Enterprise Supply Chain Research Articles

System model of risks and trees of alternative solutions for improving the logistics chain at a manufacturing enterprise

The subject of this article is the decision-making processes for improving the elements of the supply chain of a manufacturing enterprise under conditions of uncertainty and risks. The purpose of the research is to reduce the time and cost of in supply and distribution of products of manufacturing enterprises by considering possible risks through making rational management decisions. The article addresses the following tasks: examination of the characteristics of supply chain elements; investigation of the main problems of supply and distribution management and identification of ways to solve them; development of a systemic model of logistic risks for a manufacturing enterprise; and formation of decision trees for alternative decisions in strategic supply chain management at manufacturing enterprises. The methods applied include a systems approach, structural decomposition methods, a risk-oriented approach. The following results were obtained: features and problems of supply chain elements such as supply, production, storage, and distribution were examined and identified; main supply chain management tasks were investigated and solutions identified; problems in warehouse management were pinpointed; internal and external supply risks were identified; a systemic model of logistic risks for a manufacturing enterprise was formed, which main components are logistic problems, partial risks, their consequences, and possible management decisions to mitigate risks; decision trees were built for problems of raw material supply instability and transportation bottlenecks and delays; an alternative decision diagram was constructed for an illustrative example. Conclusions: To overcome the problem of raw material supply instability, it is recommended to develop diversification of supply sources, stock reservation, and the use of alternative transport routes. Building alternative decision trees in strategic management is an effective tool for making rational decisions by manufacturing enterprises in complex conditions of uncertainty and risks. They help to analyze alternatives and their consequences to choose a path to optimize the supply chain.

Research on trust mechanism of supply chain finance under Industrial Internet embedded with blockchain.

In traditional supply chain finance, the financing of enterprise mainly relies on the credit segmentation of the core enterprise, resulting in a short trust transmission radius and poor financing ability. The development of Internet technology, while expanding financing channels, has also seen an increasing severity in issues such as information fraud and data breaches, which has further aggravated the trust crisis in supply chain finance. This paper integrates blockchain technology into the industrial internet platform and analyzes the applicability of both in empowering supply chain financial trust. Then a supply chain financial trust framework, which emphasizes information sharing, data security, and trust circulation, is proposed. Furthermore, combined with the theories of Funk-SVD and entropy value, this paper designs a global trust evaluation mechanism that facilitates the trust circulation in supply chain finance and proposes a recommendation algorithm for global trust. With the testing conducted using the Epinions dataset, it is found that the algorithm proposed in this paper has a strong data dimensionality reduction and concentration ability, especially for large sample data, it can obtain more accurate evaluation values with less space occupation, thus enhancing the trust circulation ability of supply chain finance. Finally, the paper puts forward specific policy recommendations for the implementation of the supply chain finance information mechanism, aiming to better improve the financing accessibility of enterprises in supply chain, particularly small and medium-sized enterprises.

Collaborative system model construction and simulation optimization of e-commerce enterprise supply chain

ABSTRACT With the rise and rapid development of the e-commerce industry, the pressure borne by the supply chain of e-commerce enterprises is increasing, which greatly increases the complexity and uncertainty of inventory management in the e-commerce supply chain. The study integrates system dynamics and collaborative supply chain inventory management to construct a new model. The study first uses the concept of system dynamics to optimize the supply chain inventory management system; then the collaborative supply chain is used to construct a system model by combining the optimized management system. The results show that the collaborative supply chain inventory management model constructed by the study can better accelerate the product turnover rate, improve the overall operational efficiency and market competitiveness of the supply chain, and can provide new support for the development of e-commerce enterprises.

The Application of Integrating Data Mining and IoT Management Technology in Enterprise Supply Chain Information Management

The Application of Integrating Data Mining and IoT Management Technology in Enterprise Supply Chain Information Management

Data-driven View of Customer Psychological Anxiety Attributes for Cooperate Social Responsibility in Supply Chain Management: a LDA Model

Background-Cooperate Social Responsibility (CSR) in supply chain management requires understanding customer psychological anxiety attributes. A data-driven approach, such as using a Latent Dirichlet Allocation (LDA) model, can provide insights. By recognizing and addressing customer psychological anxiety, CSR can provide better support, which leads to higher customer satisfaction. When customers feel understood and supported, they are more likely to have a positive perception of the company and its supply chain services. Subjects and methods- The study aims to use the LDA method to explore consumer psychology anxiety and its attributes for CSR in supply chain management. The corpus is collected from the Web of Science core collection with keywords “CSR” and “supply chain management”, and 965 articles related to the field from1990-2022. LDA is a natural language processing technique that uncovers thematic structures in textual data. By applying LDA to customer feedback, businesses can identify anxiety attributes. Steps include data collection, preprocessing, LDA model training, topic interpretation, and deriving business insights. Results- The study used the Python program to run LDA, after putting in the text data, the study identify number of 11 topics according to the value of topic coherence, then identified topics based on the most representative words or phrases within each topic combined CSR and supply chain related knowledge and fit the service quality model to find the customer psychological anxiety attributes, the results reveal that customer tend to be anxiety about the aspects of reliability and assurance for CSR in supply chain management, more concern about the environmental and social aspects responsibility. Conclusions- The study revealed customer psychological anxiety about CSR initiatives and strategies within their supply chain management. The results show that consumers feel most anxiety about the aspects of reliability and assurance of supply chain management. They are concerned about the environment and social responsibility that the supply chain enterprise is taking, especially in the food supply chain field. By addressing these concerns, organizations can enhance customer satisfaction, build stronger relationships, and improve their overall CSR performance. The findings of this study also contribute to the field by providing valuable guidance, further research can add other text mining methods like structural topic modelling, or add deeper quantitative research in the field and develop of a new customer-CSR service quality model in the service industry.

A Study on the Reform of Practical Teaching in Purchasing Management Course

With the development of a globalized economy and rapid changes in the market environment, procurement management, as a key link in the enterprise supply chain, has an increasing demand for professional talents. However, the traditional teaching mode of procurement management often difficult to meet the industry's composite demand for high-quality procurement management talents, and there are problems such as the disconnection between theory and practice and the obsolescence of teaching resources. Therefore, the practical teaching reform of procurement management courses has become an important task to improve the quality of education and cultivate students' comprehensive ability. This paper analyzes the current problems in the teaching of procurement management, puts forward targeted reform measures, and discusses the importance of these measures to enhance students' practical ability and theoretical application abilities.

Enterprise digital transformation and supply chain resilience

Digitalization provides new opportunities for enhancing supply chain resilience and security levels. This paper, using Chinese listed companies as research samples, characterizes enterprise supply chain resilience in terms of supply chain resistance and recovery ability. By constructing an empirical econometric model, it examines the impact of enterprise digitalization level on supply chain resilience. The results show that the level of digitalization significantly enhances supply chain resilience. Furthermore, heterogeneity tests indicate that the improvement effect of enterprise digitalization on supply chain resilience is more significant in state-owned enterprises and companies with higher levels of marketization.

Is supply chain risk mitigation affected by organisational design? The roles of organic structures and cultures

The objective of this paper is to investigate the potential of organisational design as a potent approach to supply chain risk management (SCRM). Using contingency theory, the current research distinguishes between two design options: organic and mechanistic organisations, both at the structural and cultural levels. The authors predict a positive relationship between the organic nature of structural and cultural elements and the level of supply chain risk mitigation. They also predict a positive interaction effect between structural and cultural elements. To test hypotheses, multiple and moderated regression analysis was conducted on a sample of 213 small and medium-sized enterprises in the Spanish agri-food supply chain. The results confirmed the proposed hypotheses. This research contributes to the literature on SCRM by opening a discussion on the impact of organisational design as means of managing supply chain risk. In particular, it draws attention to the positive combined effects of the different design characteristics (structural and cultural). Furthermore, this study provides managers with insights into the use of organisational design as an additional tool for managing supply chain risk.

Energy supply chain efficiency in the digital era: Evidence from China's listed companies

With the widespread adoption of cutting-edge digital technologies, including big data, blockchain, artificial intelligence (AI), and cloud computing, the development and digitalization of the supply chain are experiencing significant integration. According to China's Fourteenth Five-Year Plan for a Modern Energy System, the country has embarked on a new phase of constructing a modern energy system. An accelerating trend in the digital upgrading of energy businesses marks a period of innovation and upgrading for the modern energy industry. Although policy documents highlight the role of digital technology in advancing the digital transformation of energy businesses, the underlying relationships and transmission mechanisms have yet to be fully explored, underscoring the necessity for targeted policy development. This study examines the link between enterprise digital transformation and energy supply chain efficiency, utilizing a bidirectional fixed-effects framework and analyzing data from 112 listed companies in the energy sector from 2011 to 2019. Employing a three-stage DEA model and text analysis to measure the primary indicators, findings suggest that digital transformation enhances energy supply chain efficiency by fostering technological innovation, leveraging government subsidies, and increasing openness levels. Moreover, the positive impact is more pronounced in large and private enterprises, especially in the eastern and northeastern regions. This study offers empirical support for the policy framework mentioned, advocating for the advancement of business digital transformation, the establishment and enhancement of digital supply chain systems, and the integration of supply chain enterprise resources upstream and downstream.

Study on the Joint Outsourcing Mechanism of Carbon Emission Reduction in The Supply Chain Considering Risk Appetite

In the case of considering the risk preference, according to the problem of supply chain carbon emission reduction joint outsourcing, build the enterprise outsourcing, the supply chain, and analyze the suppliers and manufacturers of the outsourcing factors of the decision, finally summarize the research in this paper, for the risk aversion of supply chain enterprise carbon emission reduction joint outsourcing mechanism to provide certain management enlightenment, to the future research.

Social enterprises in supply chains: driving systemic change through social impact

PurposeThis paper aims to provide a starting point to discuss how social enterprises can drive systemic change in terms of social impact through operations and supply chain management.Design/methodology/approachThis paper reviews existing literature and the four papers in this special issue and develops a conceptual framework of how social enterprises and their supply chains create social impact and further enable systematic change.FindingsOur paper finds that social impact and systemic change can be shaped by social enterprises at three different levels of analysis (organization, supply chain and context) and through three enablers (cognitive shift, stakeholder collaboration and scalability). Such dimensions are used to position current literature and to highlight new research directions.Originality/valueThis paper proposes a novel understanding of operations and supply chain management in social enterprises intended as catalysts for systemic change. Based on this premise we distinguish different practices and stakeholders to be considered when studying social impact at different levels. The conceptual framework introduced in the paper provides a new pathway for future research and debate by scholars engaged at the intersection of social impact, sustainable operations and supply chain management.

The Potential of New Retail Models: Financial Analysis of JD and Suning Supply Chain Management Capabilities

With the popularity of e-commerce and online consumption, offline sales stores have encountered a bottleneck period, and the competition in China’s retail market is becoming increasingly fierce. Many retail industries are moving towards the new “online + offline” retail model. This trend represents the retail industry catching up with the digital age, merging the traditional brick-and-mortar economy with online sales channels to meet better changing consumer needs. This study combines several research results, and this paper analyzes the level of the enterprise supply chain from the five indicators of revenue growth rate, inventory turnover rate, return on assets, sales expense ratio and management cost ratio. This paper will take Jingdong and Suning as examples to analyze the characteristics of the new retail model based on the overview of the new retail model, deeply study and discuss the impact of the new retail model on the development of enterprises, and analyze the opportunities and challenges they face. Finally, targeted suggestions are put forward to promote the development of the new retail model for enterprises.

Revolutionizing Supply Chains: A Comprehensive Study of Industry 4.0 Technologies (IoT, Big Data, AI, etc.)

The objective of this paper is to explain about Technologies of Industry 4.0, including the Internet of Things (IoT), Big Data, Artificial Intelligence (AI), amongst others, and how they are reshaping enterprises supply chain in the era of digitalization by boosting effectiveness, productive capacity and choices. This paper regards at how Technologies Industry 4.0 impacts firms, underlining difficulties yet chances. IoT's incorporation within Industry 4.0 assists with monitoring data instantly and analysing it, bettering optimization in production and adaptability to fluctuating market demands. Big Data Analytics within Industry 4.0 brings forth foresights for preventative upkeep plus effective allocation resources enhancing functional efficiency furthermore. Applications of AI inside Industries 4.0 performs task automation, predict machinery breakdowns along personalized marketing techniques advancing productivity plus creativity. Cyber-Physical Systems (CPS) throughout Industry 4.0 enable observing plus controlling hence perfecting decisions making along with mechanization within the supply chain. Responsive technologies such as Robotics and automation enhance manufacturing processes and be more competitive through higher efficiencies. While Augmented Reality (AR) & Virtual reality (VR) improve training and design processes, thus improving efficacies. Blockchain assures transparency and trust, revolutionizing supply chain management. Cloud computation provides scalability alongside cost-effective attributes assisting transform digitally. Though confronted by hurdles such as cybersecurity & infrastructural issues successful embracing technologies from Industry 4.0 opens up immense advantages reshaping traditional business models and societal structures. Firms must adopt these techs if they wish to stay competitive and innovative in a digital-first world. Key Words Industry 4.0, Internet of Things (IoT), Big Data, Artificial Intelligence (AI), Blockchain Technology

Resilience evaluation of low-carbon supply chain based on improved matter-element extension model.

How to evaluate the resilience level and change trend of supply chain is an important research direction in current supply chain management practice. This paper proposes a new method of supply chain resilience assessment based on hesitant fuzzy linguistic term set (HFLTS) and matter element extension theory. Firstly, based on the research status quo at home and abroad, a low-carbon enterprise supply chain resilience assessment index system is established, which includes six first-level indicators and corresponding 21 second-level indicators of product supply resilience, resource resilience, partner resilience, information response resilience, financial resilience and knowledge resilience. Secondly, HFLTS was used to collect expert opinions and Ordered Weighted Arithmetic (OWA) to calculate the expert composite language, by which the fuzzy evaluation matrix of supply chain resilience assessment indicators was obtained. Once again, the resilience indicator weights are determined based on a game-theoretic portfolio assignment method combining the best-worst method (BWM) and the CRITIC method. Finally, the nearness degree function is combined with the extension comprehensive evaluation method to improve the matter element extension model, and the supply chain resilience assessment model of low-carbon enterprises based on the game theory combination assignment-improved matter element extension is established. Taking X low-carbon enterprise as an example, the evaluation results show that the supply chain resilience level of this enterprise is II, and the eigenvalue of the grade variable is 2.69, and the supply chain resilience is shifting to III, and the supply chain resilience is shifting to III, which indicates that the supply chain resilience of this enterprise is being enhanced. Therefore, the improved matter element extension not only ensures the accuracy of the evaluation results, but also has higher prediction accuracy.

Selection of presale models for innovative products considering channel preferences and valuation differences.

To reduce financial pressure and operational risk, and improve match between supply and demand, an increasing number of enterprises are adopting presales to launch new products. In this context, this paper investigates three presale models for innovative products, namely, the no-presale model, the manufacturer presale model and the retailer presale model. A Hotelling model is used to describe the impact of channel preferences and valuation differences on the two-stage competition between innovative products. Aiming at evaluating the purchase behavior of consumers under three presale modes, a game optimization model is established to analyze the presale decision problem for innovative products under different presale entities. The research shows that: (1) Compared with no-presale, presales can help enterprises obtain more profits. The overall profit of the supply chain is optimal under the retailer presale mode. (2) When the difference in channel preferences is small, the manufacturer obtains the greatest profit by choosing the direct presale model. In contrast, the selection of different presale entities has a significant impact on product sales and supply chain enterprise profits. At this point, the manufacturer should choose the retailer presale model. (3) When the product valuation discount is high, the manufacturer can increase the spot and wholesale prices to induce consumers to choose the presale method to purchase the product. In the opposite situation, the manufacturer should lower the presale price to improve the presale utility of consumers and encourage them to participate in the presale. These conclusions provide more targeted suggestions for enterprises to formulate presale strategies, which can help them grasp market demand and improve market competitiveness.

Optimization algorithm for enterprise supply chain network based on blockchain distributed technology in the context of digital economy

In the era of digital economy, the optimization of enterprise supply chain networks has become a key challenge, while the problems of traditional supply chains, including information asymmetry and lack of trust, seriously hinder the development of enterprise supply chain networks. This paper will use the blockchain distributed technology and the digital economy background to explore how to use the blockchain distributed technology to optimize the existing problems. Firstly, study the supply chain information sharing to develop resources to reduce costs, then use the application of block chain technology and smart contract to establish information sharing mechanism to help the supply chain information more transparent and improve trust; secondly, use the block chain technology decentralized storage model to realize the decentralized supply chain research, and finally use the consensus method to improve the privacy protection of information, to avoid information asymmetry among users. Through experiments, it could be found that the optimization method of enterprise supply chain network based on blockchain distributed technology had a traceability accuracy of over 92.35% for the extracted products, with an average traceability accuracy of 93.791% for 10 products. Research on the transparency of different supply chain information was above 89.73% . By utilizing blockchain distributed technology, information protection in enterprise supply chains could be effectively improved; trust mechanisms could be better established; risk control effectiveness could be improved; optimization of enterprise supply chain networks could be better assisted.

Enterprise Supply Chain Optimization Algorithm Based on Big Data

Enterprise Supply Chain Optimization Algorithm Based on Big Data

Effects of interactions between technology spillovers and carbon transfers on carbon emission reduction decisions and coordination within supply chains

PurposeThis paper aims to refine the mechanisms affecting the two-way technology spillover and carbon transfer interactions between supply chain enterprises, and to guide their reduction of carbon emissions.Design/methodology/approachThis study formulates a supplier-led Stackelberg game model to explore the effects of the interactions between two-way technology spillover effects and carbon transfers in decentralized and centralized decision-making scenarios. The optimized Shapley value is introduced to coordinate across the supply chain and determine the overall profits lost in the decentralized scenario.FindingsEmission reductions by the low-carbon manufacturer are negatively correlated with the carbon transfers. Vertical technology spillovers promote carbon reduction, whereas horizontal technology spillovers inhibit it. The vertical technology spillovers amplify the negative effects of the carbon transfers, whereas the horizontal technology spillovers alleviate these negative effects. When the vertical technology spillover effect is strong or the horizontal technology spillover effect is weak in the centralized scenario, the carbon reduction is negatively correlated with the carbon transfers. Conversely, when the vertical technology spillover effect is weak or the horizontal technology spillover effect is strong, the enterprise’s carbon reduction is positively correlated with the carbon transfers. An optimized Shapley value can coordinate the supply chain.Originality/valueThis study examines the effects of carbon transfers on enterprises from a micro-perspective and distinguishes between vertical and horizontal technology spillovers to explore how carbon transfers and different types of technology spillovers affect enterprises’ decisions to reduce carbon emissions.

Industry 4.0 and Sustainability Integration in the Supply Chains of Micro, Small, and Medium Enterprises through People, Process, and Technology within the Triple Bottom Line Perspective

This study fills a crucial gap in the research on Micro, Small, and Medium Enterprises (MSMEs), with the main objective of proposing a framework to support the integration of Industry 4.0 (I4.0) and sustainability into the supply chains of MSMEs. This integration is accomplished by people, process, and technology (PPT) mechanisms, all while adopting the triple bottom line (TBL) perspective. A mixed-method approach was employed for this study, which included a scoping review of 147 publications, expert panels, focus groups, and a survey with 55 valid responses. The findings identified 32 key indicators linked to the primary barriers and enablers of I4.0 and sustainability integration (S-I4.0) in MSMEs’ supply chains. This study also highlighted the dominant barriers and enablers within the PPT mechanisms and TBL dimensions, and their causal relationships and influences. The results were synthesized into a novel S-I4.0 framework, separately applied to Micro and Small Enterprises (MSEs) and Medium Enterprises (MEs) due to company size-related variations. This study offers valuable insights for academics and provides practical guidelines to assist MSMEs in integrating I4.0 and sustainability into their supply chains. An important contribution concerns to the need to treat MSEs and MEs differently. These research results provide relevant and novel guidance for MSEs and MEs to accelerate the S-I4.0 adoption process, with an immediate impact on their supply chains.

Retracted: E-Commerce Enterprise Supply Chain Cost Control under the Background of Big Data

Retracted: E-Commerce Enterprise Supply Chain Cost Control under the Background of Big Data