businesses are external and so on, which makes it a win-win situation for him and his partners. But there are also some problems in Apple's supply chain management, such as excessive exploitation of downstream suppliers and neglect of employee rights and interests. Then this paper discusses how they make changes in order to improve supply management. Finally, we summarize how to effectively manage supply chains in businesses. Apple needs to pay attention to the low-end market, strengthen the supervision of suppliers, reduce the exploitation of suppliers, and truly protect the rights and interests of those suppliers' employees. In addition, it should shorten and optimize the supply chain to make the company's operations more stable.

Operational decisions of live-streaming platform supply chain based on control power: considering the dual preferences of consumers

As the problem of live streaming with goods ‘overturned’ has also emerged, it is crucial for supply chain members to make optimal decisions to maintain long-term cooperation relationship. Based on this background, we construct a new supply chain structure composed of a fresh food supplier, an online celebrity live-streaming base (OCLB) and a platform channel, and establish three game-theoretic models: the centralised decision model (CDM), two decentralised decision models (DDMs) led by fresh food supplier (P-S-L model) and OCLB (P-L-S model) to further explore the optimal decisions. The results show that, when consumers have higher dual preferences of freshness and live-streaming recommendation level, in the P-S-L model, it is in the best interest of the supply chain as a whole to pursue ‘neutral’ control power and choose a ‘moderate pricing and decent quality’ strategy, but in the P-L-S model, the OCLB as the dominant party can pursue higher control power, increase the selling price, or relax its preservation technology upgrading program, which may compensate for the loss of high preservation costs. This study follows the popular topic of live-streaming with goods, opens up new ideas to improve the high profitability of supply chain enterprises.

Low-Carbon Transformation Strategy for Blockchain-Based Power Supply Chain

Carbon abatement in the power sector is essential to achieving the “double carbon” goal, and blockchain technology, one of the most promising emerging technologies, will assist the power sector in efficiently achieving this goal. In terms of the effectiveness of carbon abatement, comparative studies on coordination mechanisms are absent in the existing literature. On this basis, aiming at the cooperative abatement strategy between power generation generators and sellers under the carbon tax policy, this paper has developed four decision models: the Stackelberg game led by power generation enterprises, the simultaneous Nash bargaining decision by both parties, the vertical integration decision by supply chain enterprises, and the cooperative carbon emission reduction game by supply chain enterprises, to analyze the changes in electricity price, sustainability level, power sales, and profits of supply chain members. The results of the numerical analysis show that user preference for blockchain technology and an increase in the proportion of low-carbon electricity information uploaded to the blockchain can significantly improve the sustainability level of the electricity supply chain. The level of investment in green technologies by electricity producers under cooperative abatement decision-making increases compared to the electricity producer-dominated Stackelberg game model. The sustainability level of the electricity supply chain is higher under the Nash simultaneous decision than under the abatement cost-sharing decision, but the decision-maker’s profit is lower. The values of overall profit and sustainability level of the electricity supply chain are both highest under the vertically integrated decision.

Retracted: Sustainable Trend of Big Data in Enterprise Supply Chain Under the Artificial Intelligence Green Financial System.

[This retracts the article DOI: 10.1155/2022/3065435.].

Reducing Costs to Enhance Profits for Logistics Companies: Strategies and Best Practices of JD Logistics

With the development of big data and technology, the competition among e-commerce enterprises is becoming increasingly fierce. Reasonable integration of modern products into the operation of enterprises to obtain higher efficiency, and lower costs, will obtain greater competitive advantages. This paper studies how to reduce the enterprise supply chain's operation, transportation, and other costs. What can draw from the analysis is that enterprises need to progress with The Times. Apply big data to the supply chain management of enterprises. Moreover, use modern technology to replace part of the manual work to improve efficiency and reduce costs. Big data management and supply chain management are beneficial to all enterprises. Take JD Logistics as an example to see the big picture. This can give more ideas for the development of the enterprise. It also promotes the development of big data and technology in reverse.

Transformation of martial law logistics

The article discusses the current problems of logistics in Ukraine that have emerged as a result of the war. Priority areas of logistics transformation are determined, based on current changes. The situation with Ukraine’s logistics infrastructure is analysed, and the damages caused by Russia’s military actions are estimated. The results of an expert research on the impact of logistics problems on business are presented and their main effects are identified. The study of current logistics problems in wartime in Ukraine has shown that companies are facing significantly increased logistics challenges. The most important factors that affect the efficiency of logistics processes are the instability of the situation at the front line, the complexity of transportation routes, restrictions on movement, changes in warehouses, etc. The article describes the problems of ensuring the safety of organizing and planning routes, warehouse support, and transportation. In addition to the situation in the warehouses, there were difficulties with the procurement of goods. This is due to the fact that the number of suppliers has decreased and the range of products has become somewhat limited. The main changes in the supply chains of enterprises are characterized, and the DDMRP approach is chosen as a priority concept for their transformation. This approach allows planning the storage volumes of goods based on the actual consumption, taking into account potential fluctuations in demand.

Allocation of the Carbon Emission Abatement Target in Low Carbon Supply Chain Considering Power Structure

The proposal of China’s dual carbon strategy is not only a kind of pressure but also an opportunity for enterprises. Both upstream and downstream enterprises in the supply chain pay more attention to carbon emission reduction, and consumers are gradually turning to a low-carbon preference. How carbon reduction targets are allocated among supply chain members with different technical efficiency and market opportunities will directly affect supply chain performance and social welfare. Power structure is an important factor that dominates the decision-making of the supply chain, so we establish the low-carbon supply chain model under three different power structures: manufacturer-led, retailer-led, and power pairs between two parties. We study the government distribution decisions of carbon emissions reduction targets under different supply chain power structures and discuss the influence of supply chain power structures on carbon emissions reduction distribution decisions and social welfare. The study found that if the carbon emissions reduction target increases, the government will adjust the allocation strategy to increase the proportion of enterprises whose emissions cuts have less impact on market demand. The study also found that the government will allocate more emissions reduction to enterprises with higher emissions reduction efficiency, and enterprises whose emissions reductions have a greater impact on market demand. When supply chain enterprises have equal power, the supply chain will have greater social welfare and market demand, but not necessarily greater supply chain profits.