Supply Chain Management Applications Research Articles

The scientific legacy of professor Y.V. Krykavskyi: development of logistics theory in Ukraine and future perspectives

The article presents the first attempt at scientometric analysis of the scientific legacy of the prominent Ukrainian scholar, Doctor of Economic Sciences, Professor Yevhen Vasylovych Krykavskyi. The main stages of his scientific work and its impact on the development of the general theory and practice of logistic science in Ukraine are identified. It is demonstrated that Y.V. Krykavskyi himself formulated the theoretical foundations of logistics as a separate direction of scientific research in the field of economic sciences, established the basic conceptual framework, founded a scientific school of marketing and logistics, and trained a large number of candidates and doctors of sciences who continue and deepen the theoretical developments of the great scientist, as well as expand the spheres of practical application of logistic concepts, tools, and methods, and supply chain management in new economic conditions.

Resilience in supply chain management: lessons learned from disruptions like the COVID-19 pandemic

The ravaging impacts of the COVID-19 pandemic on global supply chains and its exposures of the vulnerabilities of the supply chain process has been examined in this paper. Importantly, the failure of supply chain resilience and the post-COVID-19 lessons necessitated the need to examine the need for resilience in supply chain management process. The paper examined the concept of resilience and its application in supply chain management, and covered strategies for developing resilience in supply chain management, which includes: identification and assessment of associated risks, diversification of supply chain channels, enhancing collaborations and effective communication among stakeholders, inventory management and supply chain flexibility, technology adoption and digitalization, scenario planning and simulations, as well as robust continuity planning. The paper also identified the challenges of supply chain resilience building. The paper provides valuable insights into how organizations can better handle future supply chain operations by considering the intrinsic development of resilience, which will enable them to better withstand and quickly recover from future disruptions.

The Role of Deep Learning in Supply Chain Collaboration and Cooperation

In today's globalized and technologically advanced business landscape, supply chain collaboration is crucial for enterprises seeking to gain a competitive edge, enhance operational efficiency, and adapt to market dynamics. Traditional methods often fall short in managing the complexities and rapid changes within supply chains. This study introduces an innovative deep learning model, combining BERT, GAT, and RL, to address these challenges effectively. The model demonstrates its prowess in processing supply chain data, accurately predicting market trends, and optimizing decision-making processes. By leveraging deep learning, this research not only expands theoretical applications in supply chain management but also provides practical tools to boost operational efficiency, highlighting the immense potential and practical value of deep learning technology in modern supply chain management.

Penerapan Supply Chain Management di PT Nippon Indosari Corpindo Tbk

This research discusses the application of Supply Chain Management (SCM) at PT Nippon Indosari Corpindo Tbk., one of the leading companies in the bakery industry in Indonesia. Focusing on enhancing operational efficiency and reducing production costs, this study explores how PT Nippon Indosari Corpindo Tbk. integrates advanced technology and Supply Chain Management strategies to maintain product quality while minimizing losses. Through the use of the Just In Time (JIT) concept, Advanced Planning & Optimization (APO) tool, and Radio Frequency Identification (RFID), the company has successfully improved inventory management, expedited distribution, and maximized customer satisfaction. The research findings show that effective SCM implementation has reduced the bullwhip effect, increased transparency in the flow of raw materials and finished products, and supported the sustainability of the company's operations. Thus, this study provides important insights into the benefits of SCM in the food and beverage industry, especially for companies operating on a large scale with dynamic market demands

Research on the Application of Green Supply Chain Management: Based on SCOR Model

This paper takes Apple Inc. as the research object and explores the green supply chain management issues based on the SCOR model. By combining the SCOR model through the theoretical framework and the characteristics of Apple's supply chain, management practice suggestions are made to reveal Apple's green performance in terms of environment, resources, and social responsibility. The study results show that Apple performs better in green procurement and marketing, but is slightly inferior in green recycling storage, and transportation. This provides valuable ideas for Apple's subsequent industrial sustainable development strategy, as well as lessons and references for other companies and industries, helping to promote the green development of the entire supply chain industry. In the future, it will be a key area to continue in-depth research on promoting and optimizing green supply chain practices in different industries and enterprises of different sizes.

Adaptive Supply Chain Risk Management Using AI Mitigating Disruptions and Enhancing Resilience in the Post-Pandemic Era.

The COVID-19 pandemic has starkly revealed the vulnerabilities within global supply chains, prompting the urgent need for enhanced risk management strategies. This paper explores the application of Artificial Intelligence (AI) in adaptive supply chain risk management to mitigate disruptions and enhance resilience in the post-pandemic era. By leveraging AI technologies such as machine learning, predictive analytics, and optimization algorithms, organizations can proactively identify, assess, and respond to risks in real-time, thereby fortifying their supply chains against unforeseen disruptions. [1] This paper reviews existing literature on supply chain risk management, AI applications in supply chain management, and post-pandemic supply chain challenges. Furthermore, it presents examples illustrating how AI-driven adaptive risk management approaches have been implemented successfully to navigate disruptions and improve supply chain resilience. Through this analysis, the paper aims to provide insights into the transformative potential of AI-enabled adaptive risk management strategies in building agile and robust supply chains for the future. DOI: https://doi.org/10.52783/tjjpt.v45.i02.6294

Examining the effect of Internet of Things (IoT) adoption on supply chain performance

Data is the heart of the Fourth Industrial Revolution. The growth of the Internet of Things is one of the main reasons behind this (IoT). The Internet of Things (IoT) is a network of interconnected physical items (sometimes known as "things") that are implanted with sensors, software, and other technologies to communicate and share data with other devices and systems over the Internet. However, research on IoT adoption in the supply chain domain is scarce, and its acceptance in industries is also very limited due to the various challenges that come with it. The objective of this study is to gain an understanding of the impact that IoT has on supply chain performance through its integration or adoption. A quantitative approach was pursued in this study, and a questionnaire survey of 200 respondents from the supply chain domain with managerial experience was collected and analyzed using the SPSS tool. The results indicate that IoT positively and significantly affects supply chain performance. Theoretically, this study contributes to the literature about supply chain integration and technologies. This research can help those who want to specialize in IoT and its applications in supply chain management. Organizationally, the research findings tell managers about the potential IoT investment that will lead to a positive supply chain performance outcome.

Blockchain Revolutionizing Supply Chain Management: A bibliometric review of emerging research trends and challenges

Blockchain technology has garnered substantial attention for promoting sustainability in economic, social, and environmental domains. This study employs a knowledge-based visualization approach to present an extensive review of blockchain-based supply chains. Examining 1276 articles from Scopus databases between 2016 and December 2022, the research utilizes bibliometric analysis and statistical techniques for data analysis. Notably, China and the United States lead the field, investigating the integration of blockchain with emerging technologies for applications in supply chain management, finance, intellectual property, digital currency, and transaction costs. This study provides a comprehensive overview, guiding future research in blockchain within management and economics.

Blockchain technology and supply chain performance: The role of trust and relational capabilities

Blockchain technology (BCT) has become a focal point of attention within the field of supply chain management (SCM), characterized as a transformative and disruptive technology capable of instilling transparency and trust. While parallels between BCT and the internet have been drawn, its practical application in SCM remains in an early stage, resulting in a limited body of literature and a pronounced debate with divergent perspectives concerning its impact in this SCM domain. Drawing upon the Relational View (RV) and Dynamic Capabilities View (DCV), this study aims to address this debate by investigating the role of BCT in enhancing supply chain performance. The study utilizes semi-structured interviews with 31 industry experts, followed by thematic analysis, to unveil the underlying mechanisms through which BCT influences supply chain performance. Our findings underscore the pivotal role of trust, facilitated by BCT features, in enhancing SC performance, emphasizing the interdependence of trust in technology, platforms, and SC members. Moreover, our study uncovers the substantial influence of supply chain uncertainty on the association between BCT and trust, acknowledging its pertinence in the modern business landscape. Additionally, we present a conceptual model that elucidates the relationships among BCT, trust, relational capabilities, and supply chain performance. Our qualitative investigation suggests that trust, relational capabilities, and dynamic capabilities sequentially mediate the association between BCT and supply chain performance. This research, while reaffirming the applicability of the original RV model in the context of BCT, contributes to a nuanced perspective by identifying additional associations within the relational view. Specifically, we identify knowledge sharing, effective governance, and resource complementarity as mediating factors in the relationship between relation-specific assets and relational rent. Our study provides practical advice to managers and practitioners. It stresses the need to understand how BCT impacts supply chain performance and the crucial role of trust. We also recommend nurturing relational capabilities in supply chain networks and considering the context-specific benefits of BCT, especially in uncertain environments. This understanding enables informed decision-making to tackle challenges and leverage opportunities.

Analysis and Application of Supply Chain Management for Cosmetic Inventory at Hayati Store Using PHP Programming Language and MYSQL Database

Analysis and Application of Supply Chain Management for Cosmetic Inventory at Hayati Store Using PHP Programming Language and MYSQL Database

Hamacher interaction aggregation operators for complex intuitionistic fuzzy sets and their applications in green supply chain management

A complex intuitionistic fuzzy (CIF) set contains the membership and non-membership in the shape of a complex number whose amplitude term and phase term are covered in the unit interval. Moreover, Hamacher interaction aggregation operators are the combination of two major operators, called Hamacher aggregation operators and interaction aggregation operators, and they are used to aggregate the collection of information into one value. In this manuscript, we present the concept of Hamacher interaction operational laws for CIF sets (CIFSs). Further, we develop the CIF Hamacher interaction weighted averaging (CIFHIWA) operator, CIF Hamacher interaction ordered weighted averaging (CIFHIOWA) operator, CIF Hamacher interaction weighted geometric (CIFHIWG) operator, and CIF Hamacher interaction ordered weighted geometric (CIFHIOWG) operator. For these operators, we also discuss some basic properties, such as idempotency, monotonicity, and boundedness. Additionally, we develop a MADM method based on the developed operators and apply it to solve the green supply chain management problems, which can implement environmentally friendly practices to minimize carbon emissions, resource consumption, and waste generation while promoting long-term sustainability. Finally, we verify the superiority and effectiveness of the proposed method based on a comparative analysis between the proposed techniques and existing methods.

The Adoption of Digital Technologies in Supply Chains in the Manufacturing Area

The Ongoing COVID pandemic has hampered economic activity; Food is a basic need that must be fulfilled and cannot be postponed. During the current pandemic, business people need to pay attention to the situation and conditions, especially the limitation of economic activity in several regions. However, Digital technologies have been extensively studied in academic research and industry. Moreover, little is known about adopting digital technologies in manufacturing firms at a supply chain level. This paper aims to understand why and how manufacturing firms adopt digital technologies and the impact of the adoption on supply chains. This research includes the design of a Web-based Supply Chain Management application to facilitate inventory management, starting from the process of ordering goods from suppliers and procurement of goods to managing goods to customers. Digital technology in the supply chain in the manufacturing area helps companies to store goods management data, raw materials, inventories, deliveries, and daily deposits, and others that are still using manual systems or not yet computerized to maximize performance and also profits for the company, suppliers, including end customers. The study identifies that technological intelligence and supply chain cooperation are critical factors and proposes two-dimensional levels of adopting digital technologies according to their low-to-high degrees.

Analisis Manajemen Rantai Pasok (Supply Chain Management) Guna Optimalisasi Distribusi Usaha Mikro Kecil Menengah Pengepulan Kepiting di Wilayah Tarakan

Supply chain management (SCM) is a strategy that refers to the internal activities of an organization and the number of businesses in the supply chain to support the long-term performance of the system and the entire supply chain. A lot of supply chain management is implemented, such as incorporating suppliers as colleagues in the raw material supply phase, building good relationships with customers for consumer enjoyment, and providing information to suppliers about product improvements. customers and competitive tactics for competitive advantage to measure performance levels to gain confidence in the quality of goods appropriate for the market. Therefore, in the crab collecting supply chain distribution model, it is best for supply chain members to agree on time, quantity and quality, so that the flow of products, finances and information is more organized. Crab collecting supply chain model where farmers distribute crabs to crab collectors, then crab collectors deliver crabs to retailers in traditional markets, then final consumers who enter the market then buy crabs directly from retailers. This research was conducted at Bering I Harbor, Selumit Pantai, Central Tarakan, Tarakan City, North Kalimantan at Pak Anwar's crab collection, the results will be analyzed through observation and interviews, so that information can be obtained whether the application of Supply Chain Management applied to the crab collection distribution system is optimal. or not yet.

Analisis Penerapan Halal Supply Chain Management dalam Meningkatkan Kepercayaan Konsumen UMKM Al-Izza

This article aims to analyze the application of Halal Supply Chain Management in increasing consumer confidence in UMKM Al-Izza products.The research method carried out is descriptive research with a qualitative approach. Data was collected through interviews with UMKM owners and consumers, as well as direct observation at production sites. This study concludes The implementation of halal supply chain management in UMKM Al-Izza includes a series of activities involving the provision of materials, including the stage of direct purchase of goods and storage of goods. The next step includes production activities that involve taking materials from storage warehouses, product production processes, and continued with distribution activities that include delivering products to sales locations and sales processes. Islamic consumers who consume UMKM Al-Izza products argue that halal products are very important, especially for Muslims, related to the belief that the products sold by UMKM Al-Izza are halal products because of clean sales places, clean safe production sites avoid haram substances, neat packaging and there are halal compositions and logos, and the ingredients used, and also Muslim-majority neighborhoods

Blockchain and Artificial Intelligence for Ensuring the Authenticity of Organic Legume Products in Supply Chains

Background: The increasing demand for organic legume products has raised concerns about the validity of supply chains. This research explores the integration of blockchain and Artificial Intelligence (AI) technologies as a robust solution for ensuring the accuracy of organic legume products in supply chains. Leveraging the immutable and transparent nature of blockchain, the study establishes a decentralized ledger to record and validate each stage of the supply chain, from crop husbandry to distribution. Methods: Artificial intelligence (AI) algorithms are used in tandem to examine data points and identify irregularities that can signal the existence of fake goods. Through the integration of various technologies, the research aims to offer an advanced and flexible system that can anticipate and detect any risks to the validity of the product. Smart contract implementation on the blockchain enables automated verification procedures assuring, adherence to organic norms and laws. Result: Through case studies and empirical evidence, this paper demonstrates the efficacy of the proposed blockchain and AI integration in mitigating the risks associated with counterfeit organic legume products. This research contributes to the burgeoning field of blockchain and AI applications in supply chain management, offering a novel approach to fortify the integrity of organic food supply chains.

Drone Applications in Logistics and Supply Chain Management: A Systematic Review Using Latent Dirichlet Allocation

Drone Applications in Logistics and Supply Chain Management: A Systematic Review Using Latent Dirichlet Allocation

Exploration of Carbon Emission Statistics and Management in the Supply Chain of Automobile Industry based on Blockchain Technology

This paper discusses the carbon emission statistics and management of the supply chain in the automobile industry based on Blockchain technology. It first analyzes the importance and challenges of carbon emission statistics in the supply chain of the automotive industry. Then, it introduces the basic principles and characteristics of Blockchain technology and describes its potential application in supply chain management. Then, a solution for carbon emission statistics and management in the supply chain of the automotive industry based on Blockchain technology is proposed, including the establishment of a Blockchain-based carbon emission data sharing platform, the realization of data transmission and verification in each link of the supply chain, and the establishment of a smart contract to achieve the carbon emission reduction target. Finally, the possible challenges and future development direction of the solution are discussed.

An efficient swarm intelligence approach to the optimization on high-dimensional solutions with cross-dimensional constraints, with applications in supply chain management.

The Swarm Intelligence Based (SIB) method has widely been applied to efficient optimization in many fields with discrete solution domains. E-commerce raises the importance of designing suitable selling strategies, including channel- and direct sales, and the mix of them, but researchers in this field seldom employ advanced metaheuristic techniques in their optimization problem due to the complexities caused by the high-dimensional problems and cross-dimensional constraints. In this work, we introduce an extension of the SIB method that can simultaneously tackle these two challenges. To pursue faster computing, CPU parallelization techniques are employed for algorithm acceleration. The performance of the SIB method is examined on the problems of designing selling schemes in different scales. It outperforms the Genetic Algorithm (GA) in terms of both the speed of convergence and the optimized capacity as measured using improvement multipliers.

Logistics Management System using Big Data Analytics

Nowadays, the e-commerce sector has emerged as a significant player in the current financial landscape. It offers a wide range of advantages for global customers, and given the increasing demand for various services and products, there is a pressing need for the development of efficient Web applications. This e-commerce application serves as the bridge between small businesses and their clientele. The application harnesses the capabilities of various technologies, including MongoDB for data storage, Node.js and Express.js for a fast and efficient backend, and HTML CSS for constructing a user-friendly interface for clients. This thesis underscores the proficiency of the (MongoDB, Express.js, HTML, CSS, Node.js) technology stack in the creation of a comprehensive e-commerce application with robust scalability options. The study delves into a meticulous development process, spanning from the backend to the frontend. The results unequivocally underscore the indispensable role in crafting a customizable Web application. We have also investigated the realm of big data analytics and its applications in logistics and supply chain management. It delves into innovative methods, practices, and prospects within this field. The articles within this collection scrutinize multiple avenues for enhancing big data analytics and its applications in logistics and supply chain management. These include the exploration of technology-centric tracking approaches, the examination of the correlation between financial performance and data-driven supply chains, as well as the assessment of implementation challenges and the maturity of supply chain capabilities in the context of big data.

An integrated Optimization Model of Product Mix, Assortment Packing, and Distribution in A Fashion Footwear Company

Recognizing the paramount importance of operational effectiveness and resource management in supply chain management (SCM) of the fashion industry, this study addresses a specific challenge faced by a prominent Indonesian fashion footwear company. The inefficiency is due to repetitive sorting and packaging processes during product distribution, which significantly impact optimal production mixes and product distribution from the distribution center to the point of sale. A crucial aspect is also the optimization of the delivery route. To address these challenges and minimize the total cost of ownership, the study proposes an integrated optimization model. This model simultaneously determines the optimal production quantity, assortment packaging, and distribution channels, taking into account decision variables related to distribution in configuration boxes, overload and underload products, as well as production numbers that respond to store-specific demand fluctuations. A notable contribution of this research is the integration of product mix decisions into the assortment packaging and distribution model, which represents a novel approach. The optimal solution determined using the LINGO 18.0 software highlights the significant influence of product penalty costs and product demand parameters on the objective function, while shipping costs have no noticeable influence. By emphasizing the integration of product mix decisions into the optimization framework, this research contributes significantly to improving the understanding and practical application of efficient supply chain management in the fashion industry.