Supply Chain Management Model Research Articles

QAmplifyNet: pushing the boundaries of supply chain backorder prediction using interpretable hybrid quantum-classical neural network

Supply chain management relies on accurate backorder prediction for optimizing inventory control, reducing costs, and enhancing customer satisfaction. Traditional machine-learning models struggle with large-scale datasets and complex relationships. This research introduces a novel methodological framework for supply chain backorder prediction, addressing the challenge of collecting large real-world datasets with 90% accuracy. Our proposed model demonstrates remarkable accuracy in predicting backorders on short and imbalanced datasets. We capture intricate patterns and dependencies by leveraging quantum-inspired techniques within the quantum-classical neural network QAmplifyNet. Experimental evaluations on a benchmark dataset establish QAmplifyNet’s superiority over eight classical models, three classically stacked quantum ensembles, five quantum neural networks, and a deep reinforcement learning model. Its ability to handle short, imbalanced datasets makes it ideal for supply chain management. We evaluate seven preprocessing techniques, selecting the best one based on logistic regression’s performance on each preprocessed dataset. The model’s interpretability is enhanced using Explainable artificial intelligence techniques. Practical implications include improved inventory control, reduced backorders, and enhanced operational efficiency. QAmplifyNet also achieved the highest F1-score of 94% for predicting “Not Backorder” and 75% for predicting “backorder,” outperforming all other models. It also exhibited the highest AUC-ROC score of 79.85%, further validating its superior predictive capabilities. QAmplifyNet seamlessly integrates into real-world supply chain management systems, empowering proactive decision-making and efficient resource allocation. Future work involves exploring additional quantum-inspired techniques, expanding the dataset, and investigating other supply chain applications. This research unlocks the potential of quantum computing in supply chain optimization and paves the way for further exploration of quantum-inspired machine learning models in supply chain management. Our framework and QAmplifyNet model offer a breakthrough approach to supply chain backorder prediction, offering superior performance and opening new avenues for leveraging quantum-inspired techniques in supply chain management.

Empirical Evidence of Customers-driven Halal Supply Chain Management Model from The Quranic Verse

Halal and tayyib signify the foundations of research in the Halal Supply Chain (HSC). This study aims to illuminate the consumer-driven aspects of the HSC and introduce the term “Ajka” in The Noble Quran. A systematic literature review (SLR) of 46 HSC literature pieces from 2017 to 2022 reveals trends and research gaps in halal supply chain management (HSCM). The study followed inductive reasoning to explore The Noble Quran 18:19 and modeled the HSC. Content and thematic analysis were performed using the ATLAS.ti qualitative data analysis software. While most HSCM literature has focused on the concepts of halal, tayyib, and khabith, this research has incorporated the selected Quranic verse, revealing HSC variables with a downstream focus: Patron, Price (halal), Product (Ajka), and Place (Al Madinah). A significant number of consumers who are aware, involved, and engaged with halal norms connected to retail points can contribute to the sustainability of the HSC.

A Green Supply Chain Management Strategy for E-Commerce Based on Multiple Blockchain Technology

Abstract In this paper, firstly, the e-commerce green supply chain management strategy of multivariate blockchain is explored, and digital assets are traded on the e-commerce supply chain platform through the information anchoring model. Secondly, the Diffie-Hellman algorithm is used to generate the key, the AES algorithm is used to encrypt the information, and the account data, transaction data and IoT data, are stored in three independent chains. Finally, the selection strategies of different e-commerce sales models and the green supply chain management strategies of e-commerce platforms are visually analyzed through numerical arithmetic examples. The results show that when E 0 = 10, it is optimized by the ecological R&D efforts of supply chain members. When E 0 = 50, the greenness of the product is decreasing. When it finally tends to the steady state, E ∞ C > E ∞ BR > E ∞ MR. The three green supply chain management models proposed in this study are conducive to enhancing consumer utility and in line with the sustainable development strategy.

Optimization of logistics supply chain management model on consumer purchase anxiety disorder

BackgroundAnxiety refers to the intense, excessive, and persistent anxiety and fear in daily life, which will peak in a few minutes. Especially in online shopping, patients with anxiety will aggravate their anxiety because of the slow delivery of the traditional logistics supply chain management model. To reduce consumers’ anxiety, the network distribution system of logistics supply chain management mode is optimized.Subjects and MethodsThis study divided 200 patients with anxiety disorder in a city into a control group and an experimental group. In the experimental group, 100 patients used the optimized logistics supply chain management mode for online shopping. In contrast, in the control group, 100 patients used the traditional logistics supply chain management mode for online shopping. The study also used the self-rating anxiety scale (SAS) for psychological measurement and compared the SAS scores of the two groups of consumers for two months.ResultsThe data were analyzed by SPSS23.0. The SAS score of the experimental group was (1.63±0.23), and that of the control group was (1.81±0.59). The SAS scores of patients in the experimental group were better than those in the control group, and there were apparent differences between the two groups (P < 0.05).ConclusionsResearch on the choice of logistics supply chain management mode for online shopping optimizing its network distribution system can effectively shorten the online shopping distribution time and reduce consumers’ purchase anxiety.

Hunger games search optimization with deep learning model for sustainable supply chain management

The supply chain network is one of the most important areas of focus in the majority of business circumstances. Blockchain technology is a feasible choice for secure information sharing in a supply chain network. Despite the fact that maintaining security at all levels of the blockchain is difficult, cryptographic methods are commonly used in existing works. Effective supply chain management (SCM) offers various benefits to organizations, such as enhanced customer satisfaction, increased operational efficiency, competitive advantage, and cost reduction. Potential SCM for agricultural and food supply chains needs distributors, coordination and collaboration among farmers, retailers, and stakeholders. The use of technology like Block Chain (BC), sensors, and data analytics, can boost traceability and visibility, decrease waste, and ensure safety and quality throughout the supply chain. Therefore, this study develops a Hunger Games Search Optimization with Deep Learning Model for Sustainable agricultural and food Supply Chain Management (HGSODL-ASCM) technique. The fundamental goal of the HGSODL-ASCM technique is to improve decision-making processes for agricultural and food commodity production and storage in order to optimise revenue. In the provided HGSODL-ASCM technique, a bidirectional long short-term memory (Bi-LSTM) model is built to determine the amount of productivity and storage required to maximise profit. In order to boost the performance of the Bi-LSTM classification process, the HGSO algorithm has been utilized in this work. The presented HGSODL-ASCM technique can independently achieve the SCM policies via interaction with complicated and adaptive environments. A brief set of simulations were performed to ensure the improved performance of the HGSODL-ASCM technique. The simulation results demonstrated how superior the HGSODL-ASCM method is to other methods already in use.

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.

OPTIMIZATION OF THE SUPPLY CHAIN IN COMMERCIAL LOGISTICS: IMPACT ON EFFICIENCY AND PROFITABILITY

In modern conditions, when the activities of companies are constantly influenced by external factors, the efforts of top management are mainly aimed at the maximum optimization of activities, as a basis for ensuring its efficiency and profitability. The article analyzes the prerequisites for updating the issue of supply chain optimization. The essence of the supply chain optimization category was studied, the problem areas with which it is connected were systematized in terms of such components as stocks, risks, demand, expectations. The phases of supply chain optimization, which include design, planning and execution stages, are developed and graphically presented. The need to track key indicators of the supply chain is established and the most informative of them are displayed, namely: picking and packing time, cash-to-cash time cycle, inventory turnover, gross return on investment, delivery timeliness indicator, delivery terms and reasons for returns. A parallel has been drawn between theoretical developments and the practice of their implementation on the device of Ukraine in the conditions of a pandemic and war. Measures that have a positive effect on the optimization of the supply chain using innovative warehouse and routing technologies have been identified. The criteria for optimizing the supply chain were studied. The methods used to optimize the supply chain in modern conditions are considered. Reference models of supply chain management were analyzed and their role in the process of optimization of such chains was determined. A parallel has been drawn between theoretical developments and the practice of their implementation on the device of Ukraine in the conditions of a pandemic and war. The measures that have a positive effect on the optimization of the supply chain, as well as the software that is used for these purposes and allows to significantly increase its efficiency, have been identified. Further prospects for exploration in the direction of research are outlined.

Trends and Recommendations for Enhancing Maturity Models in Supply Chain Management and Logistics

Maturity models (MMs) are strategic tools used to assess and improve the current state of processes, objects, or people, with the goal of achieving continuous performance enhancement. While MMs are applied in various fields, their scope, design, and application criteria within Supply Chain Management and Logistics (SCML) lack comprehensive studies. This article aims to address this gap through a systematic literature review. The review analyzes 137 relevant articles using both bibliometric and content analysis techniques. The bibliometric analysis identifies major contributions, popular journals, and the classification and evolution of key keywords. The content analysis focuses on critical criteria related to the scope, design, and application of MMs. The findings reveal a growing emphasis on models assessing Industry 4.0 readiness and sustainability principles. However, several gaps are identified, including limited attention to optimizing and integrating logistic processes, underutilized and unvalidated MMs, and the absence of comprehensive improvement guidelines. Based on these trends and research gaps, this study proposes five recommendations for future developments that benefit both academics and practitioners. These recommendations aim to address the identified limitations and provide guidance for comprehensive and effective improvement strategies.

A Comprehensive Review and Open Issues on Supply Chain Management Models

The goal of SCM is to apply decisions, which end up with optimal organizational performance. Supply chain (SC) exists in service, manufacturing, and business organizations. Managing the reliability of processes and products in multi-stakeholder SC surroundings is a major challenge nowadays. As it provides protected control and traceability, trust, and immutability establishment among stakeholders with less-expensive solutions, blockchain has recently emerged as a most essential mechanism. This study critically evaluates 65 papers that discuss BCT in SCM, more specifically, an analysis of several performance measurements that are included in various papers is carried out. Additionally, a thorough analysis of the highest performance levels and various technical elements used in each task is conducted. Finally, the survey is extended with the identification of various research challenges, which may help the analysts to support improved future works on BCT in SCM. Chronological analysis is also performed.

Circular fashion: evolving practices in a changing industry

Today we are witnessing a change in the production paradigm of the fashion industry. The negative impacts of different processes along the supply chain are evident and consumers have begun to shift to brands seeking effective organizational strategies and supply chain-management models that consider the safeguarding of the planet’s resources and demonstrate respect for people. Impelled by these developments, fashion brands are moving from market-driven to purpose-driven strategies. The fashion industry is now recognizing the circular economy (CE) as the leading entrepreneurial model for addressing supply-chain issues related to sustainability. However, there are still gaps in the levels of environmental, economic, social, and cultural sustainability being achieved. Implementation of this model on a large scale is still in the early stages and recent experience indicates a need to rethink the current linear system to enable different actors along the fashion-supply chain to adapt. Further, the fashion system lacks a holistic vision that can support and guide this sustainable transformation toward CE. This article describes how several companies are currently implementing circularity and presents evidence that an emphasis on this concept is relevant for the global fashion industry. It aims to show how emergent design practices are supporting fashion companies to better focus their sustainability agendas, to approach them in a holistic manner, and to consider all business processes with the goal of implementing sustainable development strategies. Analyzing contemporary design-driven best practices, the article introduces a taxonomy highlighting effective ongoing strategies (mini-loops) leading to incremental changes toward CE. Furthermore, it synthesizes possible future trajectories that could lead the fashion system to finally close the loop of circularity.

Cloud model for new energy vehicle supply chain management based on growth expectation

Cloud model for new energy vehicle supply chain management based on growth expectation

A customized multi-neighborhood search algorithm using the tabu list for a sustainable closed-loop supply chain network under uncertainty

Environmental pollution and social inequalities have prompted the agricultural industry to implement sustainable supply chain management practices. However, supply chain operations and planning in developing countries such as Iran are often not economically, environmentally, and socially sustainable. To address this challenge, this paper presents a practical optimization model for sustainable closed-loop supply chain (SCLSC) management in the agricultural industry of Iran, with a focus on the olive crop. Based on the triple bottom line concept, which considers economic, environmental, and social sustainability, the proposed model makes location, allocation, and inventory decisions under uncertainty by developing a scenario-based robust optimization model. To solve this complex network design problem, we propose a metaheuristic algorithm with a multi-neighborhood procedure that efficiently handles the complexity of the problem. Specifically, we develop a customized Simulated Annealing (SA) algorithm using a tabu list to improve the initial solution found by a constructive heuristic algorithm. Our extensive analysis and comparison of our metaheuristic algorithm against the exact solver and two other powerful metaheuristic algorithms demonstrate the applicability of our SCLSC model for the agricultural industry in Iran and the high performance of the proposed metaheuristic algorithm for solving large-scale networks.

Game model of transnational green supply chain management considering government subsidies

Game model of transnational green supply chain management considering government subsidies

Supply chain management analysis of avocado in south Sumatra province through the Food Supply Chain Network (FSCN) method

One of the agricultural sub-sectors that occupy a strategic position in agricultural development is the horticultural sub-sector, with one of its potential commodities being avocado. Avocado is one of the export-based commodities, especially in South OKU Regency, South Sumatra Province. This study aims to obtain an overview of the Avocado Agribusiness Supply Chain management in South OKU Regency. The study was conducted in Warkuk Selatan District, South OKU Regency in February 2022. The research method used was a qualitative descriptive method with a type of data using primary data and secondary data. The data analysis method uses the Food Supply Chain Network (FSCN) method, which illustrates South Oku Regency's avocado supply chain model. The results showed that the Avocado Management Supply Chain Management model with the FSCN framework consisted of four main components: the supply chain structure, the business chain process, supply chain management, and supply chain resources. Avocado supply chain targets are still dominated to meet the domestic market and products in the form of fresh avocados for consumption. Avocado supply chain management comprises election partners, contractual agreements, transaction systems, government support, and supply chain collaboration. The avocado supply chain structure in South OKU Regency consists of farmers, collecting traders, local and non-local traders, retailers, and consumers with respective roles in the supply chain structure. Business processes in avocado supply chain management consist of procurement, replenishment, and customer order cycles. Based on marketing margin analysis, the lowest total marketing margin is found in channel IV, with a margin value of Rp 1,500 per kg. The four avocado marketing channels in South Warkuk Ranau District have Farmer’s Share ≥40%, so it is categorized as an efficient channel.

Sickle effect: A hybrid model of product life cycle and supply chain management for achieving sustainable development

This paper gives a basic study of Sickle effect which is a new concept developed through combination of product life cycle (PLC) and supply chain management (SCM). Various studies were being done in the field of sustainable manufacturing (SM) majorly to design a product which can be environmentally sustainable. This present concept gives a basic idea of any product which goes through various stages of PLC and represents the amount of product that can be recycled.

Interrelationship Performance Indicators Model of Agile Supply Chain Management in Palm Oil Industry

This paper tries to model agile supply chain management performance indicators in the palm oil industry. The interpretative Structural Modeling (ISM) method is used to find the relationship between these indicators. The ISM stages begin with identifying indicators, compiling contextual relationships, compiling reachability matrices, compiling level partitions, compiling digraphs, and compiling ISM models. Then MICMAC analysis is used to group each of these indicators into four categories based on their driving power and dependence power. In this study, 16 hands of agile supply chain management in the palm oil industry were obtained, of which the four-level ISM model could be constructed. Two indicators are at level 4, six hands are at level 3, three indicators are at level 2, and five indicators are at level 1. Meanwhile, through MICMAC analysis, five indicators are found in the independent indicators category, six hands are in the linkage indicator category, four indicators are included in the dependent indicator category, and one indicator is in the autonomous indicator category. This research can be used by managers in the palm oil industry who want to increase agility in their supply chain. In general, indicators at level 4 can affect indicators at level 3, and so on. So that management can start fixing the indicators at level 4 first. In addition, indicators that have a driving power value in MICMAC analysis can be prioritized to improve their performance.

Supply Chain Management Model in Digital for Supervision Management in Cooperative Educationin the Universities

Supply chain management model in digital for supervision management in a cooperative education in the universities is composed of six elements namely main elements suppliers, manufacturer, Education customers, Consumers Satisfaction and Return. The objective of this research is to develop and to evaluate an appropriate about Supply chain management model in digital for supervision management in a cooperative education in the universities A sample consisted of ten experts in supply chain. Data analysis was the average mean and standard deviation. The results from ten experts agreement of about Supply chain management model in digital for supervision management in a cooperative education in the universities was a high level which means that model can develop digital for supervision management in a cooperative education.

Supply Chain Resources and Economic Security Based on Artificial Intelligence and Blockchain Multi-Channel Technology

With the rapid growth of social economy and the improvement of people's living standards, the logistics industry not only shows a trend of rapid development, but also faces various business risks. Therefore, supply chain management becomes particularly important. Strengthening supply chain management has become a general trend. The traditional cost-oriented supply chain management model has been unable to meet the requirements of modern enterprise development. Given that the changes in customer demand, production, and sales have not been considered, enterprise resources are easily wasted. How to build a new supply chain model driven by value and customer demand has become one of the problems that large enterprises must solve. The combination of artificial intelligence (AI) and blockchain technology (BT) can realize information sharing, risk sharing, data interaction, and other functions. Through smart contracts, the division of responsibilities among all roles in the supply chain is controlled, which makes the supply chain safer and more efficient. In this paper, the authors designed a new supply chain financial system model that can effectively reduce financial risks, improved the efficiency of capital use, and enhanced the competitiveness of enterprises. The authors compared the traditional supply chain management mode with the management mode under the combination of AI and BT. The supply chain resource and economic security management based on AI and blockchain multichannel technology was more efficient, the system security index was higher, and the internal employee satisfaction of the enterprise also increased by 5.98%. The simulation application system for the internet of things and edge computing has the characteristics of high real-time and scalability. By analyzing the differences between the internet of things and edge computing technologies in terms of device perception, communication mode, data processing, and processing performance, product manufacturing efficiency can be improved to a certain extent.

Optimal management of company procurement process from the perspective of supply chain

In order to solve the problem of the company's procurement process, the author proposes an optimization management from the perspective of supply chain. With the formation and development of the integration of the times, the company can be said to have both opportunities and challenges in the process of participating in market competition, if the company wants to continuously improve its competitiveness, it needs to strengthen the management of each link based on updating the management concept. In this process, the importance of procurement management has gradually become prominent, and based on the supply chain management model, the company needs to realize the optimization and transformation of the corresponding procurement process, reduce product costs with a systematic and complete procurement process, and improve its own economic benefits and competitiveness. The author conducts a comparative study on procurement methods and traditional procurement methods in the supply chain environment, the improved procurement process, and the effective path to enhance procurement capabilities lie in changing concepts, accelerate the development of informatization, improve the operating efficiency of workflow, the flow of funds, and better understand and meet customer needs.

An application of a smart production system to control deteriorated inventory

Deteriorating products require different handling procedures. Handling procedure includes prevention of the natural deterioration rate of the product. The production of deteriorating products requires prevention technology for those products to use for a long time. Overproduction of deteriorating types of products causes more trouble in preventing deterioration. This study uses a smart production system to control the production of deteriorating products. A controllable production rate controls the production of deteriorating products, and preservation technology reduces the deterioration rate of products. Preservation technology helps extend the life of products, but it requires a specific temperature-controlled environment to work at maximum efficiency. Transportation of these products uses refrigerated transportation to maintain the quality during the transportation time. The purpose of using all these features for deteriorating products is to reduce the deterioration rate, which helps to reduce waste generation from production. Besides, imperfect products from the production system pass through a remanufacturing process to support the waste reduction process. A sustainable supply chain management model under the above-stated strategies is described here. A classical optimization is used to find global optimum solution of the objective function. Then, the total cost of the supply chain is optimized using unique solutions of production rate, number of deliveries, delivery lot size, system reliability, and preservation investment. Global optimum solutions are established theoretically, and few propositions are developed. Some special cases, case studies, and a comparison graph are provided to validate the results. The beta distribution provides the minimum total cost of the system than uniform, gamma, triangular, and double triangular distribution. Smart production allows 72% system reliability with a negligible amount of imperfect products. Besides, the proposed policy gain 22.72% more profit than exiting literature. The model is more realistic through convex 3D graphs, sensitivity analyses, and managerial insights.