Model system for educational management in supply chains

Challenges and Opportunities in Sustainable Supply Chains

Can We Connect? Benefits and Barriers to Adoption of Transformative Technology in Global Supply Chains

Mesoeconomics represents a critical intermediate layer of economic analysis, bridging the gap between microeconomics and macroeconomics. With the growing complexity of global supply chains, traditional economic frameworks and data analysis techniques have proven insufficient. The increasing availability and use of big data technologies have highlighted the relevance of mesoeconomic approaches in analyzing networked economic interactions across international supply chains. The research aims to explore how mesoeconomic frameworks can be effectively utilized to analyze global supply chain networks through big data analytics. It seeks to identify the advantages of applying mesoeconomic analysis in understanding the structure, flow, and dynamics of supply chains, as well as the challenges associated with data integration and analytics. The research employs a qualitative and conceptual analysis of mesoeconomic theory in the context of supply chains, supplemented by a review of current big data analytics methods used by companies. The analysis includes an examination of various data sources (primary and secondary), network structures, and classification techniques that support the processing and interpretation of large-scale data related to goods and services flows. The findings suggest that mesoeconomics, when combined with big data analytics, offers a robust framework for capturing the complexities of global supply chains. This approach enhances the understanding of relationships among products, producers, and processes, enabling more efficient and informed decision-making. However, challenges such as data quality, interoperability, privacy, and security remain significant barriers to the full realization of big data’s potential in supply chain analysis.

The article examines key issues in the business processes of large logistics companies and their impact on operational efficiency and financial performance. The relevance of the study is determined by the increasing complexity of global supply chains and the growing demand for cost-effective logistics solutions. Purpose. The novelty of the research lies in a comprehensive analysis that includes inaccurate inventory tracking, suboptimal planning, high transportation costs, and delays caused by documentation errors. The role of artificial intelligence (AI) and real-time tracking systems in optimizing logistics operations is described. Materials and methods. Industry reports and academic publications highlighting the potential of AI-driven automation in cost reduction and service quality improvement were discussed. Results. The main result of the study is the identification of key business process issues in large logistics companies, such as a lack of accurate information, inefficient planning, high costs, missed deadlines, and resource shortages. Effective solutions are proposed, including the use of real-time tracking systems and artificial intelligence to enhance operational efficiency and competitiveness. This article will be of interest to logistics professionals, supply chain managers, and researchers focused on digital transformation in transportation and warehousing.

The growing complexity of global supply chains and the rising demand for efficient logistics solutions have made Third-Party Logistics (3PL) services a strategic necessity for modern businesses. This study explores the impacts of 3PL services on a logistics company, focusing on four key dimensions: operational efficiency, cost reduction, service quality, and scalability. By collecting and analyzing primary data from internal stakeholders, the research evaluates how outsourcing logistics functions—such as transportation, warehousing, and inventory management—affects overall organizational performance. Statistical tools such as Chi-square tests, ANOVA, and Regression Analysis are employed to interpret relationships between key performance indicators and 3PL outcomes. The findings reveal that 3PL services significantly enhance operational flexibility and cost-effectiveness, while also improving delivery performance and customer satisfaction. However, the study also identifies certain challenges, such as coordination issues and risks associated with service dependency. The insights generated aim to guide logistics firms in making informed decisions regarding 3PL adoption, ensuring strategic alignment with organizational goals. KEYWORDS: Third-Party Logistics (3PL), Company Performance, Supply Chain Management, Logistics Outsourcing, Operational Efficiency, Cost Reduction, Service Quality, Technology Integration, Inventory Management, Transportation Services, Warehousing Solutions, Logistics Optimization, Business Competitiveness, Organizational Growth

The Impact of Sustainability on Triple-A Supply Chains

The paper presents possible solutions to small farmers in the agricultural sector in a small island setting grappling with challenges of enhancing their local industry and import substitution through a supply-demand chain framework. In 2005, Hawaiian farms produced approximately 363,200 kg of avocados. However, Hawaiian demand for these fruits required an additional 908,000 kg of avocados that were supplied through imports. At the same time, it is worth noting; almost 49% of locally produced avocados did not reach the market. These facts clearly suggest inefficiencies in the local avocado supply chain. Review of the literature on supply chain management suggests a sustainable avocado industry requires an integrated supply and demand chain management system. Hence, a modified conceptual model of supply-chain management called the Supply Demand Integrated Management (SDIM) model is proposed in this paper. Traditional supply chains contain three functional components: supply coordination, physical production and logistic management. In the new model, we propose adding R4D (Research for Development), a public good provided by the government to agricultural industries as an integral part of the supply-demand chain system. It articulates the significance of research and supply chain partnerships between small growers, industry groups, and public agencies. A well-integrated demand/supply chain in the avocado industry allows sharing of vital market information which can contribute to long-term strategic decisions that help local avocado growers increase their competitiveness against foreign imports. It also provides metrics in terms of consumer satisfaction, profitability, competitiveness, self-sufficiency, import substitution and sustainability. The SDIM model as applied to the avocado industry suggests two hypotheses relevant to the current situation. The hypotheses are: (1) There is a lack of coordination between what the farmers are growing and the chefs' (a high-end customer/buyer) preferences; (2) Forming an avocado farmer cooperative will enhance the profitability of local farmers. Survey data was collected from Hawaiian chefs and avocado farmers. Data was analysed using a Duncan multi-range test and a mathematical model, respectively, to test the hypotheses. The test revealed a lack of coordination between what the farmers are growing and buyer preferences. The results from the mathematical model suggested that formation of an avocado marketing cooperative would enhance the profitability of local farmers. Thus, the SDIM framework expands existing body of knowledge about supply chain management and provides useful information to local avocado growers that can help strengthen their supply and demand chain management.

Product Safety and the Food Supply Chain

Contributors

Implementation and adoption of new technologies are gaining the result of smooth supply chain and logistics operations. Internet of things (IoT) artificial intelligence, including data mining, intensified in all fields of life, particularly in supply chain management and operations. Blockchain technology has the capability to reform the supply chain and logistics operations management. Blockchain provides digital database solutions for all transactions across supply chain and operations management. Radio frequency identification device (RFID) is also helping technology transmit electromagnetic waves to radio-compatible integrated circuits to look after and manage the entire supply chain and logistics operations management. The Fourth Industry Revolution 4.0 refers to the automation, interconnectivity, machine learning, and real-time data that help supply chain and logistics operations management in the 21st century.

Maximizing supply chain performance leveraging machine learning to anticipate customer backorders

Purpose This study examines how green marketing strategies—environmental commitment, customer perceived value, green brand communication, and ethical sourcing—influence FMCG brand image. We'll examine how these components affect consumers' perceptions and boost brand image. Structured questionnaires were delivered to 255 FMCG consumers using convenience sampling. Data analysis and hypothesis testing were done using SEM. Design/methodology/approach Sustainability and environmental responsibility boost company image, according to research. Value was a key aspect, showing how consumers value sustainable product benefits. Effective green brand marketing and ethical sourcing policies boost consumers' trust and loyalty. FMCG firms looking to include sustainable practices into their marketing strategies can learn from the study about the importance of authenticity in green communication and responsible sourcing for brand growth. Findings The findings of research on Green Marketing Strategies and Brand Image in the context of FMCG (Fast-Moving Consumer Goods) generally focus on how environmental commitment, consumer perceived value, green brand communication, and ethical sourcing contribute to shaping brand image and influencing consumer behavior. Strong Positive Influence on Brand Image: Brands that are committed to environmental sustainability are often viewed more positively by consumers. This commitment can improve the brand’s reputation, as consumers are increasingly looking for eco-friendly practices in the brands they support. Originality Environmental commitment, ethical sourcing, green brand communication, and sustainable product offerings play a critical role in enhancing brand image and fostering long-term consumer loyalty. However, brands must ensure transparency and avoid greenwashing to maintain credibility. Overall, a well-executed green marketing strategy can create a strong, positive brand image that resonates with eco-conscious consumers and contributes to the brand’s success in competitive markets. Many consumers today consider the ethical sourcing of products to be just as important as the quality of the product itself. Research limitations/implications Mismatched Claims and Impact: Many FMCG brands may make environmental claims that don’t align with their actual environmental impact. This misalignment can lead to consumer disillusionment, but measuring the true environmental benefits of green initiatives can be complex. Difficulty in Measuring Full Environmental Impact: It's often challenging for researchers to measure the actual environmental impact of a product’s lifecycle—from sourcing to production to disposal—due to the complexity of global supply chains in the FMCG sector. Practical implications While research on green marketing strategies and brand image in the FMCG sector provides valuable insights, there are several limitations that hinder its generalizability and long-term applicability. These include challenges in measuring the true effectiveness of green marketing strategies, consumer perception variability, the complexity of global supply chains, and difficulties in defining and quantifying "green" practices. To overcome these limitations, future research should focus on longitudinal studies, standardized metrics for green marketing success, and the integration of cultural and regional differences in consumer behavior. Social implications The social implications of Green Marketing Strategies and Brand Image in the context of FMCG (Fast-Moving Consumer Goods) are significant, as they shape how brands interact with society, influence consumer behavior, and contribute to broader environmental and social changes. Green marketing not only affects consumer perceptions but also impacts society in various ways, including ethical, social, and cultural dimensions. Below are some of the key social implications of green marketing strategies and brand image in the FMCG sector

The demand and supply chain planning process for manufacturers, distributors, and retailers has evolved over the years. It has gone from a disjointed, unconnected, slow, inaccurate, fairly manual set of processes to an integrated, timely process enabled by the use and coordination of highly trained people, lean, agile processes, and cutting-edge technology. To make this set of processes work effectively, one has to fully understand and appreciate that there is an "art and science" aspect to the process which can take years of education and experience to fully understand. Essentially, this book will offer the reader a chance to fully understand the interconnected set of processes in a "best-practice" application. Furthermore, examples and cases will be used to illustrate its practical application in today’s complex global supply chain. In addition, readers will understand and be able to apply and articulate the concepts, tools, and techniques used in the efficient supply of goods and services in today’s changing global economy. It will help them to learn how businesses, through their supply chain, work both internally and with their trading partners – both upstream and downstream – to build strong relationships and integrate demand and supply planning activities across the supply chain to deliver customer value efficiently and effectively. They will learn about the tools and technologies enabling integration, and the critical drivers and key metrics of supply chain performance.

This chapter presents an exploratory qualitative study on the use of artificial intelligence (AI) in supply chain management (SCM). With the growing complexity and uncertainty of supply chains, the integration of AI has gained increased attention as a potential solution for enhancing SCM. Using semi-structured interviews with experts in the field, this study investigates the application of AI for supply chain optimization, as well as the challenges that firms face in implementing such technologies. The results of this study reveal that AI-based SCM systems have the potential to enhance supply chain efficiency, reduce costs, and improve overall performance. However, challenges such as data quality and compatibility, organizational resistance to change, and lack of trust in AI technology were identified as barriers to successful implementation. These findings contribute to the understanding of the current state and future direction of AI in SCM, and provide practical implications for managers seeking to use AI-based solutions in their supply chain operations.

Business executives have recently indicated that supply chain disruptions represent a major threat to their firm’s profitability and revenue growth (Smyrlis, 2006; Hendricks and Singhal, 2009). In the literature, a number of conceptual studies have suggested that supply chain complexity is a main driver of supply chain disruptions (Choi & Krause, 2006; Christopher & Lee, 2004; Juettner et al., 2003). Other studies have suggested that the degree of coupling in the supply chain is a major determinant of supply chain disruptions (Agrawal and Nahimias, 1997; Ahuja, 2000). Building on the theoretical foundation of Normal Accident Theory (NAT), this paper proposes a nuanced relationship between supply chain complexity and coupling and their collective impact on supply chain disruptions. Through an empirical examination, we seek to validate the theoretical proposition that complex, tightly coupled systems are inherently prone to failures or accidents. This study contributes significantly to the supply chain management discourse, providing a detailed analysis of the mechanisms underlying supply chain vulnerabilities and offering practical guidance for developing more resilient and responsive supply chain systems. Our findings invite future research to further explore the intricacies of supply chain disruptions, complexity, and coupling, aiming to refine and expand upon the mitigation strategies discussed herein.