Supply Chain Management Methods Research Articles

Research on supply chain efficiency optimization algorithm based on reinforcement learning

Supply chain efficiency is critical to enterprises and can affect their competitiveness. The supply chain faces an uncertain and complex external market environment, facing the problem of supply chain efficiency optimization; the traditional optimization method is ineffective, which can better face the current environment and deal with problems. It has advantages in optimizing supply chain efficiency and has been widely used. This paper first expounds on the importance of supply chain management status, the limitations of traditional supply chain management methods, and reinforcement learning in the application of supply chain optimization. Then, through experiments, reinforcement learning, supply chain optimization problems, and the analysis of related algorithm design, the optimal algorithm focuses on inventory management optimization. Finally, this paper points out the future research directions and development trend of the supply chain efficiency optimization algorithm based on reinforcement learning.

Enhancing supply chain security and transparency with ai and blockchain integration for future-proof solutions

The objective of this review paper is to examine the integration of Artificial Intelligence (AI) and blockchain technology to enhance supply chain security and transparency, providing future-proof solutions for global industries. As the digital landscape evolves, traditional supply chain management methods face increasing vulnerabilities and inefficiencies. This paper reviews existing literature to assess the current challenges and potential benefits of integrating AI and blockchain in supply chains. The review highlights how AI enhances predictive analytics, demand forecasting, and operational efficiency, while blockchain ensures immutable, decentralized ledgers for real-time tracking and verification of goods. The synergy between these technologies offers unprecedented levels of transparency, enabling stakeholders to detect and respond to anomalies swiftly. Case studies across various industries demonstrate significant improvements in reducing fraud, counterfeiting, and human errors, alongside enhanced compliance with regulatory standards. Conclusions drawn from this review underscore the transformative potential of AI and blockchain in creating resilient, transparent, and secure supply chains. The integration of these technologies not only addresses current vulnerabilities but also lays the foundation for adaptive, intelligent supply chain networks capable of withstanding future disruptions. This paper provides actionable insights and practical frameworks for businesses and policymakers aiming to implement AI and blockchain solutions, emphasizing the importance of strategic planning, cross-industry collaboration, and continuous innovation in achieving long-term supply chain sustainability and security.

Analyzing the Negative Impact of Supply Chain Regionalization

In response to increasing global trade, IKEA implemented a more efficient supply chain strategy and introduced a new policy in 2011 to localize its supply chain. The objective of this inquiry was to examine the alterations in supply chain management. Following the transition from centralized to regionalized supply chains, corporations faced adverse consequences such as decreased operational efficiency, increased operating expenses, and reduced adaptability in meeting market needs. These implications include increased complexity in supply chain management, decentralized operating models that result in repeated investments in fixed assets, and trade restrictions that create challenges in integrating information. The article proposes implementing efficient management systems, enhancing collaboration with local suppliers, and utilizing artificial intelligence to optimize the structure of the supply chain based on the observed impacts and outcomes. The objective is to offer risk management guidance for firms that have reached maximum production capacity and require a shift in their supply chain management methods.

Analyzing the Negative Impact of Supply Chain Regionalization

In response to increasing global trade, IKEA implemented a more efficient supply chain strategy and introduced a new policy in 2011 to localize its supply chain. The objective of this inquiry was to examine the alterations in supply chain management. Following the transition from centralized to regionalized supply chains, corporations faced adverse consequences such as decreased operational efficiency, increased operating expenses, and reduced adaptability in meeting market needs. These implications include increased complexity in supply chain management, decentralized operating models that result in repeated investments in fixed assets, and trade restrictions that create challenges in integrating information. The article proposes implementing efficient management systems, enhancing collaboration with local suppliers, and utilizing artificial intelligence to optimize the structure of the supply chain based on the observed impacts and outcomes. The objective is to offer risk management guidance for firms that have reached maximum production capacity and require a shift in their supply chain management methods.

Improved Association Rule Mining-based Data Sanitisation with Blockchain for Secured Supply Chain Management

A supply chain management (SCM) method must include information sharing as a vital component in order to improve supply chain performance and boost an organisation’s strategic advantage. Since, due to a lack of trust concern over information leakage, and security breaches by nefarious individuals or groups, several organisations are hesitant to share information with their supply chain partners. This work presents a new supply chain management-based secure data transmission method. By using blockchain-based data storage, it is assumed that the manufacturers, suppliers, and customers would transfer data that must be kept private during transmission. As a consequence, this paper aims to provide an improved association rule mining with a data sanitisation scheme with an improved Apriori algorithm used in the proposed data sanitisation process. In particular, the Long Short-Term Memory (LSTM) will generate keys by considering the objective relying on the value of the preservation ratio, false rule generation, hiding failure, and degree of modification. The weights are adjusted via a novel Minkowski distance-based Namib beetle optimisation (MDNBO) technique, which also improves the performance of the LSTM model. The reverse process of encryption occurs when encrypted data are restored at the receiving end. By contrasting it with the old methods with regard to security as well, the proposed protected data in SCM with blockchain technology will be proved to be efficient.

Impact of green manufacturing, green purchasing, and eco-design on organizational performance in the FMCG sector of Pakistan

Global warming, air pollution, and natural resource depletion have severely changed how businesses manufacture and provide goods and services. Greening supply chains have attracted the attention of practitioners in several nations in this context. Carbon taxes, for example, have been made a legal necessity in various countries. However, green supply chain management methods and their influence on company performance are still in their early stages of adoption. Firms frequently require the engagement of their supply chain participants to meet rising stakeholder demands for ecologically friendly goods and processes. GSCM is a collection of managerial approaches that include environmental concerns in the supply chain. Green supply chain management may help a company gain a competitive edge while improving its environmental sustainability. The overarching goal of this thesis is to add to the conversation on green supply chain management methods by examining their drivers and performance implications for the FMCG sector of Pakistan. FMCG company's supply chain must be prioritized to be efficient and effective in GSCM because these products are essential for everyone. This study aims to raise awareness about the importance of GSCM practices for the advantage of society and long-term economic and environmental development. The respondents of the 136 helped in the collection of data. They use SPSS and techniques like ANOVA, regression analysis, and correlation. All of the three hypotheses were accepted.

Emergency Management and Response Strategies for Resilient Supply Chain Systems in the Face of Unexpected Events

In the increasingly globalized and complex supply chain environment, unexpected events such as natural disasters, pandemics, and cyber-attacks have become more frequent and severe. Traditional supply chain management methods, due to their highly integrated and lean production characteristics, often lack resilience and are difficult to cope with such interruptions. The vulnerability exposed by recent global events highlights the urgent need to develop strong strategies to ensure continuity and rapid recovery. This paper aims to explore emergency management and response strategies for resilient supply chain systems in the face of unexpected events, providing systematic solutions to ensure stable operation and rapid recovery. The study delves into various aspects critical to enhancing supply chain resilience, including risk assessment, early warning systems, and emergency planning. It examines the role of advanced technologies such as big data analytics, artificial intelligence, and the Internet of Things (IoT) in predicting and mitigating risks. Additionally, it addresses the importance of effective communication and information sharing across the supply chain network, emphasizing the need for transparency and real-time data exchange. By adopting a multi-faceted approach, this paper also explores supply chain design enhancements, such as multi-sourcing strategies and redundancy, which are crucial for minimizing disruption impacts. The rapid response and decision-making frameworks are discussed to highlight the need for swift and coordinated actions during crises. Furthermore, the importance of collaboration and coordination with supply chain partners is underscored as a means to build collective resilience. Overall, this paper provides a comprehensive framework for emergency management and response in supply chains, offering practical recommendations and best practices to ensure resilience in the face of unforeseen disruptions. The insights presented aim to guide practitioners and researchers in developing and implementing robust strategies to safeguard supply chain integrity and performance amidst an ever-changing risk landscape.

Building “Porang” processing industry using supply chain management method

Wonogiri Regency is one of the leading porang producing regions in Indonesia, but the potential of its industry is still largely unexplored. Currently, business actors market corms and chips in East Java Province, resulting in a multiplier effect. This is because these actors cover only a small portion of the region. Therefore, the purpose of this study was to develop porang processing industry model through Supply Chain Management method. The study employed both quantitative and qualitative methods with Interpretive Structural Modelling (ISM) analysis. The triangulation method was used to cross-examine data at the respondents’ level. Based on the results, processed product demand, supplier engagement in the production process, and glucomannan production technology were the sub-criteria with the greatest effect on supply chain management. Furthermore, market access was identified as the major factor influenced by other sub-criteria. The strategies for establishing processing industry based on the 18 sub-criteria were in the linkage quadrant, showing the presence of high effect and interconnection. Variables in this sector must be investigated carefully because the relationship between variables is unstable. Every action on this variable will affect others and the feedback effect can magnify the impact. The strategy implemented must undergo various reviews to obtain best results. The findings of this study can be used as a reference for stakeholders to strengthen competitive advantage and implementing effective strategies

An empirical investigation of green supply chain management (GSCM) and environmental sustainability in Saudi manufacturing SMEs: The mediating role of operations analytics

Incorporating sustainability principles into Supply Chain Management (SCM) has received considerable attention in recent years, with a particular emphasis on Green Supply Chain Management (GSCM), which aims to reduce environmental consequences. Saudi Arabia has launched sustainability initiatives; however, the application of green SCM methods in SMEs in Saudi Arabian manufacturing has yet to be explored. Therefore, this research aimed to empirically assess the effect of GSCM in promoting environmental sustainability in Saudi manufacturing SMEs, focusing on the mediating function of operations analytics. Therefore, this study used a quantitative research technique to discover the link between the study variables—a rigorous questionnaire obtained primary data from managers and team leaders. SPSS was used for descriptive statistics, while SMARTPLS was used for structural equation modelling. The measurement model, path analysis, and indirect impact analysis were used to validate the research constructs and analyze the hypothesized associations. The findings support the evidence of direct positive links between green manufacturing, green business practices, eco-design and environmental sustainability in Saudi manufacturing SMEs. Conversely, no evidence was found to support the function of operations analytics as a bridge between green SCM and environmental sustainability. Although operations analytics can improve green SCM processes, more studies are needed to understand its full impact on environmental sustainability outcomes.

Models and Methods of Applied Mathematics in Supply Chain Management and Optimization

Abstract Amidst the swift expansion of the global trade economy, enterprises are confronted with escalating competition within their industries. Enhancing market competitiveness to boost economic efficiency emerges as a pivotal strategy for ensuring corporate viability. This study employs applied mathematics to refine the optimization of supply chain management, thereby offering a novel approach to augmenting management efficacy in enterprise supply chains. Initially, the research adopts mathematical models tuned to the traditional structure of enterprise supply chains, addressing prevalent profiling issues. Subsequently, it introduces a two-tier planning model to facilitate multi-objective decision-making in supply chain management. This model is rigorously applied to resolve various decision-making scenarios. An empirical analysis is conducted using Company M as a case study. Post-optimization, Company M's inventory exhibited only one instance of material shortfall, involving 132 items. The capital tied up in inventory was significantly reduced to 214,092 yuan—a decrease of 36,319 yuan compared to the capital occupied under traditional supply chain management methods. Furthermore, the optimized supply chain management system demonstrated a notable increase in the average inventory turnover rate to 12.3507%, marking an improvement of 3.6923% over the traditional model. The findings underscore the efficacy of the proposed optimization in enhancing the economic efficiency of enterprise supply chain management. This optimization not only streamlines operations but also provides robust support for the ongoing development of enterprise supply chains.

Research on E-Commerce Commodity Demand Forecasting and Inventory Optimization Based on Time Series Forecasting Model

In this study, 1996 sets of time series data are extracted from the three dimensions of merchant, warehouse and commodity, and the outliers are removed using the 3σ criterion. Through visual analysis, it was found that home improvement building materials and food and beverages were popular commodities. Then ARIMA and LSTM models were used to forecast the demand. Through 1-wmape index evaluation, LSTM model was found to perform better. Finally, the K-Means cluster analysis is carried out based on the categories of goods, merchants and warehouses, and the cluster number is selected as 70. The cosine similarity method is used to match the newly added dimensions to the category of the cluster in problem 1, and the ARIMA model is used for prediction. The results show that the cosine similarity method can accurately predict the commodity demand, the 1-wmape index is 0.801, and the residual plot presents randomness. The data of November 2022 is added to the original data, and the missing data is processed by linear interpolation. The LSTM model was used to forecast the increase of the total demand during Double 11. By setting a periodic time series with a step size of 30, the model achieves a good accuracy in predicting the demand in June, with a 1-wmape index of 0.829. To sum up, this study comprehensively considers three dimensions of merchants, warehouses and commodities, and uses different models to make accurate predictions. The ARIMA and LSTM models are adopted, while the promotion characteristics are considered and the appropriate LSTM parameters are selected. The research results provide practical forecasting tools and methods for supply chain management.

Adaptation of supply chain management methods within reverse supply chains of wood biomass

Adaptation of supply chain management methods within reverse supply chains of wood biomass

Efficiency and Sustainability in X Fresh Fruit Supply Chain: Challenges and Solutions

With the introduction of the new retail concept, China's fresh fruit supply chain industry has seen rapid growth. However, the industry faces a series of challenges during this booming phase. With the vigorous development of the community fresh fruit industry, the traditional fresh fruit supplier X Fresh Fruit is also seeking transformation opportunities. By analyzing the X Fresh Fruit supply chain company case, this paper reveals the problems of opaque supply chain structure, inefficient supply chain management and production, and high supply chain costs. Measures are needed to address these issues, including optimizing the supply chain structure, improving production and management methods, and controlling procurement, transportation, and storage costs. These measures are expected to improve supply chain efficiency, reduce costs, and ensure the quality and freshness of fresh fruits, thus creating greater value and competitiveness for enterprises. The research in this paper helps X fresh fruit companies solve their current problems and provides useful suggestions for the sustainable development of the fresh fruit supply chain industry.

Optimization models in the SCM-system: progressive supply chain management

Transformations in socio-economic space affect functioning of entrepreneurial activity, leading to a change in the configuration of business processes. In the context of increasing complexity of external environment and digitalization, subjects must ensure the activities effectiveness based on supply chains optimization. Entities are required to use progressive methods of supply chain management. The purpose of the study is to analyze main optimization models in supply chain management (SCM) to determine progressive ways to improve them. The issues of SCM have been worked out, models of their optimization considered and suggestions for their improvement made. Theoretical analysis and generalization of information that allow to substantiate the SCM optimization models’ apparatus (SCOR, DCOR, CCOR) act as a methodological basis. As a result, it is proposed to focus on possibilities of progressive supply chain management, which make it possible to use information technologies to work through a large array of data and continuously obtain values for indicators, contributing to the development of models for optimizing logistics operations and processes in the SCM. The developments obtained are planned to be used for the development of practical models for optimizing enterprises’ supply chains.

IMPLEMENTING NEW SUPPLY CHAIN MANAGEMENT PRACTICES TO IMPROVE INDUSTRIAL PRODUCTIVITY AMID THE COVID-19 PANDEMIC

This study aimed to develop a methodological approach to assessing the major directions for introducing new supply chain management (SCM) methods to improve the industrial enterprises’ productivity during the COVID-19 pandemic and test the developed approach at enterprises in the real economy related to Russia, Kazakhstan, and Azerbaijan. To this end, a comprehensive research project needed to be implemented to assess the main prospects for implementing new SCM practices. The objective was to boost the productivity of the enterprises in the context of the pandemic and identify the main problems hindering the sustainable development of such chains. The testing identified the principal characteristics of supply chains amidst the pandemic, namely reliability (30 experts spoke in favor), resilience (22), and economy (19). At the same time, a sharp decrease was observed concerning the interest in the enterprises’ supply chains optimization (7 experts), flexibility (6), efficiency (2), and environmental friendliness (4). The most promising technologies for the development of supply chains, according to the results of the study, should be considered the Internet of things (µ = 3.8), additive manufacturing (3D printing) (µ = 3.77), big data analytics (µ = 3.73), and blockchain and virtual reality (µ = 3.6 each).

Supply Chain Performance Analysis of Plant Seedling Distribution System Using Supply Chain Operations Reference Method

In the industrial world, distribution activities are one of the important things in the flow of a business process. The role of advances in information technology also has a considerable good impact on the process of exchanging information in business processes. The XYZ agency is responsible for organizing the distribution of plant seeds to all communities and farmer groups as an effort to improve the economy in the agro-industrial sector. However, there are obstacles in the distribution process activities carried out by the XYZ agency such as the lack of harmonization of information exchange with regional posts. This causes the distribution process to be hampered and also not even distributed. Therefore, it is necessary to describe the process flow using the Supply Chain Management (SCM) method to manage seeds distribution management appropriately. SCM elaborates each supply chain process in detail by categorizing each process with the attributes of plan, source, make, deliver, and return. In addition, performance measurement using the Supply Chain Operations Reference (SCOR) model is carried out to determine and provide recommendations for improvements needed for each related performance metric. There are 31 Key Performance Indicators (KPI) that are in accordance with the distribution process and validated in XYZ agency. The result of performance measurement based on the Key Performance Indicator reached 83.12, which indicated the performance monitoring of the actual seeds distribution process by XYZ agency at the Good level.

Instant Noodle Production Information System Using The Method Supply Chain Management To Overcome Targets Not Achieved

Improvement This research aims to analyze and implement an instant noodle production information system using the Supply Chain Management (SCM) method to overcome the inability to achieve predetermined production targets. In this study, an analysis was carried out on the entire supply chain in the production of instant noodles, which includes raw material suppliers, production processes, distribution and sales. The research method used is a qualitative method. The subjects of this study were instant noodle company employees. The results showed that the application of a production information system using the SCM method could help companies increase the efficiency of instant noodle production. With an integrated information system, companies can gain better visibility on consumer demand, raw material inventory, and production status. This allows companies to carry out more accurate production planning, accelerate production cycle times, and optimize resource use

Blockchain-based smart dairy supply chain: catching the momentum for digital transformation

PurposeThis research attempted to establish the underlying dimensions of supply chain management practices, blockchain technology and supply chain performance in the Indian dairy industry. Additionally, the study proposes a conceptual model that shows the mediating effects of blockchain technology in the relationship between supply chain management practices and supply chain performance.Design/methodology/approachStructural equation modelling (SEM) is incorporated to examine the proposed model using SPSS and AMOS version 24. The study population includes 119 registered Indian dairy processing units operating in Uttar Pradesh and New Delhi (source: Dairy – India). Individual registered dairy processing unit's top four executives, that is Head of the Dairy Processing Plant, Supply Chain head and Marketing Head, and IT head are chosen as the respondents of the study, which renders the sample size of 476. Judgmental sampling based on the organisation's market position and plant production capacity (i.e. one lakh litre per day) has been set as the benchmark for selecting the dairy processing units. The executives are selected as respondents as they are well-versed in the phenomenon of supply chain management practices, blockchain technology and supply chain performance compared to other staff working in the dairy industry. The data was collected from December 2021 to March 2022 through judgmental sampling. The target sample size was 476, but only 286 questionnaires were received in a completed state and were further used for analysis.FindingsManufacturing practices, information sharing, distribution management, inventory management and blockchain technology have a significant and positive impact on supply chain performance in the Indian dairy industry. Furthermore, the research demonstrates that blockchain technology partially mediates the relationship between supply chain management practices and supply chain performance in the context of the Indian dairy industry.Research limitations/implicationsThis research is focused on the Indian dairy industry operating in only two states, namely New Delhi and Uttar Pradesh. More research is needed to determine whether SCM practices and the prospects for blockchain technology among channel members are universally applicable to merchants in non-dairy products. Similar investigations should be carried out on dairy industry operating in various formats and in numerous geographic locations. Further, case studies can be conducted by future researchers to learn how supply chain management methods are deployed, what precisely these practices entail and what costs and time demands are required by these practices in context of small independent retailers across different germane expanse.Originality/valueWhile the available literature on the research area is spread out, the influence of blockchain technology in the Indian dairy industry has not yet been sufficiently analysed. Therefore, the research article focused on exploring underlying dimensions of the constructs of supply chain management practices, blockchain technology adoption and supply chain performance in the context of the Indian dairy industry.

A review on the melt extrusion-based fused deposition modeling (FDM): background, materials, process parameters and military applications

AbstractThe contemporary military sector needs a tailor-made product at a low cost and time. Fused Deposition Modeling (FDM) is a melt extrusion-based Additive Manufacturing technology for processing thermoplastics, composites, and biomaterials. FDM is competent in fabricating complex parts in different industries, including military, aerospace, automotive, biomedical, and jewellery. The FDM can process various materials and is ideal for fabrication prototypes, functional parts, visualization, concept proofs and fast product development. FDM is currently used in the military for novel components developments and maintenance, opening new logistics and supply chain management methods. Integrating sensors into weaponry for real-time physiological feedback and threat information is also possible. Additionally, FDM can fabricate trauma models for surgical planning and educating military surgeons. This paper presents the FDM background, filaments, and process parameters. Also, the work provides information to readers on the applications and possibilities of the FDM process from a military standpoint.

The Changing Landscape of Supply Chain Management in India: An Analytical Study of Implications for Competitiveness

The supply chain management landscape in India has changed dramatically in recent years. With India's rise as a key participant in the global economy, supply chain management has become an essential component of the country's competitiveness. This analytical research investigates the consequences of evolving supply chain management methods for India's competitiveness. The research focuses on the changing landscape's problems and possibilities, such as the advent of e-commerce, the development of new technologies, and the shift towards sustainability. The report highlights important elements that are expected to define the future of supply chain management in India using both primary and secondary data and gives advice for organisations wishing to increase their competitiveness in the Indian market.