Traditional Supply Research Articles

Sustainable supply chain management in U.S. healthcare: Strategies for reducing environmental impact without compromising access

The U.S. healthcare sector’s supply chain operations are responsible for about 8.5% of all national greenhouse gas (GHG) emissions. In healthcare, traditional supply chain management has focused on cost efficiency to the detriment of environmental considerations leading to higher emissions, waste, and resource depletion. The focus of this study is to investigate strategies for making sustainable supply chain management (SSCM) in the U.S. healthcare system, while reducing environmental impact at minimal cost to patient care quality. The objectives of the study are to evaluate the current state of healthcare supply chains, explore sustainable practices, evaluate emerging technologies, propose an SSCM implementation framework, and explore policy implications. Sustainable supply chain management can be achieved by forming the key strategies: comprehensive waste reduction and recycling programs, adoption of energy efficient transportation and storage solutions, green energy sourcing, and use of data driven inventory management that would help optimize inventory, along with other technologies like blockchain, IoT and artificial intelligence that could achieve transparency and efficiency. The research wouldn't go into specific case studies but would likely look at institutions that have already been able to implement these practices. The findings indicate that considerable environmental footprint reduction of the U.S. healthcare sector is possible without sacrificing access to high quality care through adoption of SSCM practices. But it requires joint efforts from policymakers, healthcare providers and industry partners. The long-term goal is a sustainable, resilient healthcare system that will integrate environmental stewardship with high quality care, that will help mitigate climate change and acknowledge the interdependence of environmental and human health.

Blockchain-Enabled Supply Chain Finance: A Bibliometric Review and Research Agenda

The COVID-19 pandemic has revealed weaknesses in traditional supply chain finance systems, highlighting the need for digital change. Blockchain technology, with its ability to create secure and transparent records of transactions, offers a potential solution. This study uses bibliometric analysis and a literature review to examine research on blockchain-enabled supply chain finance, drawing on a database of 446 articles from ScienceDirect and Scopus. The findings show a growing interest in how blockchain can improve transparency, efficiency, and security in supply chain finance, addressing challenges like information asymmetry. This study suggests future research should focus on real-world applications of blockchain, how it can be used with other technologies, regulations and governance, and the social and environmental impacts of blockchain-based supply chain finance. This research also highlights the different priorities of the Global North and South in blockchain-enabled supply chain finance. The North focuses on efficiency and traceability, while the South emphasizes adding value and transparency. A lack of research on fair pricing, especially in the Global South, points to a critical gap that future research needs to address to ensure fairness in global trade.

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 offshore parcel delivery efficiency through vessel-unmanned aerial vehicle collaborative routing

Offshore oil and gas production is vital for global energy supply, but it faces logistical challenges due to the high costs and inefficiencies of traditional supply methods. This paper introduces the vessel-unmanned aerial vehicle (UAV) routing problem with multiple visits in a single flight (VURP-M), a novel logistical model that addresses aimed at enhancing the replenishment of offshore platforms with small, essential items. The VURP-M allows the UAV to perform multiple visits during a single flight, optimising the delivery process. To tackle the VURP-M, we propose two mixed-integer second-order cone programs that capture the problem's complexities. Given its NP-hard nature, we employ an adaptive large neighbourhood search (ALNS) method, featuring a segmented initialisation process and problem-specific operators guided by a rule-based mechanism to improve solution efficiency. The ALNS formulates an initial solution by solving a travelling salesman problem to create a giant tour, which is then used to group sequential targets into multiple UAV flights. The subsequent optimal resolution of a SOCP determines the take-off and landing points for each flight. Subsequently, the ALNS refines the initial solution through destroy and repair operators, enhancing the search for superior sequences and allocation schemes. The effectiveness of our approach is demonstrated through a real-world case study and numerical experiments on random instances featuring up to 100 platforms. The results offer implications of the collaborative vessel-UAV model for the offshore logistics industry.

Transforming agri-food value chains in Bangladesh: A practical application of blockchain for traceability and fair pricing

The agricultural sector is a vital component of Bangladesh's economy, but its agri-food supply chain faces signifi-cant inefficiencies primarily due to the involvement of numerous intermediaries. This complexity not only reduces the profits for farmers but also affects the overall transparency and efficiency of the supply chain. This study aims to em-ploy blockchain technology to transform the traditional agri-food supply chain in Bangladesh, focusing on increasing transparency, enhancing efficiency, and improving profitability for farmers, thus potentially bolstering the entire agri-food ecosystem in the country. The research involves setting up a blockchain-based smart contract on the Ethereum Blockchain network. This approach guarantees that all transactions within the agri-food supply chain are transparent, traceable, and accountable. Additionally, the study develops a web application to facilitate user interaction with the smart contract, enhancing accessibility and usability. Performance analysis and testing of the implemented smart con-tract demonstrate its capability to handle a significant volume of transactions without compromising on performance. The solution effectively reduces the dependency on intermediaries, thereby increasing the profit margins for the farm-ers involved. The integration of blockchain technology in the agri-food supply chain has shown promising results in enhancing transparency and efficiency. It lays a solid foundation for future improvements and suggests a scalable model that could be applied to other sectors within the country to further enhance agricultural practices and economic growth.

Pipeline leak detection and localization based on the flow balance and negative pressure wave methods

The traditional water supply pipeline leak detection and location method has problems of false alarms, low positioning accuracy, and low stability. This paper focuses on the pipeline leak detection and location experimental platform to investigate water supply pipeline leaks, followed by simulation and experimental validation. This study integrates the mass flow balance method and pressure change inflection points to determine pipeline leaks and introduces an improved negative pressure wave method for locating leakage points. The results demonstrate that the system accurately detects pipeline leaks. The average positioning error of the improved negative pressure wave method for the leakage point is 4.76%, which has good stability and high positioning accuracy.

APPROVISIONNEMENT EN EAU ET SANTE DES POPULATIONS RURALES: LE CAS DATTEHOU (AGBOVILLE-COTE DIVOIRE)

Water is a vital element for human life. It is available in Attehou, although its supply constitutes a problem for the population. The objective of this present study is to highlight the influence of the issue of water supply on the health of the population of Attehou. The methodology is based on the use of documents, field observation, interviews, the use of reports from the Information and Management Systems (GIS) of the Elevi health center and a field survey of 257 households. The processing of the data collected made it possible to obtain the following results. The population of Attehou uses traditional water supply methods (traditional wells, Wochi River, backwaters and the Agneby River) and a modern supply method (Village Hydraulic pumps). In the dry season, the population is subject to enormous supply difficulties which manifest themselves in the drying up of water sources, the regularity and long breakdown times of pumps, the inadequacy of modern infrastructure, a long time of water supply and use of unimproved sources. All these difficulties make the population vulnerable to water-borne diseases (diarrhea, typhoid fever, scabies, itchy skin and malaria).

Impacts of blending advanced treated water and traditional groundwater supply on lead and copper concentrations and microbial diversity in premise plumbing

In response to stresses on water demands, some regions augment conventional drinking water sources with alternative water supplies such as desalinated seawater and reclaimed wastewater. The advanced treatment of wastewater by reverse osmosis, microfiltration, and advanced oxidation processes can produce high quality water for potable uses. However, if not appropriately stabilized, the resulting water can be corrosive to metal-based distribution pipes and plumbing materials. We conducted long-term premise plumbing pipe loop experiments with copper pipes containing lead solder to test the impact of the introduction of advanced treated water on the water quality. Advanced treated water (ATW) originally at low pH (<7) and low alkalinity (<10 mg/L as CaCO3) was stabilized with a calcite contactor before being blended with baseline ground water (BLW). The effects of percentages of ATW on the release of lead and copper and on the changes in the microbial diversity were monitored. Experiments monitored metal release from pipes receiving (1) only BLW, (2) a series of blends of BLW and ATW that gradually increased from 25 % to 100 % ATW, and (3) an abrupt switch from BLW to 100 % ATW. Introducing 100 % ATW dramatically increased lead release and simultaneously decreased copper release. Pipe scale analysis showed that the introduction of ATW had destabilized sulfate-containing pipe scales, which exposed the copper pipe surface to galvanic corrosion. The dissolution of scale material was associated with a significant decrease in sulfate concentration in the 100 % ATW which was in agreement with theoretical solubility calculations. The impact of blending ATW on microbial diversity was studied via 16S rRNA gene amplicon sequencing. The composition of the microbial communities changed significantly after water was in contact with the copper pipes in experiments with both BLW and ATW. The type of water recirculating in the pipes affected the structure of the microbial community. The results from this study can be useful for water utilities that are considering potable reuse as they develop strategies to mitigate any adverse impacts of water quality changes.

Leveraging blockchain for sustainable supply chain management: A data privacy and security perspective

This review examines how blockchain technology can be leveraged to enhance data privacy and security in sustainable supply chain management (SSCM). As global supply chains become increasingly complex and the demand for sustainability grows, ensuring data privacy and security has become a critical concern. Traditional supply chain systems often face challenges such as data breaches, lack of transparency, and difficulty in tracing products and materials. Blockchain technology, with its decentralized, immutable, and transparent architecture, offers a promising solution to these challenges. Blockchain can enhance data security by ensuring that data is tamper-proof, traceable, and encrypted, thus protecting sensitive information across the supply chain. It provides transparency while allowing permissioned access, ensuring that stakeholders can verify data without exposing confidential information. Furthermore, privacy-preserving technologies such as zero-knowledge proofs and homomorphic encryption allow verification of data without compromising its security. Smart contracts enable automated compliance with regulatory frameworks like GDPR, reducing the risk of human error and improving operational efficiency. The integration of blockchain in SSCM can improve traceability, transparency, and accountability, thereby promoting environmental and social sustainability. By tracking the origin and journey of goods, blockchain helps verify ethical sourcing practices and reduce carbon footprints. However, the technology also presents challenges, including scalability, integration with legacy systems, and cost considerations. Through case studies in industries such as food, textiles, and renewable energy, this review highlights the practical applications and benefits of blockchain for SSCM. It concludes that blockchain has the potential to revolutionize supply chain operations, but careful consideration must be given to overcoming its technical and financial barriers to widespread adoption.

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.

COLLABORATIVE SUPPLY CHAIN MANAGEMENT IN THE SHARING ECONOMY: AN EMPIRICAL RESEARCH

This study examines the impact of the sharing economy on collaborative supply chain management among Turkish international trade firms. The sharing economy, which involves temporary access to underutilized resources via digital platforms, has challenged traditional supply chain models, necessitating resilient and flexible collaborations. The research utilizes the Inter-organizational Relationships (IOR), Unified Theory of Acceptance and Use of Technology (UTAUT), and Resource-Based View (RBV) frameworks, highlighting dynamic capabilities. Through structural equation modeling and expert interviews, the findings reveal that trust and information sharing are essential, but their effects on e-collaboration are complex. Trust negatively correlates with e-collaboration, indicating that electronic platforms may mediate trust in low-trust environments. On the other hand, performance expectancy and facilitating conditions significantly boost e-collaboration adoption. The study identifies e-collaboration as a dynamic capability, improving operational performance, customer/supplier satisfaction, growth, and profitability. This research contributes theoretically by integrating organizational and individual perspectives on e-collaboration and elucidates the intricate relationships between trust, information sharing, and technology in supply chains. Practical recommendations are provided for leveraging technological innovations to enhance trust and information sharing in collaborative supply chains.

A Bibliometric Analysis on Visualising and Mapping Green Supply Chain Management

The emergent field of green supply chain management (GSCM) has recently piqued the interest of both academics and practitioners, owing to its crucial role in integrating sustainable environmental processes into the traditional supply chain. An essential research goal is to understand the overall structure of research and what has been completed in the area so far to build a strong research program to address forthcoming GSCM problems. The purpose of conducting a bibliometric analysis of GSCM in its current state is to gain insights into the existing body of knowledge, identify trends, and understand the research landscape. Several literature reviews concentrating on certain elements of GSCM have been published from 2002 to 2021 (data update time is April 10, 2021). Thus, this study used a bibliometric method to examine the present level of research on the GSCM. The Scopus database, one of the world-leading publishers-independent global citation databases, was used to search for documents related to GSCM. A bibliometric tool called Bibliometrix was executed to examine the data collected from the search, which generated 717 documents. This software was used to build maps based on scientific publication network data, revealing relationships between researchers, countries, and journals. This comprehensive mapping of the field serves to graphically depict the evolution of publications over time as well as identify current research interests. Finally, the findings of the bibliometric analysis point out a growing trend in green supply chain studies around the world, indicating that people are becoming more conscious of the need for environmental management and protection, and sustainable development.

Optimizing the Agricultural Supply Chain Through the Internet + Model: Enhancing Efficiency with a Case Study of TikTok

This study uses the TikTok platform as a case study to explore the application of the Internet+ model in the agricultural supply chain and analyses the impact of Internet+ model on improving supply chain efficiency and reducing costs. With the development of science and technology, Internet+ has become an important trend in modern industry, which deeply integrates traditional agriculture with information technology and promotes the innovation and efficiency of supply chain management. This study not only discusses the practical application of the Internet + model in agriculture but also proposes to solve the bottlenecks in the traditional agricultural supply chain using logistics informatization, intelligent scheduling system, cold chain monitoring and intelligent warehouse management. Through case studies, the effectiveness of Internet technology in optimizing the supply chain, improving the circulation efficiency of agricultural products and reducing costs are verified, providing theoretical and case study support for promoting the development of agricultural modernization.

What is the impact of demand patterns on integrated online-offline and buy-online-pickup in-store (BOPS) retail in a smart supply chain management?

Retailers aim to provide in-person and remote interactions to accelerate purchases through hybrid methods, which introduce additional delivery and emissions loads but create a seamless shopping experience. The challenges of unified inventory, customer information, pricing, demand forecasting complications, and order fulfillment are met successfully in the hybrid methods. Here, a smart supply chain management that integrates traditional physical presence with cloud-based and hybrid buy-online-pickup in-store channels is optimized to meet customer demand in different demand patterns. The demand patterns considered are linear, cubic, and normalized functions of the selling price, the advertising cost, and the product lifetime. The article incorporates sustainable supply chain and omnichannel strategies to optimize supply chain performance and profitability. The paper compares the results of the proposed models with traditional supply chain models and provides some managerial insights and suggestions for online retailers. Numerical simulation reveals that nonlinear price dependence in demand provides an opportunity for higher promotional investment with a substantial rise in optimal selling price and overall profit. The shift-to-imperfect probability is seen to be the volatile component in the solution surface. The markup of the offline channel has a greater impact than buy-online-pickup in-store markup.

Economic Substantiation of Innovative Solutions for Direct Cooperation between Manufacturers and Restaurants

The traditional supply chain management between manufacturers and restaurants is not effective enough, considering its high costs, long turnaround times and reliance on third parties, which creates challenges to profitability and agility. This study aims to find out how this system helps optimise costs and supply chain management within the restaurant industry. Data was obtained through manager interviews for some middling and high-end restaurants presenting some operational issues confronted before and after the system was installed. A sample of 50 restaurants was selected using a stratified sampling technique, targeting various restaurant categories. A structured questionnaire was designed to interview restaurant managers on operational efficiency, cost reduction, and supply chain performance. The logistics costs, transaction costs and overall efficiency improvements, among other quantitative metrics, were monitored for the first and second intervals. To achieve this, the analysis used a difference-in-difference methodology, where restaurants before and after the implementation of the system were compared concerning specific performance indicators.Data was processed using SPSS Statistics 27, ensuring accuracy and reliability in the analysis. The findings show that wastage management cost efficiency has improved to 15%, while significant decreases have also been observed regarding transaction time and logistics costs. This also resulted in a substantial decline in time-to-order delivery which positively influences operational speed. Based on these findings, it is suggested that direct trade models would benefit the restaurant business in terms of cost savings and enhanced performance. The policy recommendations include promoting digital supply chain platforms using tax credits, assisting SMEs with government-sponsored projects, and facilitating direct interaction between producers and consumers.

Towards autonomous supply chains: Definition, characteristics, conceptual framework, and autonomy levels

Recent global disruptions, such as the COVID-19 pandemic and the ongoing geopolitical conflicts, have profoundly exposed vulnerabilities in traditional supply chains, requiring exploration of more resilient alternatives. Among various solution offerings, Autonomous supply chains (ASCs) have emerged as key enablers of increased integration and visibility, enhancing flexibility and resilience in turbulent trade environments through the widespread automation of low level decision making. Although ASC solutions have been discussed and trialled over several years, they still lack well-established theoretical foundations. This paper addresses this research gap by presenting a formal definition of ASC along with its defining characteristics and auxiliary concepts. We propose a layered conceptual framework, called the MIISI model. An illustrative case study focusing on the meat supply chain demonstrates an initial ASC implementation based on this conceptual model. Furthermore, we introduce a seven-level supply chain autonomy reference model, delineating a trajectory towards achieving full supply chain autonomy. Recognising that this work represents an initial endeavour, we emphasise the need for continued exploration in this emerging domain. This work is designed to stimulate further research, both theoretical and technical, and contribute to the continual evolution of ASCs.

A Study on The Dominance of Digital Transaction Over M3 Money Supply Transactions

The financial landscape is evolving increasingly with digital transactions dominating traditional M3 money supply transactions. Given the growth of digital payments, fintech innovations and cryptocurrencies, there is an urgent need to understand the degree to which these electronic transactions have now surpassed or altered conventional M3 money supply operations. In this study, we seek to fill that gap with our understanding and direction forwards. By investigating the effect on financial stability, economic growth and the overall resilience of monetary systems, this research opens up new avenues for analysis in an ongoing dialogue about how digital transformation has been affecting financial transactions and its wider implications for the money landscape.

Research on Supply Chain Optimization and Management Based on Deep Reinforcement Learning

This research introduces a groundbreaking approach to supply chain optimization and management, termed as Deep Reinforcement Learning based Supply Chain Optimization and Management (DRL-SCOM). At the core of this approach is the utilization of advancements in Deep Reinforcement Learning (DRL), specifically through the integration of Randomized Ensembled Double Q-learning (REDQ) and Trust Region Policy Optimization (TRPO). DRL-SCOM is designed to effectively tackle the inherent complexities and dynamic challenges that are characteristic of supply chain management. One of the key strengths of DRL-SCOM lies in its use of REDQ, which plays a crucial role in mitigating the overestimation bias commonly associated with traditional Q-learning methods. This results in more accurate value estimation and policy improvement, a critical factor in the effective management of supply chains. Additionally, the integration of TRPO into the framework brings the advantage of safe and stable policy updates. Such stability is vital for maintaining the robustness required in the fluctuating environment of supply chain operations. The combination of REDQ and TRPO in DRL-SCOM creates a powerful synergy. REDQ’s ensembled learning approach, when fused with TRPO’s trust-region method, enables the framework to efficiently navigate the complex and high-dimensional decision space typical of supply chains. This allows for real-time optimization of decisions while staying within operational constraints. The DRL-SCOM methodology shows significant potential in addressing various aspects of supply chain management, from demand forecasting and inventory management to logistics, adeptly handling the nonlinearities and uncertainties that are prevalent in these areas. Thus, the DRL-SCOM framework emerges as an innovative solution, pushing the frontiers of traditional supply chain management. It paves the way for a more agile, responsive, and intelligent system, equipped to adapt to changing market demands and operational challenges. This approach represents a significant stride towards transforming supply chain management into a more advanced, data-driven, and adaptive field.

Model of the non-stationary thermal processes in the ground heat pump system

One of the main directions for improving heat supply systems is the tendency to switch to low-temperature heating systems by using heat pump units is the tendency of implementation the low-temperature heating systems based on the use of heat pump units. In the work, the main attention is focused on the improvement of thermal parameters and circuit design features of elements of the heat pump system of heat supply using soil energy. For this purpose, the toolkit of mathematical modelling of processes in ground heat pumps is applied, taking into account the climatic conditions of Ukraine. The paper proves the technical possibility of creating an autonomous system of alternative heat supply for energy-saving technologies with the possibility of using ground energy, taking into account environmental requirements. It is substantiated that the use of the proposed systems is a promising direction for Ukraine, which is experiencing a shortage of its own energy resources, because it provides an opportunity to increase the share of organic fuel substitution and reduce the volume of heat emissions into the environment. A mathematical model of heat processes in the elements of the heat exchange equipment of the heat pump system based on renewable energy (soil energy) and secondary energy (wastewater) was developed, taking into account environmental requirements (preventing hypothermia of the soil during the operation of soil pipes and damage to vegetation, respectively), which allows choosing a rational mode of operation of the system under seasonal climatic changes and technological conditions. Numerical modelling of heat processes in elements of the heat exchange equipment of the heat pump system using groundwater and waste water was performed, and the energy and environmental efficiency of the system under variable climatic and technological factors was determined. Analysis and generalization of the calculation results of the heat pump heat supply systems using alternative energy based on the proposed mathematical model, taking into account environmental requirements (preventing thermal relaxation of the soil) allows to take into account the change in the temperature gradient around the soil heat exchanger and more accurately determine the heat flow from each section of the heat exchanger. It has been established that for heat pumps with soil heat exchangers, the maximum substitution ratio of the traditional fuel is 75 %, and the economically feasible quantity of soil heat exchangers is 9 units. Heat pumps using waste water can completely replace traditional heat supply systems. For individual consumers, it is possible to recommend heat pump units with soil heat exchangers, at the same time, it is necessary to provide a backup source of energy to increase the reliability of heat supply.

Optimal Financing Strategy in a Dual-Channel Supply Chain with Agricultural Product

This study models a two-stage agricultural supply chain consisting of a financially constrained manufacturer of agricultural products and a financially stable retailer. We examine two supply chain structures: traditional and dual channel. Our analysis centers on the effects of consumer green preferences, consumer sensitivity to the freshness of agricultural products, and substitution rate between green and non-green agricultural products on the profitability of supply chain members. The purpose of this work is to study the optimal financing strategy for companies producing both regular and organic products simultaneously. We analyze optimal financing strategies for the manufacturer using three models: bank financing, internal debt financing, and internal equity financing. Our results indicate that in both traditional and dual-channel supply chains, increased consumer green preferences or greater sensitivity to the freshness of agricultural products improve supply chain profitability, while a higher substitution rate between green and non-green products reduces profits. Additionally, the manufacturer prefers internal debt financing when consumer environmental awareness is low. Conversely, as consumer environmental awareness increases, internal equity financing becomes more profitable. These findings offer valuable insights for agricultural product manufacturers facing financial constraints, assisting them in selecting the most appropriate financing model.