Aspects Of Supply Chain Management Research Articles

Framework for E-commerce Warehouse Site Selection Evaluation: The Impact of Consumer Repurchase Intention

Supply chains play a decisive role in the development of e-commerce. Although site selection problem for e-commerce warehouses is an important aspect of supply chain management, this topic has received insufficient research attention. This paper fills this research gap by proposing an evaluation framework for the e-commerce warehouse site selection. This framework incorporates consumer repurchase intention (CRI) as a key factor in the evaluation to analyze its impact. This study also employs the matter-element evaluation model to classify the levels of alternatives, and then adopts the probabilistic linguistic terms set to optimize the research results. The feasibility and effectiveness of the proposed evaluation framework is validated through a case study of e-commerce warehouse site selection in China. The results of the case study demonstrate the performance of the proposed framework and highlight the significant impact of CRI on the evaluation outcomes. The proposed framework makes full use of the evaluation information and significantly improves the differences between adjacent alternatives, which can enhance the credibility and accuracy of decision results to provide a more reliable alternative ranking for decision makers.

Utilizing predictive analytics to enhance supply chain efficiency and reduce operational costs

This study investigates the application of predictive analytics to enhance supply chain efficiency and reduce operational costs. The primary objective is to understand how predictive analytics can be leveraged to optimize various aspects of supply chain management, including demand forecasting, inventory management, and logistics. The research methodology involved a comprehensive literature review, coupled with a case study analysis of several organizations that have successfully implemented predictive analytics in their supply chain operations. Key findings reveal that predictive analytics significantly improves demand forecasting accuracy, which in turn optimizes inventory levels, reduces stockouts and overstock situations, and enhances overall supply chain responsiveness. Additionally, predictive analytics helps in identifying potential disruptions in the supply chain, allowing for proactive measures to mitigate risks and maintain continuity. The study also highlights the cost benefits, where organizations reported a notable reduction in operational costs due to improved efficiency and better resource allocation. The conclusions drawn emphasize the transformative potential of predictive analytics in supply chain management, suggesting that its strategic implementation can lead to substantial improvements in efficiency and cost savings. This research underscores the need for organizations to invest in advanced analytics tools and skills to fully harness the benefits of predictive analytics in their supply chain operations.

Technology as a solution to the supply chain problems in the United States: What more can be done?

The study examined the critical role of technology in addressing supply chain challenges in the United States, with a focus on identifying gaps and exploring opportunities for improvement. Through a comprehensive analysis of existing literature and empirical studies, the research uncovered key supply chain challenges faced by firms in the U.S., including issues related to counterfeit goods, logistics inefficiencies, environmental concerns, inaccurate demand forecasting, and cyber-security threats. Also, the study examined the role of emerging technologies such as blockchain, artificial intelligence, Internet of Things, big data analytics, and machine learning in enhancing supply chain resilience and agility. This study highlighted the contributions of these technologies in promoting transparency, traceability, sustainability, and efficiency across various aspects of supply chain management. By synthesizing insights from diverse sources and datasets, the study provided valuable recommendations and strategies for leveraging technology to address supply chain challenges effectively. These recommendations covers areas such as investment in advanced technologies, collaborative data sharing platforms, integration of sustainability metrics, predictive analytics for risk management, and supply chain resilience planning.

Evaluating the Impact of ERP Implementation on Supply Chain Performance: A Case Study of Youngs Food in Pakistan

This study investigated the impact of Enterprise Resource Planning (ERP) implementation on supply chain performance at Youngs Food, a leading FMCG company in Pakistan. Utilizing a quantitative research methodology, the study aimed to assess how ERP systems influence various aspects of supply chain management, including process automation, lead time reduction, cost reduction, and delivery improvement. Data were collected from employees involved in the ERP transformation process through a structured questionnaire. The findings revealed that ERP implementation significantly enhances supply chain performance. Specifically, process automation emerged as the most influential factor, followed by cost reduction, improved deliveries, and lead time reduction. The study confirmed that ERP systems streamline operations, reduce operational costs, and improve efficiency and customer satisfaction. The comprehensive analysis underscores the critical role of ERP systems in modern supply chain management, advocating for their strategic adoption to achieve competitive advantage and operational excellence.

Routing and facility location optimization in a dairy products supply chain

Routing and facility location optimization is an important aspect of supply chain management. This is because the problem of determining which facilities within a supply chain echelon should cost-effectively supply products to facilities in the next echelon is usually encountered by supply chain managers and analysts. In this paper, a linear programming model for supply chain routing and facility location optimization has been proposed. The model can be solved using the PuLP optimization library implemented in Python programming language. The model has been applied to a small dairy products supply chain to determine the most cost-effective routes for products in the supply chain. The optimization results proffered the optimal contribution of each factory warehouse to each distribution warehouse in order to satisfy distribution warehouse demand while minimizing costs. The results of the study indicated that the model is efficient in solving the routing and facility location optimization problem usually encountered in supply chain management. Therefore, this study will aid supply chain analysts and managers in determining the most cost-effective route for distributing products between echelons or stages of supply chains under study.

Importance of Packaging in Supply Chain Management

Establishment of efficient linkages and making a strong and transparent supply chain is the essence of modern day manufacturing. The inventory costs and transportation costs constitute a large proportion of the overall costs. In a competitive world efficiency of manufacturing would be to reduce the cost of manufacturing to increase profit rather than increase selling price to increase the profit. It is true that customer would be displeased with a product in case it is damaged or tampered. So for reduced inventory, transportation cost and safety and security of the product transported packaging is an important aspect. With the emphasis on Green supply chain efforts are being made to reduce the dependency on packaging materials, more so an effort to go in for reusable packaging materials. The proposed research work has the aim of analyzing the importance of packaging in supply chain management. Review of literature indicates that the aspect of packaging is crucial in the field of supply chain management. Studies carried out on the financial aspects of supply chain management have brought out factors such as lack of attention given to packaging of products. A descriptive research methodology is adopted. In the past such a correlation has not been attempted realistically, thus it was found that a study would be enriching, useful and interesting. The findings will give an insight on to the relevance of practicable methods to undertake innovation in the field of packaging not only at the industry level but also at global operations level and may serve as input in improving profitability, ensuring efficiency in business methods and support further research on the subject.

A Preliminary Study of Role and Challenges of IOT in Supply Chain Management

Abstract: This paper delves into research on the Internet of Things (IoT) within the context of supply chain management (SCM). It comprehensively addresses the definition of IoT, key technology enablers, various SCM processes, and applications. The Internet of Things has the potential to address limitations in certain aspects of SCM, such as monitoring, production management, logistics operations efficiency, information exchange and communication, supply chain modeling, intelligent information collection, and security. The advent of IoT technology has ushered in a new era in logistics. The paper examines the current application areas and future prospects of this technology. Challenges encountered in implementation underscore the need for further refinement of IoT technology. Despite these obstacles, experts contend that the crux lies not in issues of costs, standards, and techniques, but in the establishment of a viable business model in the SCM and logistics industries.

Enhancing Sales Demand Prediction for Supply Chain Management: A Dimensionality Reduction Approach at Mukwano Company Limited, Uganda

In the dynamic landscape of today's business environment, the accurate prediction of sales demand plays a pivotal role for companies striving to maintain competitiveness. This study focuses on refining demand sales prediction for supply chain management at Mukwano Industries Limited through the application of dimensionality reduction techniques. The research involved a systematic iterative process encompassing problem identification, data preparation, modeling, evaluation, validation, optimization, and documentation. To ensure confidentiality, secondary data from the Mukwano IT department underwent meticulous merging and anonymization. Four dimensionality reduction algorithms, namely PCA, SVD, MDS, and t-SNE, were employed and evaluated using RMSE metrics. The results reveal that MDS and t-SNE exhibited exceptional performance, achieving accuracies of 89% and 88.8%, respectively. PCA and SVD also demonstrated commendable performance with an accuracy of 82.4%. The study underscores the crucial role of dimensionality reduction in enhancing predictive accuracy and optimizing inventory management. Recommendations include the incorporation of feature selection and regularization techniques to address the challenges associated with the curse of dimensionality. In conclusion, this research contributes valuable insights into the effectiveness of diverse dimensionality reduction techniques for demand prediction and inventory management. Additionally, the study highlights the need to address the curse of dimensionality and suggests exploring further research avenues in other aspects of supply chain management. These recommendations are essential for guiding future research efforts in this evolving field. Keywords: Demand sales prediction, Supply chain management, Feature selection, Inventory management, Predictive accuracy

A Lagrangian heuristic for integrated production planning, material ordering and investment multi-project scheduling in a project-driven supply chain

Effective decision making in large project planning presents a significant challenge. Despite progress in developing mathematical models, few studies comprehensively address project and supply-chain management aspects in an integrated framework. This article presents an integrated approach for multi-project resource investment, material ordering and production planning in a project-driven supply chain. A mixed-integer programming model is developed to optimize the total cost of renewable resource investment, production, transportation, and material ordering and holding, with an opportunity to share mobile renewable resources across multiple projects. A Lagrangian relaxation heuristic algorithm is proposed to determine the upper and lower bounds for the objective function, with an additional set of valid cuts to reduce the distance between bounds. The results of numerical experiments demonstrate the favourable performance of the proposed algorithm compared to the GAMS solver. This article provides insights into supply-chain participant expenses and activity scheduling based on these findings.

Domestic retailing, supply chain management, and the rise of fresh food supermarkets in China

This study investigates the emergence of fresh food supermarkets and explores domestic retailers’ fresh food supply chain management in China. The study explores two aspects of supply chain management: procurement and logistics. In line with prior research, the results suggest that domestic retailers’ continuous dominance over international retailers stems from their development of supply chain management. This study demonstrates that endogenous creativity fostered the emergence of fresh food supermarkets. Additionally, it underscores the importance of focusing beyond the transplantation route and Western impact when studying supermarkets in less developed countries.

User Experience on a New Medical Supplies Management Information System at The National Hospital of Sri Lanka

Introduction: The new Medical Supplies Management Information System (MSMIS), an e-based logistics management system was implemented in 2023 by the Medical Supplies Division of the Ministry of Health, Sri Lanka to effectively manage medical supplies among state healthcare institutions across the island. The new system replaced the previous MSMIS to incorporate wider aspects of supply chain management on par with the changing environment. Methods: It was a mixed-method descriptive study conducted at the National Hospital of Sri Lanka (NHSL) in 2023. A survey was done with the help of a tailor-made tool (5-point Likert scale) among all the users of MSMIS at NHSL. Key information interviews and observational visits were done to complement the quantitative findings. Objective: The study aimed to evaluate the experiences of users in the new MSMIS by comparing it with the previous one at the NHSL. Results: More than 60% of respondents (n=21) were found to have negative or highly negative experiences with all ten components of the system evaluated. The composite mean score of overall experience was 2.17(SD=0.56). The qualitative data fortified the findings of the quantitative data. Conclusion: The majority of MSMIS users at the NHSL had a negative experience with the new MSMIS in comparison with the previous system. Recommendation: It is recommended for similar studies on a larger scale (regional/national) to produce findings with fewer concerns for validity and reliability.

Perancangan Sistem Informasi Pengendalian Intern Persediaan Barang Dagang Dengan Metode Reorder Point(Rop)


 This research discusses the development and implementation of a Reorder Point (ROP) information system in the context of inventory management. ROP is a critical method for optimizing merchandise inventory, avoiding stock shortages, and minimizing inventory costs. The aim of this research is to design and implement an information system that allows companies to calculate and monitor ROP efficiently. The research methodology includes user needs analysis, software development, and system testing in real environments. The research results show that the ROP information system can help companies improve inventory control accuracy, reduce costs, and improve customer service. This research also identifies challenges in implementing ROP information systems and provides insight into how to overcome these obstacles. In an era of competitive business, the ability to respond quickly to changes in demand and delivery is the key to success. A sophisticated Reorder Point information system gives companies a competitive advantage by optimizing inventory levels and avoiding excess or shortage of stock that can be detrimental to the company. Additionally, by integrating data from various aspects of supply chain management, the system provides better visibility into company operations, enabling more timely decisions and accurate information. Therefore, the results of this study indicate that the ROP information system is a valuable asset in efficient inventory management and helps companies to remain relevant and sustainable in a dynamic business environment. In conclusion, ROP information systems are a valuable tool in efficient inventory management and contribute to the success of a company's supply chain.

Role of Supply Chain Management in Quality of Healthcare Services

Healthcare organizations in Haryana (Kurukshetra) face many supply chain management challenges that can be addressed through effective operational and management decisions. The aim of this paper is to examine the supply chain management of healthcare quality in developing countries, particularly in rural healthcare in Haryana (Kurukshetra), and to consider demographic variables such as gender, age, education level and healthcare experience. Design and Hypothesis Testing Approach Distributed 500 questionnaires to determine the impact of aspects of supply chain management on the quality of health services. 27 of his seven procurement officers and administrative staff in Kurukshetra Haryana. The primary method was to collect data from 73 rural health managers and procurement managers to identify the quality and size of health services. The results of our study show that a combination of timely delivery of health products, specifications, level of health product providers and safety in the rural health sector of Haryana (Kurukshetra) is related to the quality of health services. The scope of this article focuses on employing appropriate human resources and highly trained professionals in supply chain departments to improve the quality of health services in the supply chain. As a practical contribution, this article can help healthcare supply chain managers and organizations do their jobs better or create a competitive advantage by addressing the issues and challenges facing individual healthcare managers, organizations and their partners.

Theoretical and methodological foundations of business process management of a modern enterprise based on the «lean production management» approach

Business process management is an important aspect of supply chain management. Effective management of business processes by supply chains makes it possible to increase operational activity, reduce transportation and storage costs, increase the level of service for the end customer, as well as increase competitiveness in the market. The ability to effectively manage business processes is provided by the lean production management model. This scientific article discusses the theoretical and methodological foundations of business process management in logistics based on the lean production management approach. The article describes the concept of a business process, the essence and main characteristics of business processes, the concept of lean manufacturing, tools and the formation of a business process management system. Special attention is also paid to the business process improvement model. The purpose of the article is to study the relevance of this study, the research methods used, as well as its results and conclusions. In conclusion the article highlights the importance of logistics business process management and the potential benefits of lean manufacturing as a methodology for enterprise development, such as creating value for customers, reducing costs, reducing waste, improving working conditions, increasing competitiveness and developing innovation.

LOGISTICS PERFORMANCE FOR PRACTICE IN THE FMCG INDUSTRY THROUGH A SUPPLY CHAIN MANAGEMENT APPROACH

Business competition that is getting tougher in the digitalization 5.0 era requires companies to further improve their business performance, especially in the aspect of supply chain management. Logistics, which is a critical process in supply chain management, needs to be made into an integrated system from upstream to downstream. Logistics activities which include distributing goods, managing warehousing, and managing consumer orders are of concern to the entire industry, including the FMCG industry. This study used a quantitative method using multiple regression analysis. The company used as a case study is a multinational FMCG company. Descriptive quantitative to describe a symptom, event, and incident that occurs when the attempt is made to photograph the events and incidents that are the center of attention of the researcher and then describe them as they are. This study focuses on logistics activities that become variables, namely transportation, handling and storage, and product availability. The results showed that transportation, handling and storage, and product availability. greatly affect the logistics performance of FMCG companies.

Roles of Blockchain Technology in Supply Chain Capability and Flexibility

Blockchain technology is a major innovation that has swept through global supply chains recently. Blockchain technology has received immense attention in the supply chain industry due to its promising capabilities. This study was conducted to evaluate the potential capabilities of blockchain technology, which are highly relevant to the supply chain industry. To improve the understanding of the effect of blockchain on the supply chain, this research focuses on two crucial aspects of supply chain management, namely, supply chain capabilities and flexibility. The research procures measuring items for blockchain characteristics, supply chain capabilities, and flexibility through a questionnaire, the previous literature, and interviews conducted with industry experts. Through the use of statistical analysis, this study identifies the relationship between the above variables. The effect of blockchain on each variable is examined using a simple linear regression model. The findings disclose that blockchain technology has generated a notable impact on the supply chain capabilities and supply chain flexibility of firms. This makes blockchain technology highly essential for firms to generate a competitive advantage in the market and develop a new set of capabilities ahead of their competitors.

ІМПАКТ-ІНВЕСТУВАННЯ ЯК СУЧАСНИЙ КОНЦЕПТ СТАЛОГО РОЗВИТКУ ЛОГІСТИЧНИХ СИСТЕМ

The article analyzes the principles of impact investing in the sustainable development of logistics systems, considers trends in logistics provision in the context of the sustainable development paradigm, and identifies the prerequisites, driving forces, and opportunities for ensuringthe sustainability of logistics systems at all levels. In addition, potential trends in their future development was analyzed. The sustaina-bility of a logistics system involves the efficient use of resources, cost reduction and process optimization. The author proposes a conceptual model of sustainable development of a logistics system. It con-tains two contours (strategic development contour and sustainable development contour). These con-tours in their interaction within the logistics system ensure its sustainable development in the long term. The basis is the sustainable development paradigm, and the main goal of the concept is to solve logistics problems not only in the interestsof the current needs of the economy, but also taking into account the right to meet the needs of future generations.The concept of "sustainable development of a logistics system" means the integration of sustain-able practices and principles into the operations and management of logistics systems. This involves balancing the economic, environmental and social aspects of supply chain management to ensure long-term viability and minimize the negative impact on the environment and society. It has been found that a sustainable logistics system should be aimed at reducing environmental impact through the use of environmentally friendly vehicles, energy-efficient technologies, waste man-agement, and reduction of greenhouse gas emissions. Another important aspect is the use of environ-mentally friendly packaging and materials. Consideration of social aspects, such as occupational safety, quality of life of employees, respect for human rights and ethical standards. To achieve these goals, it is important to develop socially responsible labor practices. Aspects of sustainable development require new approaches to the investment processes of logis-tics systems, such as impact investing. The article defines the criteria for impact investing and the di-rections for determining the effectiveness and efficiency of this type of investment, taking into account the specifics of the investment object. When evaluating impact investments in the logistics sector, the authors propose to take into account the following criteria: placeand importance of the logistics system in the supply chain or national economy; resilience of the type of logistics provision to economic down-turn and peculiarities of the system's functioning during stagnation (which allows assessing risks); social significance of the logistics system; provision of the logistics system with its own financial re-sources; level of support for the development of the industry and the degree of control by the State

Intelligent Decision Support Machine Learning Based Optimizing Inventory Management

Inventory management (InvM) is a critical aspect of supply chain management (SCM) and optimizing inventory levels can lead to significant cost savings and improved customer satisfaction. Hence, business organizations have recently worked to increase the value of their operations by utilizing modern and digital technologies as industry 4.0 (Ind 4.0). In the era of Ind 4.0, the technologies as Internet of Every Things (IoET), AI, BDA…etc. Recognizing the significance of InvM in a supply chain (SC), motivated us to volunteer technologies of Ind 4.0 as machine learning (ML) techniques to boosting Decision Making (DM) process to optimize InvM. Subsequently, this study is constructed for providing an intelligent Decision Support ML framework for automating the process of optimizing inventory management. Our constructed framework ensembles powerful ML prediction algorithms for inventory management, such as Artificial Neural Networks (ANNs), Random Forest (RF), and Support Vector Machine (SVM) for building robust sales regressors. The extensive experimentations on a case study of Walmart suggested that the proposed system has the potential to transform inventory management and improve supply chain performance, but further research is needed to address the challenges of data availability and quality.

Research on multi-factory combination optimization based on DOSTAR

With the development of industrial big data, it has become an important research direction to use combinatorial optimization to coordinate multi-objective problems in complex manufacturing scenarios with multiple factories. At present, most of the multi-objective problems are decomposed into single-objective solutions. However, it is difficult to resolve the contradiction between multiple goals. There are many participants in multi-objective problems and complex data types, so there is no suitable research method at present. Based on big data, this paper integrates various aspects of supply chain management of multiple factories, and proposes a DOSTAR combined model. On the one hand, it conducts knowledge discovery based on the fusion of human-cyber-physical ternary data, on the other hand, it conducts multi-objective optimization through knowledge structure. Among them, the most important thing is to establish the six-tuple as the basic model. Then the space weight, time weight and decision weight are obtained through the weight sub-model. Finally, the improved reinforcement learning algorithm is used to extract relevant new knowledge and complete multi-objective coordination. This article takes the supply chain management of Haier water heaters as an example, using the above-mentioned combined model, and the experimental results show that the purpose of improving performance has been achieved. • This article builds a combined optimization model based on knowledge discovery and reinforcement learning. • The combined model mainly includes: six tuples, weight sub-models (AHP and spatiotemporal data), and improved reinforcement learning algorithms. • This research solves the multi-objective optimization problem in the complex manufacturing environment of multi-factories.

Covid-19 Pandemic: Is it a Challenge or Opportunity for Pharmaceutical Industry around the Globe?

In this opinion article, authors emphasized the role of pharmaceutical industries or organizations, the way forward to deal efficiently with pandemics such as covid-19 and various aspects of supply chain management are discussed so as to reach the vaccine to the last end user.